GLM 5.3 Flash pricing: real cost per million tokens
What Zhipu's GLM 5.3 Flash 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 Flash is GLM Coding Pro (v2 ¥149) Off-peak at a real cost of about $0.00293 per million tokens ($21.98/month for roughly 7.492B tokens a month). We track 23 plans and API channels that serve GLM 5.3 Flash. Official API list price per million tokens: $0.03 cached input, $0.15 input, $0.5 output — about $0.0353 per million tokens on a standard workload mix.
- Lowest real price
- $0.00293/MTokGLM Coding Pro (v2 ¥149) Off-peak
- API list price
- $0.0353/MTokstandard workload mix
- Most monthly tokens
- 67.36BDroid Max
- Plans & APIs
- 2323 subscriptions · 0 metered APIs
Plot GLM 5.3 Flash on the price–capability chart →
GLM 5.3 Flash 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 | 7.492B | $0.00293 | 12× | High | Evidence ↓ | |
| Droid Max | Factory | Subscription | $200/mo | 67.36B | $0.00297 | 11.9× | Medium | Evidence ↓ | |
| GLM Coding Pro (v2 ¥149) Midpoint | Zhipu | Subscription | $21.98/mo | 5.619B | $0.00391 | 9× | High | Evidence ↓ | |
| GLM Coding Max (v2 ¥469) Off-peak | Zhipu | Subscription | $69.19/mo | 17.481B | $0.00396 | 8.9× | High | Evidence ↓ | |
| GLM Coding Max (v2 ¥469) Midpoint | Zhipu | Subscription | $69.19/mo | 13.111B | $0.00528 | 6.7× | High | Evidence ↓ | |
| GLM Coding Lite (v2 ¥49) Off-peak | Zhipu | Subscription | $7.23/mo | 1.249B | $0.00579 | 6.1× | High | Evidence ↓ | |
| GLM Coding Pro (v2 ¥149) Peak | Zhipu | Subscription | $21.98/mo | 3.746B | $0.00587 | 6× | High | Evidence ↓ | |
| OpenCode Go | OpenCode | Subscription | $10/mo | 1.697B | $0.00589 | 6× | Medium | Evidence ↓ | |
| GLM Coding Lite (v2 ¥49) Midpoint | Zhipu | Subscription | $7.23/mo | 0.936B | $0.00772 | 4.6× | High | Evidence ↓ | |
| GLM Coding Max (v2 ¥469) Peak | Zhipu | Subscription | $69.19/mo | 8.74B | $0.00792 | 4.5× | High | Evidence ↓ | |
| Command Code GOAT | Command Code | Subscription | $10/mo | 1.132B | $0.00884 | 4× | Medium | Evidence ↓ | |
| GLM Coding Max (v3 ¥1078) Off-peak | Zhipu | Subscription | $159/mo | 17.481B | $0.0091 | 3.9× | High | Evidence ↓ | |
| GLM Coding Pro (v3 ¥538) Off-peak | Zhipu | Subscription | $79.37/mo | 7.492B | $0.01059 | 3.3× | High | Evidence ↓ | |
| GLM Coding Lite (v2 ¥49) Peak | Zhipu | Subscription | $7.23/mo | 0.624B | $0.01158 | 3× | High | Evidence ↓ | |
| Ollama Max | Ollama | Subscription | $100/mo | 8.487B | $0.01178 | 3× | Medium | Evidence ↓ | |
| Ollama Pro | Ollama | Subscription | $20/mo | 1.697B | $0.01178 | 3× | Medium | Evidence ↓ | |
| GLM Coding Max (v3 ¥1078) Midpoint | Zhipu | Subscription | $159/mo | 13.111B | $0.01213 | 2.9× | High | Evidence ↓ | |
| GLM Coding Lite (v3 ¥118) Off-peak | Zhipu | Subscription | $17.41/mo | 1.249B | $0.01394 | 2.5× | High | Evidence ↓ | |
| GLM Coding Pro (v3 ¥538) Midpoint | Zhipu | Subscription | $79.37/mo | 5.619B | $0.01412 | 2.5× | High | Evidence ↓ | |
| GLM Coding Max (v3 ¥1078) Peak | Zhipu | Subscription | $159/mo | 8.74B | $0.0182 | 1.9× | High | Evidence ↓ | |
| GLM Coding Lite (v3 ¥118) Midpoint | Zhipu | Subscription | $17.41/mo | 0.936B | $0.0186 | 1.9× | High | Evidence ↓ | |
| GLM Coding Pro (v3 ¥538) Peak | Zhipu | Subscription | $79.37/mo | 3.746B | $0.02119 | 1.7× | High | Evidence ↓ | |
| GLM Coding Lite (v3 ¥118) Peak | Zhipu | Subscription | $17.41/mo | 0.624B | $0.0279 | 1.3× | High | 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$0.00293388/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00293388
- Monthly tokens
- 7,492,000,000 (7.492B)
- Quota confidence
- High
- Calculation
- $21.98 / month (¥149) ÷ 7,492,000,000 tokens × 1,000,000 ≈ $0.00293388 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 1.873B ×4 weeks = 7.492B; 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$0.00296912/MTok
- Data date
