GLM 5.3 pricing: real cost per million tokens
What Zhipu's GLM 5.3 really costs across 23 plans from 5 providers: monthly fees, usable allowances and real per-token prices, against the official API list price and independent leaderboards.
Data updated · How real prices are computed
As of 2026-10-08, the cheapest way to use GLM 5.3 is GLM Coding Pro (v2 ¥149) Off-peak at a real cost of about $0.00889 per million tokens ($21.98/month for roughly 2.472B tokens a month). We track 23 plans and API channels that serve GLM 5.3. Official API list price per million tokens: $0.26 cached input, $1.4 input, $4.4 output — about $0.3092 per million tokens on a standard workload mix.
- Lowest real price
- $0.00889/MTokGLM Coding Pro (v2 ¥149) Off-peak
- API list price
- $0.3092/MTokstandard workload mix
- Most monthly tokens
- 7.217BDroid Max
- Plans & APIs
- 2323 subscriptions · 0 metered APIs
Plot GLM 5.3 on the price–capability chart →
GLM 5.3 plans and real prices
Real price = monthly fee ÷ tokens you can actually use in a month. “vs API” shows how many times cheaper than the official API list price (standard workload mix) the plan is. “Evidence” opens the full calculation and sources for that row.
| Plan | Provider | Billing | Monthly fee | Monthly tokens | Real $/MTok | vs API | Confidence | Data date | |
|---|---|---|---|---|---|---|---|---|---|
| GLM Coding Pro (v2 ¥149) Off-peak | Zhipu | Subscription | $21.98/mo | 2.472B | $0.00889 | 34.8× | High | Evidence ↓ | |
| GLM Coding Pro (v2 ¥149) Midpoint | Zhipu | Subscription | $21.98/mo | 1.854B | $0.01186 | 26.1× | High | Evidence ↓ | |
| GLM Coding Max (v2 ¥469) Off-peak | Zhipu | Subscription | $69.19/mo | 5.769B | $0.01199 | 25.8× | High | Evidence ↓ | |
| GLM Coding Max (v2 ¥469) Midpoint | Zhipu | Subscription | $69.19/mo | 4.327B | $0.01599 | 19.3× | High | Evidence ↓ | |
| GLM Coding Lite (v2 ¥49) Off-peak | Zhipu | Subscription | $7.23/mo | 0.412B | $0.01754 | 17.6× | High | Evidence ↓ | |
| GLM Coding Pro (v2 ¥149) Peak | Zhipu | Subscription | $21.98/mo | 1.236B | $0.01778 | 17.4× | High | Evidence ↓ | |
| GLM Coding Lite (v2 ¥49) Midpoint | Zhipu | Subscription | $7.23/mo | 0.309B | $0.02339 | 13.2× | High | Evidence ↓ | |
| GLM Coding Max (v2 ¥469) Peak | Zhipu | Subscription | $69.19/mo | 2.884B | $0.02399 | 12.9× | High | Evidence ↓ | |
| GLM Coding Max (v3 ¥1078) Off-peak | Zhipu | Subscription | $159/mo | 5.769B | $0.02757 | 11.2× | High | Evidence ↓ | |
| Droid Max | Factory | Subscription | $200/mo | 7.217B | $0.02771 | 11.2× | Medium | Evidence ↓ | |
| GLM Coding Pro (v3 ¥538) Off-peak | Zhipu | Subscription | $79.37/mo | 2.472B | $0.03211 | 9.6× | High | Evidence ↓ | |
| GLM Coding Lite (v2 ¥49) Peak | Zhipu | Subscription | $7.23/mo | 0.206B | $0.03509 | 8.8× | High | Evidence ↓ | |
| GLM Coding Max (v3 ¥1078) Midpoint | Zhipu | Subscription | $159/mo | 4.327B | $0.03675 | 8.4× | High | Evidence ↓ | |
| GLM Coding Lite (v3 ¥118) Off-peak | Zhipu | Subscription | $17.41/mo | 0.412B | $0.04225 | 7.3× | High | Evidence ↓ | |
| GLM Coding Pro (v3 ¥538) Midpoint | Zhipu | Subscription | $79.37/mo | 1.854B | $0.04281 | 7.2× | High | Evidence ↓ | |
| GLM Coding Max (v3 ¥1078) Peak | Zhipu | Subscription | $159/mo | 2.884B | $0.05514 | 5.6× | High | Evidence ↓ | |
| GLM Coding Lite (v3 ¥118) Midpoint | Zhipu | Subscription | $17.41/mo | 0.309B | $0.05633 | 5.5× | High | Evidence ↓ | |
| GLM Coding Pro (v3 ¥538) Peak | Zhipu | Subscription | $79.37/mo | 1.236B | $0.06421 | 4.8× | High | Evidence ↓ | |
| GLM Coding Lite (v3 ¥118) Peak | Zhipu | Subscription | $17.41/mo | 0.206B | $0.0845 | 3.7× | High | Evidence ↓ | |
| Ollama Max | Ollama | Subscription | $100/mo | 0.97B | $0.1031 | 3× | Medium | Evidence ↓ | |
| Ollama Pro | Ollama | Subscription | $20/mo | 0.194B | $0.1031 | 3× | Medium | Evidence ↓ | |
| Command Code GOAT | Command Code | Subscription | $10/mo | 0.065B | $0.1546 | 2× | Medium | Evidence ↓ | |
