GLM-4.5-Air vs GLM-4.5V vs Mistral Medium 3.1
Too close to call on our weighted score (Mistral Medium 3.1 50, GLM-4.5V 49, GLM-4.5-Air 49). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.5-Air
49/100- ECI—
- Price$0.20 / $1.10
- Context131K
- Z.ai (Zhipu)
GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
Mistral AIMistral Medium 3.1
50/100- ECI—
- Price$0.40 / $2.00
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Mistral Medium 3.1 50/100, GLM-4.5V 49/100, GLM-4.5-Air 49/100), so choose by what matters most for your work: GLM-4.5-Air on price and Mistral Medium 3.1 for long inputs. 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-4.5-AirGLM-4.5-Air $0.425 · Mistral Medium 3.1 $0.80 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextMistral Medium 3.1Mistral Medium 3.1 262,144 · GLM-4.5-Air 131,072 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VGLM-4.5-Air: Text · GLM-4.5V: Text, Images, Video · Mistral Medium 3.1: Text, Images
- Self-hostingGLM-4.5-Air and GLM-4.5VPublishes downloadable weights
| Measure | Weight | GLM-4.5-Air | GLM-4.5V | Mistral Medium 3.1 |
|---|---|---|---|---|
| Price | 50% | 68 | 52 | 54 |
| Inputs & features | 30% | 35 | 70 | 50 |
| Context window | 20% | 24 | 12 | 37 |
| Overall | 100% | 49/100 | 49/100 | 50/100 |
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-4.5-AirZ.ai (Zhipu) | GLM-4.5VZ.ai (Zhipu) | Mistral Medium 3.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 (best) | $0.60 | $0.40 |
| Output | $1.10 (best) | $1.80 | $2.00 |
| Cached input | $0.03 | — | — |
| Blended (3:1) | $0.425 (best) | $0.90 | $0.80 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Z.AI API | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens | 64,000 tokens | 262,144 tokens (best) |
| Max output | 98,304 tokens | 16,384 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.5-air | glm-4.5v | mistral-medium-2508 |
| API providers | 13 (best) | 11 | 1 |
| Released | Jul 28, 2025 | Aug 11, 2025 | Aug 12, 2025 |
| Knowledge cutoff | Apr 2025 | Apr 2025 | May 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-Air$4.20
- GLM-4.5V$9.60
- Mistral Medium 3.1$8.00
Which should you choose?
Which is better: GLM-4.5-Air, GLM-4.5V or Mistral Medium 3.1?
It is close. Our weighted score puts them within a point (Mistral Medium 3.1 50/100, GLM-4.5V 49/100, GLM-4.5-Air 49/100), so choose by what matters most for your work: GLM-4.5-Air on price and Mistral Medium 3.1 for long inputs. 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-Air, GLM-4.5V or Mistral Medium 3.1?
GLM-4.5-Air is cheaper at $0.20 input / $1.10 output per million tokens (official Z.AI API price). Mistral Medium 3.1 costs $0.40 input / $2.00 output per million tokens (official Mistral API price); GLM-4.5V costs $0.60 input / $1.80 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.425 per million tokens for GLM-4.5-Air versus $0.80 for Mistral Medium 3.1 (1.9× as much) and $0.90 for GLM-4.5V (2.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5-Air has not been scored yet, GLM-4.5V has not been scored yet and Mistral Medium 3.1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Air, GLM-4.5V and Mistral Medium 3.1 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Mistral Medium 3.1 has the largest context window at 262,144 tokens, against 131,072 for GLM-4.5-Air and 64,000 for GLM-4.5V. Maximum output per response: GLM-4.5-Air up to 98,304, GLM-4.5V up to 16,384, Mistral Medium 3.1 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Air accepts text; GLM-4.5V accepts text, images and video; Mistral Medium 3.1 accepts text and images. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5-Air and GLM-4.5V publishes its weights and can be self-hosted; Mistral Medium 3.1 is proprietary.
Which is newer?
Mistral Medium 3.1 is the newest, released Aug 12, 2025. GLM-4.5V came out Aug 11, 2025; GLM-4.5-Air came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Air Apr 2025, GLM-4.5V Apr 2025, Mistral Medium 3.1 May 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 Oct 4, 2026.