- 2026-09-29 · derived; uses the data date of Droid Max · claude-opus-5.5
- Real price / MTok
- $0.00296912
- Monthly tokens
- 67,360,000,000 (67.36B)
- Quota confidence
- Medium
- Calculation
- $200 / month ÷ 67,360,000,000 tokens × 1,000,000 ≈ $0.00296912 / MTok
- Quota basis
Anthropic workload: 97% cache reads / 2.5% cache writes / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 × 26.666666666666668
Factory official multipliers Opus 5.5 1.6× / glm-5.3-flash 0.06×: 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 (v2 ¥149) MidpointZhipu$0.00391184/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00391184
- Monthly tokens
- 5,619,000,000 (5.619B)
- Quota confidence
- High
- Calculation
- $21.98 / month (¥149) ÷ 5,619,000,000 tokens × 1,000,000 ≈ $0.00391184 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 1.4047B ×4 weeks = 5.619B; 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$0.00395786/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00395786
- Monthly tokens
- 17,481,000,000 (17.481B)
- Quota confidence
- High
- Calculation
- $69.19 / month (¥469) ÷ 17,481,000,000 tokens × 1,000,000 ≈ $0.00395786 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 4.3702B ×4 weeks = 17.481B; 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$0.00527704/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00527704
- Monthly tokens
- 13,111,000,000 (13.111B)
- Quota confidence
- High
- Calculation
- $69.19 / month (¥469) ÷ 13,111,000,000 tokens × 1,000,000 ≈ $0.00527704 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 3.2777B ×4 weeks = 13.111B; 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$0.00578745/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00578745
- Monthly tokens
- 1,249,000,000 (1.249B)
- Quota confidence
- High
- Calculation
- $7.23 / month (¥49) ÷ 1,249,000,000 tokens × 1,000,000 ≈ $0.00578745 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 312.2M ×4 weeks = 1.249B; 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$0.00586776/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00586776
- Monthly tokens
- 3,746,000,000 (3.746B)
- Quota confidence
- High
- Calculation
- $21.98 / month (¥149) ÷ 3,746,000,000 tokens × 1,000,000 ≈ $0.00586776 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 936.5M ×4 weeks = 3.746B; 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
OpenCode GoOpenCode$0.00589171/MTok
- Plan
- OpenCode Go · OpenCode
- Data date
- 2026-09-30 · official source date
- Real price / MTok
- $0.00589171
- Monthly tokens
- 1,697,300,000 (1.697B)
- Quota confidence
- Medium
- Calculation
- $10 / month ÷ 1,697,300,000 tokens × 1,000,000 ≈ $0.00589171 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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: 444M (request estimate)→1.6973B: min(shared monthly pool $60, model Usage $60) ÷ project standard-workload weighted price; official Usage $15->$60 (reverified 2026-09-30); goat-opencode-catalogs-round3-2026-09-30.json. 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 Coding Lite (v2 ¥49) MidpointZhipu$0.00772278/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00772278
- Monthly tokens
- 936,000,000 (0.936B)
- Quota confidence
- High
- Calculation
- $7.23 / month (¥49) ÷ 936,000,000 tokens × 1,000,000 ≈ $0.00772278 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 234.1M ×4 weeks = 936M; 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$0.00791617/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00791617
- Monthly tokens
- 8,740,000,000 (8.74B)
- Quota confidence
- High
- Calculation
- $69.19 / month (¥469) ÷ 8,740,000,000 tokens × 1,000,000 ≈ $0.00791617 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 2.1851B ×4 weeks = 8.74B; 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
Command Code GOATCommand Code$0.00883783/MTok
- Data date