| OpenCode Go | OpenCode | Subscription | $10/mo | 0.049B | $0.2062 | 1.5× | Medium | Evidence ↓ |
Behind each number
For every plan: the data date, the exact calculation, the quota basis, how leaderboard scores were mapped, and the original adoption evidence with its sources.
GLM Coding Pro (v2 ¥149) Off-peakZhipu$0.00889183/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00889183
- Monthly tokens
- 2,472,000,000 (2.472B)
- Quota confidence
- High
- Calculation
- $21.98 / month (¥149) ÷ 2,472,000,000 tokens × 1,000,000 ≈ $0.00889183 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 60000, off-peak coefficient 2×, weekly 618.1M ×4 weeks = 2.472B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Pro (v2 ¥149) MidpointZhipu$0.0118558/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0118558
- Monthly tokens
- 1,854,000,000 (1.854B)
- Quota confidence
- High
- Calculation
- $21.98 / month (¥149) ÷ 1,854,000,000 tokens × 1,000,000 ≈ $0.0118558 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 60000, midpoint coefficient 1.5×, weekly 463.6M ×4 weeks = 1.854B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Max (v2 ¥469) Off-peakZhipu$0.0119929/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0119929
- Monthly tokens
- 5,769,000,000 (5.769B)
- Quota confidence
- High
- Calculation
- $69.19 / month (¥469) ÷ 5,769,000,000 tokens × 1,000,000 ≈ $0.0119929 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 140000, off-peak coefficient 2×, weekly 1.4422B ×4 weeks = 5.769B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Max (v2 ¥469) MidpointZhipu$0.0159897/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0159897
- Monthly tokens
- 4,327,000,000 (4.327B)
- Quota confidence
- High
- Calculation
- $69.19 / month (¥469) ÷ 4,327,000,000 tokens × 1,000,000 ≈ $0.0159897 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 140000, midpoint coefficient 1.5×, weekly 1.0816B ×4 weeks = 4.327B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Lite (v2 ¥49) Off-peakZhipu$0.017545/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.017545
- Monthly tokens
- 412,000,000 (0.412B)
- Quota confidence
- High
- Calculation
- $7.23 / month (¥49) ÷ 412,000,000 tokens × 1,000,000 ≈ $0.017545 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 10000, off-peak coefficient 2×, weekly 103M ×4 weeks = 412M; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Pro (v2 ¥149) PeakZhipu$0.0177837/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0177837
- Monthly tokens
- 1,236,000,000 (1.236B)
- Quota confidence
- High
- Calculation
- $21.98 / month (¥149) ÷ 1,236,000,000 tokens × 1,000,000 ≈ $0.0177837 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 60000, peak coefficient 1×, weekly 309M ×4 weeks = 1.236B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Lite (v2 ¥49) MidpointZhipu$0.0233933/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0233933
- Monthly tokens
- 309,000,000 (0.309B)
- Quota confidence
- High
- Calculation
- $7.23 / month (¥49) ÷ 309,000,000 tokens × 1,000,000 ≈ $0.0233933 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 10000, midpoint coefficient 1.5×, weekly 77.3M ×4 weeks = 309M; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Max (v2 ¥469) PeakZhipu$0.0239901/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0239901
- Monthly tokens
- 2,884,000,000 (2.884B)
- Quota confidence
- High
- Calculation
- $69.19 / month (¥469) ÷ 2,884,000,000 tokens × 1,000,000 ≈ $0.0239901 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 140000, peak coefficient 1×, weekly 721.1M ×4 weeks = 2.884B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Max (v3 ¥1078) Off-peakZhipu$0.0275659/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0275659
- Monthly tokens
- 5,769,000,000 (5.769B)
- Quota confidence
- High
- Calculation
