GLM-4.5 vs Pixtral Large (25.02)
GLM-4.5 comes out ahead, 39 to 33 on our weighted score, and it is the cheaper option too.
- Our pick
Z.ai (Zhipu)GLM-4.5
39/100- ECI—
- Price$0.60 / $2.20
- Context131K
Mistral AIPixtral Large (25.02)
33/100- ECI—
- Price$2.00 / $6.00
- Context128K
Add a model
Make it a three-way comparison.
GLM-4.5 is our pick
GLM-4.5 is the better all-round choice, scoring 39/100 against Pixtral Large (25.02) (33). It leads on price. Pixtral Large (25.02) wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGLM-4.5GLM-4.5 $1.00 · Pixtral Large (25.02) $3.00 per 1M tokens (3:1 blend)
- Longest contextGLM-4.5GLM-4.5 131,072 · Pixtral Large (25.02) 128,000 tokens
- Widest inputsPixtral Large (25.02)GLM-4.5: Text · Pixtral Large (25.02): Text, Images
- Self-hostingGLM-4.5Publishes downloadable weights
| Measure | Weight | GLM-4.5 | Pixtral Large (25.02) |
|---|---|---|---|
| Price | 50% | 48 | 26 |
| Inputs & features | 30% | 35 | 50 |
| Context window | 20% | 25 | 24 |
| Overall | 100% | 39/100 | 33/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-4.5Z.ai (Zhipu) | Pixtral Large (25.02)Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.60 (best) | $2.00 |
| Output | $2.20 (best) | $6.00 |
| Cached input | $0.11 | — |
| Blended (3:1) | $1.00 (best) | $3.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 3 providers |
| Limits | ||
| Context window | 131,072 tokens (best) | 128,000 tokens |
| Max output | 98,304 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | glm-4.5 | — |
| API providers | 19 (best) | 3 |
| Released | Jul 28, 2025 | Apr 8, 2025 |
| Knowledge cutoff | Apr 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.5$10.40
- Pixtral Large (25.02)$32.00
Which should you choose?
Which is better: GLM-4.5 or Pixtral Large (25.02)?
GLM-4.5 is the better all-round choice, scoring 39/100 against Pixtral Large (25.02) (33). It leads on price. Pixtral Large (25.02) wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-4.5 or Pixtral Large (25.02)?
GLM-4.5 is cheaper at $0.60 input / $2.20 output per million tokens (official Z.AI API price). Pixtral Large (25.02) costs $2.00 input / $6.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for GLM-4.5 versus $3.00 for Pixtral Large (25.02) (3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.5 has not been scored yet and Pixtral Large (25.02) has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5 and Pixtral Large (25.02) yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
GLM-4.5 has the largest context window at 131,072 tokens, against 128,000 for Pixtral Large (25.02). Maximum output per response: GLM-4.5 up to 98,304, Pixtral Large (25.02) up to 8,192 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5 accepts text; Pixtral Large (25.02) accepts text and images. Pixtral Large (25.02) handles the widest range of inputs.
Are any of these open source?
GLM-4.5 publishes its weights and can be self-hosted; Pixtral Large (25.02) is proprietary.
Which is newer?
GLM-4.5 is the newest, released Jul 28, 2025. Pixtral Large (25.02) came out Apr 8, 2025. Knowledge cutoff: GLM-4.5 Apr 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
