GLM-4.5V vs GPT-4.1 mini vs Mistral Medium 3.1
GPT-4.1 mini comes out ahead, 62 to 50 and 49 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
- Our pick
OpenAIGPT-4.1 mini
62/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Mistral AIMistral Medium 3.1
50/100- ECI—
- Price$0.40 / $2.00
- Context262K
GPT-4.1 mini is our pick
GPT-4.1 mini is the better all-round choice, scoring 62/100 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-4.1 miniGPT-4.1 mini $0.70 · Mistral Medium 3.1 $0.80 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · Mistral Medium 3.1 262,144 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5V and GPT-4.1 miniGLM-4.5V: Text, Images, Video · GPT-4.1 mini: Text, Images, PDFs · Mistral Medium 3.1: Text, Images
- Self-hostingGLM-4.5VPublishes downloadable weights
| Measure | Weight | GLM-4.5V | GPT-4.1 mini | Mistral Medium 3.1 |
|---|---|---|---|---|
| Price | 50% | 52 | 57 | 54 |
| Inputs & features | 30% | 70 | 70 | 50 |
| Context window | 20% | 12 | 61 | 37 |
| Overall | 100% | 49/100 | 62/100 | 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-4.5VZ.ai (Zhipu) | GPT-4.1 miniOpenAI | Mistral Medium 3.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 135.0 | — |
| ECI rank | — | #115 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 65.9% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 44.7% | — |
| SimpleQA VerifiedShort factual questions | — | 12.7% | — |
| Price per million tokens | |||
| Input | $0.60 | $0.40 (best) | $0.40 (best) |
| Output | $1.80 | $1.60 (best) | $2.00 |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $0.90 | $0.70 (best) | $0.80 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official OpenAI API | Official Mistral API |
| Limits | |||
| Context window | 64,000 tokens | 1,047,576 tokens (best) | 262,144 tokens |
| Max output | 16,384 tokens | 32,768 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-4.5v | gpt-4.1-mini | mistral-medium-2508 |
| API providers | 11 | 24 (best) | 1 |
| Released | Aug 11, 2025 | Apr 14, 2025 | Aug 12, 2025 |
| Knowledge cutoff | Apr 2025 | Apr 2024 | 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
- GPT-4.1 mini$7.20
- Mistral Medium 3.1$8.00
Which should you choose?
Which is better: GLM-4.5V, GPT-4.1 mini or Mistral Medium 3.1?
GPT-4.1 mini is the better all-round choice, scoring 62/100 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, GLM-4.5V, GPT-4.1 mini or Mistral Medium 3.1?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI 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 $0.70 per million tokens for GPT-4.1 mini versus $0.80 for Mistral Medium 3.1 (1.1× 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. GLM-4.5V has not been scored yet, GPT-4.1 mini has an ECI of 135.0 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-4.5V, GPT-4.1 mini 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?
GPT-4.1 mini has the largest context window at 1,047,576 tokens, against 262,144 for Mistral Medium 3.1 and 64,000 for GLM-4.5V. Maximum output per response: GLM-4.5V up to 16,384, GPT-4.1 mini up to 32,768, Mistral Medium 3.1 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5V accepts text, images and video; GPT-4.1 mini accepts text, images and PDFs; Mistral Medium 3.1 accepts text and images. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V publishes its weights and can be self-hosted; GPT-4.1 mini and 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; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: GLM-4.5V Apr 2025, GPT-4.1 mini Apr 2024, 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.