- $159 / month (¥1078) ÷ 5,769,000,000 tokens × 1,000,000 ≈ $0.0275659 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 140000, off-peak coefficient 2×, weekly 1.4422B ×4 weeks = 5.769B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
Droid MaxFactory$0.027712/MTok
- Data date
- 2026-09-29 · derived; uses the data date of Droid Max · claude-opus-5.5
- Real price / MTok
- $0.027712
- Monthly tokens
- 7,217,100,000 (7.217B)
- Quota confidence
- Medium
- Calculation
- $200 / month ÷ 7,217,100,000 tokens × 1,000,000 ≈ $0.027712 / MTok
- Quota basis
Anthropic workload: 97% cache reads / 2.5% cache writes / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
Derived from same-plan claude-opus-5.5 2.526B × 2.857142857142857
Factory official multipliers Opus 5.5 1.6× / glm-5.3 0.56×: the same Standard Usage pool scaled by multiplier — not a measurement of this model; inherits the Opus 5.5 row's Anthropic-tier workload, not recomputed for each model's own price gap; docs.factory.ai/docs/models; droid-model-multipliers-2026-09-29.json; Droid Core models draw Standard Usage first, then a separate free open-source pool applies (independent cap unmeasured); this value counts only the Standard Usage part
droid-model-multipliers-2026-09-29.jsonBrowse the public evidence archive
GLM Coding Pro (v3 ¥538) Off-peakZhipu$0.0321061/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0321061
- Monthly tokens
- 2,472,000,000 (2.472B)
- Quota confidence
- High
- Calculation
- $79.37 / month (¥538) ÷ 2,472,000,000 tokens × 1,000,000 ≈ $0.0321061 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 60000, off-peak coefficient 2×, weekly 618.1M ×4 weeks = 2.472B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Lite (v2 ¥49) PeakZhipu$0.0350899/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0350899
- Monthly tokens
- 206,000,000 (0.206B)
- Quota confidence
- High
- Calculation
- $7.23 / month (¥49) ÷ 206,000,000 tokens × 1,000,000 ≈ $0.0350899 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 10000, peak coefficient 1×, weekly 51.5M ×4 weeks = 206M; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Max (v3 ¥1078) MidpointZhipu$0.0367524/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0367524
- Monthly tokens
- 4,327,000,000 (4.327B)
- Quota confidence
- High
- Calculation
- $159 / month (¥1078) ÷ 4,327,000,000 tokens × 1,000,000 ≈ $0.0367524 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 140000, midpoint coefficient 1.5×, weekly 1.0816B ×4 weeks = 4.327B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Lite (v3 ¥118) Off-peakZhipu$0.0422511/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0422511
- Monthly tokens
- 412,000,000 (0.412B)
- Quota confidence
- High
- Calculation
- $17.41 / month (¥118) ÷ 412,000,000 tokens × 1,000,000 ≈ $0.0422511 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 10000, off-peak coefficient 2×, weekly 103M ×4 weeks = 412M; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Pro (v3 ¥538) MidpointZhipu$0.0428081/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0428081
- Monthly tokens
- 1,854,000,000 (1.854B)
- Quota confidence
- High
- Calculation
- $79.37 / month (¥538) ÷ 1,854,000,000 tokens × 1,000,000 ≈ $0.0428081 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 60000, midpoint coefficient 1.5×, weekly 463.6M ×4 weeks = 1.854B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Max (v3 ¥1078) PeakZhipu$0.0551413/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0551413
- Monthly tokens
- 2,884,000,000 (2.884B)
- Quota confidence
- High
- Calculation
- $159 / month (¥1078) ÷ 2,884,000,000 tokens × 1,000,000 ≈ $0.0551413 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 140000, peak coefficient 1×, weekly 721.1M ×4 weeks = 2.884B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Lite (v3 ¥118) MidpointZhipu$0.0563348/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0563348
- Monthly tokens
