GLM-4.5V vs Mistral Medium 3.1 vs Mistral Medium 3.5
Too close to call on our weighted score (Mistral Medium 3.1 50, GLM-4.5V 49, Mistral Medium 3.5 42). The right pick depends on what you value most.
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
- Mistral AI
Mistral Medium 3.5
42/100- ECI141.4
- Price$1.50 / $7.50
- 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, Mistral Medium 3.5 42/100), so choose by what matters most for your work: Mistral Medium 3.1 on price. 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 priceMistral Medium 3.1Mistral Medium 3.1 $0.80 · GLM-4.5V $0.90 · Mistral Medium 3.5 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Medium 3.1 and Mistral Medium 3.5Mistral Medium 3.1 262,144 · Mistral Medium 3.5 262,144 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VGLM-4.5V: Text, Images, Video · Mistral Medium 3.1: Text, Images · Mistral Medium 3.5: Text, Images
- Self-hostingGLM-4.5V and Mistral Medium 3.5Publishes downloadable weights
| Measure | Weight | GLM-4.5V | Mistral Medium 3.1 | Mistral Medium 3.5 |
|---|---|---|---|---|
| Price | 50% | 52 | 54 | 27 |
| Inputs & features | 30% | 70 | 50 | 70 |
| Context window | 20% | 12 | 37 | 37 |
| Overall | 100% | 49/100 | 50/100 | 42/100 |
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-4.5VZ.ai (Zhipu) | Mistral Medium 3.1Mistral AI | Mistral Medium 3.5Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 141.4 |
| ECI rank | — | — | #95 of 148 |
| Price per million tokens | |||
| Input | $0.60 | $0.40 (best) | $1.50 |
| Output | $1.80 (best) | $2.00 | $7.50 |
| Cached input | — | — | $0.15 |
| Blended (3:1) | $0.90 | $0.80 (best) | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Mistral API | Official Mistral API |
| Limits | |||
| Context window | 64,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 16,384 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | Yeshigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | glm-4.5v | mistral-medium-2508 | mistral-medium-2604 |
| API providers | 11 | 1 | 12 (best) |
| Released | Aug 11, 2025 | Aug 12, 2025 | Apr 29, 2026 |
| Knowledge cutoff | 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-4.5V$9.60
- Mistral Medium 3.1$8.00
- Mistral Medium 3.5$30.00
Which should you choose?
Which is better: GLM-4.5V, Mistral Medium 3.1 or Mistral Medium 3.5?
It is close. Our weighted score puts them within a point (Mistral Medium 3.1 50/100, GLM-4.5V 49/100, Mistral Medium 3.5 42/100), so choose by what matters most for your work: Mistral Medium 3.1 on price. 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-4.5V, Mistral Medium 3.1 or Mistral Medium 3.5?
Mistral Medium 3.1 is cheaper at $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); Mistral Medium 3.5 costs $1.50 input / $7.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.80 per million tokens for Mistral Medium 3.1 versus $0.90 for GLM-4.5V (1.1× as much) and $3.00 for Mistral Medium 3.5 (3.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5V has not been scored yet, Mistral Medium 3.1 has not been scored yet and Mistral Medium 3.5 has an ECI of 141.4.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5V, Mistral Medium 3.1 and Mistral Medium 3.5 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 and Mistral Medium 3.5 have the largest context windows (262,144 and 262,144 tokens), against 64,000 for GLM-4.5V. Maximum output per response: GLM-4.5V up to 16,384, Mistral Medium 3.1 up to 262,144, Mistral Medium 3.5 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5V accepts text, images and video; Mistral Medium 3.1 accepts text and images; Mistral Medium 3.5 accepts text and images. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V and Mistral Medium 3.5 publishes its weights and can be self-hosted; Mistral Medium 3.1 is proprietary.
Which is newer?
Mistral Medium 3.5 is the newest, released Apr 29, 2026. Mistral Medium 3.1 came out Aug 12, 2025; GLM-4.5V came out Aug 11, 2025. Knowledge cutoff: 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.