- 2026-09-30 · official source date
- Real price / MTok
- $0.00883783
- Monthly tokens
- 1,131,500,000 (1.132B)
- Quota confidence
- Medium
- Calculation
- $10 / month ÷ 1,131,500,000 tokens × 1,000,000 ≈ $0.00883783 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 1.1315B: min(shared monthly pool $70, model allowance $40) ÷ project standard-workload weighted price; official three-part pricing. 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
GLM Coding Max (v3 ¥1078) Off-peakZhipu$0.00909717/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.00909717
- Monthly tokens
- 17,481,000,000 (17.481B)
- Quota confidence
- High
- Calculation
- $159 / month (¥1078) ÷ 17,481,000,000 tokens × 1,000,000 ≈ $0.00909717 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 4.3702B ×4 weeks = 17.481B; 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) Off-peakZhipu$0.0105935/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0105935
- Monthly tokens
- 7,492,000,000 (7.492B)
- Quota confidence
- High
- Calculation
- $79.37 / month (¥538) ÷ 7,492,000,000 tokens × 1,000,000 ≈ $0.0105935 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 1.873B ×4 weeks = 7.492B; 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$0.0115842/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0115842
- Monthly tokens
- 624,000,000 (0.624B)
- Quota confidence
- High
- Calculation
- $7.23 / month (¥49) ÷ 624,000,000 tokens × 1,000,000 ≈ $0.0115842 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 156.1M ×4 weeks = 624M; 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$0.0117833/MTok
- Plan
- Ollama Max · Ollama
- Data date
- 2026-09-06 · official source date
- Real price / MTok
- $0.0117833
- Monthly tokens
- 8,486,600,000 (8.487B)
- Quota confidence
- Medium
- Calculation
- $100 / month ÷ 8,486,600,000 tokens × 1,000,000 ≈ $0.0117833 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 8.4866B: 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$0.0117834/MTok
- Plan
- Ollama Pro · Ollama
- Data date
- 2026-09-06 · official source date
- Real price / MTok
- $0.0117834
- Monthly tokens
- 1,697,300,000 (1.697B)
- Quota confidence
- Medium
- Calculation
- $20 / month ÷ 1,697,300,000 tokens × 1,000,000 ≈ $0.0117834 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 1.6973B: 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
GLM Coding Max (v3 ¥1078) MidpointZhipu$0.0121293/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0121293
- Monthly tokens
- 13,111,000,000 (13.111B)
- Quota confidence
- High
- Calculation
- $159 / month (¥1078) ÷ 13,111,000,000 tokens × 1,000,000 ≈ $0.0121293 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 3.2777B ×4 weeks = 13.111B; 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$0.0139371/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0139371
- Monthly tokens
- 1,249,000,000 (1.249B)
- Quota confidence
- High
- Calculation
- $17.41 / month (¥118) ÷ 1,249,000,000 tokens × 1,000,000 ≈ $0.0139371 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 312.2M ×4 weeks = 1.249B; 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$0.0141246/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0141246
- Monthly tokens
- 5,619,000,000 (5.619B)
- Quota confidence
- High
- Calculation
- $79.37 / month (¥538) ÷ 5,619,000,000 tokens × 1,000,000 ≈ $0.0141246 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 1.4047B ×4 weeks = 5.619B; 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$0.0181954/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0181954
- Monthly tokens
- 8,740,000,000 (8.74B)
- Quota confidence
- High
- Calculation
- $159 / month (¥1078) ÷ 8,740,000,000 tokens × 1,000,000 ≈ $0.0181954 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 2.1851B ×4 weeks = 8.74B; 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$0.0185977/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0185977
