GLM-4.5V vs Mistral Medium 3.1 vs Qwen3 Coder Flash
Too close to call on our weighted score (Qwen3 Coder Flash 50, Mistral Medium 3.1 50, GLM-4.5V 49). 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
Alibaba (Qwen)Qwen3 Coder Flash
50/100- ECI—
- Price$0.30 / $1.50
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (Qwen3 Coder Flash 50/100, Mistral Medium 3.1 50/100, GLM-4.5V 49/100), so choose by what matters most for your work: Qwen3 Coder Flash on price and Qwen3 Coder Flash 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 priceQwen3 Coder FlashQwen3 Coder Flash $0.60 · Mistral Medium 3.1 $0.80 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextQwen3 Coder FlashQwen3 Coder Flash 1,000,000 · Mistral Medium 3.1 262,144 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VGLM-4.5V: Text, Images, Video · Mistral Medium 3.1: Text, Images · Qwen3 Coder Flash: Text
- Self-hostingGLM-4.5VPublishes downloadable weights
| Measure | Weight | GLM-4.5V | Mistral Medium 3.1 | Qwen3 Coder Flash |
|---|---|---|---|---|
| Price | 50% | 52 | 54 | 60 |
| Inputs & features | 30% | 70 | 50 | 25 |
| Context window | 20% | 12 | 37 | 60 |
| Overall | 100% | 49/100 | 50/100 | 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) | Mistral Medium 3.1Mistral AI | Qwen3 Coder FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.40 | $0.30 (best) |
| Output | $1.80 | $2.00 | $1.50 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.90 | $0.80 | $0.60 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 64,000 tokens | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 16,384 tokens | 262,144 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-4.5v | mistral-medium-2508 | qwen3-coder-flash |
| API providers | 11 (best) | 1 | 10 |
| Released | Aug 11, 2025 | Aug 12, 2025 | Jul 28, 2025 |
| Knowledge cutoff | Apr 2025 | May 2025 | 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-4.5V$9.60
- Mistral Medium 3.1$8.00
- Qwen3 Coder Flash$6.00
Which should you choose?
Which is better: GLM-4.5V, Mistral Medium 3.1 or Qwen3 Coder Flash?
It is close. Our weighted score puts them within a point (Qwen3 Coder Flash 50/100, Mistral Medium 3.1 50/100, GLM-4.5V 49/100), so choose by what matters most for your work: Qwen3 Coder Flash on price and Qwen3 Coder Flash 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-4.5V, Mistral Medium 3.1 or Qwen3 Coder Flash?
Qwen3 Coder Flash is cheaper at $0.30 input / $1.50 output per million tokens (official Alibaba 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 $0.60 per million tokens for Qwen3 Coder Flash versus $0.80 for Mistral Medium 3.1 (1.3× as much) and $0.90 for GLM-4.5V (1.5× 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 Qwen3 Coder Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5V, Mistral Medium 3.1 and Qwen3 Coder Flash 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?
Qwen3 Coder Flash has the largest context window at 1,000,000 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, Mistral Medium 3.1 up to 262,144, Qwen3 Coder Flash up to 65,536 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; Qwen3 Coder Flash accepts text. 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 Qwen3 Coder Flash is proprietary.
Which is newer?
Mistral Medium 3.1 is the newest, released Aug 12, 2025. GLM-4.5V came out Aug 11, 2025; Qwen3 Coder Flash came out Jul 28, 2025. Knowledge cutoff: GLM-4.5V Apr 2025, Mistral Medium 3.1 May 2025, Qwen3 Coder Flash 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.