- 309,000,000 (0.309B)
- Quota confidence
- High
- Calculation
- $17.41 / month (¥118) ÷ 309,000,000 tokens × 1,000,000 ≈ $0.0563348 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 10000, midpoint coefficient 1.5×, weekly 77.3M ×4 weeks = 309M; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Pro (v3 ¥538) PeakZhipu$0.0642122/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0642122
- Monthly tokens
- 1,236,000,000 (1.236B)
- Quota confidence
- High
- Calculation
- $79.37 / month (¥538) ÷ 1,236,000,000 tokens × 1,000,000 ≈ $0.0642122 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 60000, peak coefficient 1×, weekly 309M ×4 weeks = 1.236B; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
GLM Coding Lite (v3 ¥118) PeakZhipu$0.0845023/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0845023
- Monthly tokens
- 206,000,000 (0.206B)
- Quota confidence
- High
- Calculation
- $17.41 / month (¥118) ÷ 206,000,000 tokens × 1,000,000 ≈ $0.0845023 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
docs.bigmodel.cn official weekly credits and three-tier credit coefficients; standard-token-mix-round1-2026-09-07.json
Unified standard workload; weekly credits 10000, peak coefficient 1×, weekly 51.5M ×4 weeks = 206M; peak/valley midpoint no longer used; exchange rate 1 USD = 6.7787 CNY (2026-09-04 CNY central parity rate; old rate 7.2); CNY monthly fee divided by the rate to get USD; https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.html
https://www.xinhuanet.com/20260904/4c1ce1cbf39d416997cb9c237d6f5024/c.htmlstandard-token-mix-round1-2026-09-07.jsonBrowse the public evidence archive
Ollama MaxOllama$0.103072/MTok
- Plan
- Ollama Max · Ollama
- Data date
- 2026-09-06 · official source date
- Real price / MTok
- $0.103072
- Monthly tokens
- 970,200,000 (0.97B)
- Quota confidence
- Medium
- Calculation
- $100 / month ÷ 970,200,000 tokens × 1,000,000 ≈ $0.103072 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
https://ollama.com/pricing official usage credits and three-part pricing; https://ollama.com/blog/transparent-pricing; code-subscriptions-round1-2026-09-06.json; ollama-deepseek-v41-round1-2026-09-11.json
Added 970.2M: shared monthly pool $300 ÷ project standard-workload weighted price; official three-part pricing. Allowances of different models in the same plan are not additive (assuming the shared pool is used up on a single model); no usage-panel token+% screenshot — computed from official absolute credits and the price list
https://ollama.com/pricinghttps://ollama.com/blog/transparent-pricingcode-subscriptions-round1-2026-09-06.jsonollama-deepseek-v41-round1-2026-09-11.jsonBrowse the public evidence archive
Ollama ProOllama$0.103093/MTok
- Plan
- Ollama Pro · Ollama
- Data date
- 2026-09-06 · official source date
- Real price / MTok
- $0.103093
- Monthly tokens
- 194,000,000 (0.194B)
- Quota confidence
- Medium
- Calculation
- $20 / month ÷ 194,000,000 tokens × 1,000,000 ≈ $0.103093 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
https://ollama.com/pricing official usage credits and three-part pricing; https://ollama.com/blog/transparent-pricing; code-subscriptions-round1-2026-09-06.json; ollama-deepseek-v41-round1-2026-09-11.json
Added 194M: shared monthly pool $60 ÷ project standard-workload weighted price; official three-part pricing. Allowances of different models in the same plan are not additive (assuming the shared pool is used up on a single model); no usage-panel token+% screenshot — computed from official absolute credits and the price list
https://ollama.com/pricinghttps://ollama.com/blog/transparent-pricingcode-subscriptions-round1-2026-09-06.jsonollama-deepseek-v41-round1-2026-09-11.jsonBrowse the public evidence archive
Command Code GOATCommand Code$0.15456/MTok
- Data date
- 2026-09-30 · official source date
- Real price / MTok
- $0.15456
- Monthly tokens
- 64,700,000 (0.065B)