- Monthly tokens
- 936,000,000 (0.936B)
- Quota confidence
- High
- Calculation
- $17.41 / month (¥118) ÷ 936,000,000 tokens × 1,000,000 ≈ $0.0185977 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 234.1M ×4 weeks = 936M; 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$0.0211869/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0211869
- Monthly tokens
- 3,746,000,000 (3.746B)
- Quota confidence
- High
- Calculation
- $79.37 / month (¥538) ÷ 3,746,000,000 tokens × 1,000,000 ≈ $0.0211869 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 936.5M ×4 weeks = 3.746B; 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$0.0278966/MTok
- Data date
- 2026-09-03 · official source date
- Real price / MTok
- $0.0278966
- Monthly tokens
- 624,000,000 (0.624B)
- Quota confidence
- High
- Calculation
- $17.41 / month (¥118) ÷ 624,000,000 tokens × 1,000,000 ≈ $0.0278966 / MTok
- Quota basis
Standard workload: 97% cache reads / 2.5% input / 0.5% output
Official API list (cached / in / out, per MTok): $0.03 / $0.15 / $0.5 · standard-load blended ≈ $0.0353/MTok
- Benchmark mapping
- Artificial Analysis Intelligence Index v4.3: Medium (1 configuration)
Terminal-Bench 4.0 (AA): Low (1 configuration)
Code Arena | WebDev Overall: Low (1 configuration)
Agent Arena · Overall (Ranking / Pareto): 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 156.1M ×4 weeks = 624M; 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 5.3 Flash 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 | 41.81 | #19 / 60 | GLM-5.3-Flash | — | — | 1 | 2026-10-01 |
| Terminal-Bench 4.0 (AA) | Resolution Rate % | 32.83 | #16 / 53 | Artificial Analysis - GLM-5.3-Flash | — | Artificial Analysis | 1 | 2026-10-01 |
| Code Arena | WebDev Overall | Arena Score | 1,615 | #20 / 54 | glm-5.3-flash | — | — | 1 | 2026-09-30 |
| Agent Arena · Overall (Ranking / Pareto) | Net Improvement % | -0.28 | #25 / 39 | GLM 5.3 Flash | — | — | 1 | 2026-09-30 |
| DeepSWE v1.1 | Pass@1 % | 63.39 | #17 / 33 | mini-swe-agent - glm-5-3-flash (max) | Max | mini-swe-agent | 1 | 2026-09-03 |
Every archived configuration
Artificial Analysis Intelligence Index v4.3 1 configuration
Terminal-Bench 4.0 (AA) 1 configuration
| Configuration | Score | Score interval | Harness / effort / mode | Source task cost (mean / median) | Checked | Links |
|---|---|---|---|---|---|---|
| Artificial Analysis - GLM-5.3-FlashAA'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. | 32.8283 | — | Artificial Analysis / — / — | — / — | 2026-10-01 | Source · Archive |
Code Arena | WebDev Overall 1 configuration
Agent Arena · Overall (Ranking / Pareto) 1 configuration
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 Flash official API pricing
| Cached input | Input | Output |
|---|---|---|
| $0.03 | $0.15 | $0.5 |
Frequently asked questions
How much does GLM 5.3 Flash really cost per million tokens?
Measured as monthly fee ÷ tokens you can actually use, GLM 5.3 Flash ranges from $0.00293 (GLM Coding Pro (v2 ¥149) Off-peak) to $0.0279 (GLM Coding Lite (v3 ¥118) Peak) per million tokens.
Which subscription gives the most GLM 5.3 Flash usage?
Droid Max allows roughly 67.36B tokens of GLM 5.3 Flash per month for $200.
What is the official API price of GLM 5.3 Flash?
Official API list price per million tokens: $0.03 cached input, $0.15 input, $0.5 output — about $0.0353 per million tokens on a standard workload mix.
How does GLM 5.3 Flash score on independent leaderboards?
GLM 5.3 Flash has scores on 5 leaderboards; its strongest placement is 32.83 (Resolution Rate %) on Terminal-Bench 4.0 (AA), #16 of 53 models tracked.
Who makes GLM 5.3 Flash, and where can I use it?
GLM 5.3 Flash (model ID glm-5.3-flash) 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 | $0.00889 | 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 |