Mistral Medium 3.1 vs GPT-5.1 Codex mini vs GLM-4.5V
GPT-5.1 Codex mini comes out ahead, 59 to 50 and 49 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Medium 3.1
50/100- ECI—
- Price$0.40 / $2.00
- Context262K
- Our pick
OpenAIGPT-5.1 Codex mini
59/100- ECI—
- Price$0.25 / $2.00
- Context400K
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
GPT-5.1 Codex mini is our pick
GPT-5.1 Codex mini is the better all-round choice, scoring 59/100 against Mistral Medium 3.1 (50) and GLM-4.5V (49). It leads on price and context window. 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 priceGPT-5.1 Codex miniGPT-5.1 Codex mini $0.688 · Mistral Medium 3.1 $0.80 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Mistral Medium 3.1 262,144 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VMistral Medium 3.1: Text, Images · GPT-5.1 Codex mini: Text, Images · GLM-4.5V: Text, Images, Video
- Self-hostingGLM-4.5VPublishes downloadable weights
| Measure | Weight | Mistral Medium 3.1 | GPT-5.1 Codex mini | GLM-4.5V |
|---|---|---|---|---|
| Price | 50% | 54 | 58 | 52 |
| Inputs & features | 30% | 50 | 70 | 70 |
| Context window | 20% | 37 | 44 | 12 |
| Overall | 100% | 50/100 | 59/100 | 49/100 |
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 | Mistral Medium 3.1Mistral AI | GPT-5.1 Codex miniOpenAI | GLM-4.5VZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.40 | $0.25 (best) | $0.60 |
| Output | $2.00 | $2.00 | $1.80 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.80 | $0.688 (best) | $0.90 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 10 providers | Official Z.AI API |
| Limits | |||
| Context window | 262,144 tokens | 400,000 tokens (best) | 64,000 tokens |
| Max output | 262,144 tokens (best) | 128,000 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | mistral-medium-2508 | — | glm-4.5v |
| API providers | 1 | 10 | 11 (best) |
| Released | Aug 12, 2025 | Nov 13, 2025 | Aug 11, 2025 |
| Knowledge cutoff | May 2025 | Sep 30, 2024 | 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.
- Mistral Medium 3.1$8.00
- GPT-5.1 Codex mini$6.50
- GLM-4.5V$9.60
Which should you choose?
Which is better: Mistral Medium 3.1, GPT-5.1 Codex mini or GLM-4.5V?
GPT-5.1 Codex mini is the better all-round choice, scoring 59/100 against Mistral Medium 3.1 (50) and GLM-4.5V (49). It leads on price and context window. 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, Mistral Medium 3.1, GPT-5.1 Codex mini or GLM-4.5V?
GPT-5.1 Codex mini is cheaper at $0.25 input / $2.00 output per million tokens (median across 10 API providers). 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 $0.688 per million tokens for GPT-5.1 Codex mini versus $0.80 for Mistral Medium 3.1 (1.2× as much) and $0.90 for GLM-4.5V (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mistral Medium 3.1 has not been scored yet, GPT-5.1 Codex mini has not been scored yet and GLM-4.5V has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Medium 3.1, GPT-5.1 Codex mini and GLM-4.5V 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?
GPT-5.1 Codex mini has the largest context window at 400,000 tokens, against 262,144 for Mistral Medium 3.1 and 64,000 for GLM-4.5V. Maximum output per response: Mistral Medium 3.1 up to 262,144, GPT-5.1 Codex mini up to 128,000, GLM-4.5V up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Mistral Medium 3.1 accepts text and images; GPT-5.1 Codex mini accepts text and images; GLM-4.5V accepts text, images and video. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V publishes its weights and can be self-hosted; Mistral Medium 3.1 and GPT-5.1 Codex mini is proprietary.
Which is newer?
GPT-5.1 Codex mini is the newest, released Nov 13, 2025. Mistral Medium 3.1 came out Aug 12, 2025; GLM-4.5V came out Aug 11, 2025. Knowledge cutoff: Mistral Medium 3.1 May 2025, GPT-5.1 Codex mini Sep 30, 2024, GLM-4.5V 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 Oct 4, 2026.