- Quota confidence
- Medium
- Calculation
- $10 / month ÷ 64,700,000 tokens × 1,000,000 ≈ $0.15456 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
https://commandcode.ai/docs/plans/goat official per-model allowance and three-part pricing; https://commandcode.ai/pricing; $10->$70 credits; code-subscriptions-round1-2026-09-06.json; goat-opencode-catalogs-round3-2026-09-30.json
Added 64.7M: min(shared monthly pool $70, model allowance $20) ÷ project standard-workload weighted price; official three-part pricing; New models default $20. Processing fee ignored; allowances of different models in the same plan are not additive; no usage-panel token+% screenshot — computed from official absolute credits and the price list
https://commandcode.ai/docs/plans/goathttps://commandcode.ai/pricing;code-subscriptions-round1-2026-09-06.jsongoat-opencode-catalogs-round3-2026-09-30.jsonBrowse the public evidence archive
OpenCode GoOpenCode$0.206186/MTok
- Plan
- OpenCode Go · OpenCode
- Data date
- 2026-09-30 · official source date
- Real price / MTok
- $0.206186
- Monthly tokens
- 48,500,000 (0.049B)
- Quota confidence
- Medium
- Calculation
- $10 / month ÷ 48,500,000 tokens × 1,000,000 ≈ $0.206186 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.26 / $1.4 / $4.4 · standard-load blended ≈ $0.3092/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (2 configurations)
Terminal-Bench 4.0: Low (1 configuration)
Terminal-Bench 4.0 (AA): Low (2 configurations)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): Low (1 configuration)
Artificial Analysis Coding Agent Index v1.5: Low (1 configuration)
DeepSWE v1.1: Low (1 configuration)Mapping confidence: how directly each score refers to the model served here.
Adoption evidence · source and rationale (translated from the Chinese record)
https://opencode.ai/docs/go/ official per-model Usage and three-part pricing; opencode-go-round5-2026-09-06.json; goat-opencode-catalogs-round3-2026-09-30.json
Old: 57.1M (request estimate)→48.5M: min(shared monthly pool $60, model Usage $15) ÷ project standard-workload weighted price; single official tier. The official request counts serve only as a cross-check and are no longer the primary allowance figure; allowances of different models in the same plan are not additive
https://opencode.ai/docs/go/goat-opencode-catalogs-round3-2026-09-30.jsonopencode-go-round5-2026-09-06.jsonBrowse the public evidence archive
GLM 5.3 benchmark scores
Highest archived configuration per leaderboard; ranks are among all models each board archives in this dataset. Scores are never mixed across boards.
| Leaderboard | Metric | Score | Rank | Configuration | Effort | Harness | Configs | Snapshot |
|---|---|---|---|---|---|---|---|---|
| Artificial Analysis Intelligence Index v4.3 | Intelligence Index | 44.78 | #14 / 60 | GLM-5.3 (max) | Max | — | 2 | 2026-10-01 |
| Terminal-Bench 4.0 | Resolution Rate % | 41.82 | #6 / 18 | Claude Code - GLM-5.3 (max) | Max | Claude Code | 1 | 2026-09-21 |
| Terminal-Bench 4.0 (AA) | Resolution Rate % | 41.92 | #9 / 53 | Artificial Analysis - GLM-5.3 (max) | Max | Artificial Analysis | 2 | 2026-10-01 |
| Code Arena | WebDev Overall | Arena Score | 1,622 | #15 / 54 | glm-5.3-max | Max | — | 1 | 2026-09-30 |
| Agent Arena · Overall (Ranking / Pareto) | Net Improvement % | 2.57 | #19 / 39 | GLM 5.3 (Max) | Max | — | 1 | 2026-09-30 |
| Artificial Analysis Coding Agent Index v1.5 | Coding Agent Index | 53.55 | #11 / 19 | Opencode - GLM-5.3 ({'reasoning_effort': 'max'}) | Max | Opencode | 1 | 2026-10-01 |
| DeepSWE v1.1 | Pass@1 % | 68.96 | #10 / 33 | mini-swe-agent - glm-5-3 (max) | Max | mini-swe-agent | 1 | 2026-09-03 |
Every archived configuration
Artificial Analysis Intelligence Index v4.3 2 configurations
| Configuration | Score | Score interval | Harness / effort / mode | Source task cost (mean / median) | Checked | Links |
|---|---|---|---|---|---|---|
| GLM-5.3 (max) | 44.7774 | — | — / Max / — | — / — | 2026-10-01 | Source · Archive |
| GLM-5.3 (low) | 34.299 | — | — / Low / — | — / — | 2026-10-01 | Source · Archive |
Terminal-Bench 4.0 1 configuration
| Configuration | Score | Score interval | Harness / effort / mode | Source task cost (mean / median) | Checked | Links |
|---|---|---|---|---|---|---|
| Claude Code - GLM-5.3 (max)Official Terminal-Bench 4.0 leaderboard row; score belongs to this harness × model × effort configuration. | 41.82 | 38.59 – 45.05 | Claude Code / Max / — | — / — | 2026-10-01 | Source · Archive |
Terminal-Bench 4.0 (AA) 2 configurations
| Configuration | Score | Score interval | Harness / effort / mode | Source task cost (mean / median) | Checked | Links |
|---|---|---|---|---|---|---|
| Artificial Analysis - GLM-5.3 (max)AA's own-harness independent measurement of Terminal-Bench 4.0 (the terminalBench40 field in the models-board payload, fraction×100); scored separately from the official tbench.ai board. | 41.9192 | — | Artificial Analysis / Max / — | — / — | 2026-10-01 | Source · Archive |
| Artificial Analysis - GLM-5.3 (low)AA's own-harness independent measurement of Terminal-Bench 4.0 (the terminalBench40 field in the models-board payload, fraction×100); scored separately from the official tbench.ai board. | 34.8485 | — | Artificial Analysis / Low / — | — / — | 2026-10-01 | Source · Archive |
Code Arena | WebDev Overall 1 configuration
Agent Arena · Overall (Ranking / Pareto) 1 configuration
Artificial Analysis Coding Agent Index v1.5 1 configuration
| Configuration | Score | Score interval | Harness / effort / mode | Source task cost (mean / median) | Checked | Links |
|---|---|---|---|---|---|---|
| Opencode - GLM-5.3Opencode - GLM-5.3 ({'reasoning_effort': 'max'})Score belongs to this named agent/harness × model configuration; it is not a harness-independent model measurement. indexScore stored as percent (raw fraction × 100). | 53.5548 | — | Opencode / Max / — | $4.241 / — | 2026-10-01 | Source · Archive |
DeepSWE v1.1 1 configuration
These are reference mappings, not benchmarks of a subscription or API channel. Harness and quota-measurement effort alignment are unverified. Source task costs are not subscription task costs.
- Exact served-model reference; quota-measurement effort is unverified.
- Exact served-model reference only; product harness and quota-measurement effort are unverified. Not a benchmark measurement of this subscription or API channel.
GLM 5.3 official API pricing
| Cached input | Input | Output |
|---|---|---|
| $0.26 | $1.4 | $4.4 |
Frequently asked questions
How much does GLM 5.3 really cost per million tokens?
Measured as monthly fee ÷ tokens you can actually use, GLM 5.3 ranges from $0.00889 (GLM Coding Pro (v2 ¥149) Off-peak) to $0.2062 (OpenCode Go) per million tokens.
Which subscription gives the most GLM 5.3 usage?
Droid Max allows roughly 7.217B tokens of GLM 5.3 per month for $200.
What is the official API price of GLM 5.3?
Official API list price per million tokens: $0.26 cached input, $1.4 input, $4.4 output — about $0.3092 per million tokens on a standard workload mix.
How does GLM 5.3 score on independent leaderboards?
GLM 5.3 has scores on 7 leaderboards; its strongest placement is 41.92 (Resolution Rate %) on Terminal-Bench 4.0 (AA), #9 of 53 models tracked.
Who makes GLM 5.3, and where can I use it?
GLM 5.3 (model ID glm-5.3) is made by Zhipu and is available through Command Code, Factory, Ollama, OpenCode, Zhipu.
More Zhipu models
| Model | Lowest real $/MTok | Cheapest plan | Plans |
|---|---|---|---|
| GLM 5.3 Flash | $0.00293 | GLM Coding Pro (v2 ¥149) Off-peak | 23 |
| GLM 5.2 | $0.02771 | Droid Max | 5 |
| GLM 5.2 Fast | $0.04157 | Droid Max | 2 |
| GLM 5.3 FlashX | $0.04413 | Command Code GOAT | 1 |
| GLM 5.1 | $0.07833 | Ollama Max | 3 |
| GLM 5 | $0.1175 | Command Code GOAT | 1 |