Qwen3-Next 80B-A3B Instruct 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, Qwen3-Next 80B-A3B Instruct 39). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- 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, Qwen3-Next 80B-A3B Instruct 39/100), so choose by what matters most for your work: Mistral Medium 3.1 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 priceMistral Medium 3.1Mistral Medium 3.1 $0.80 · Qwen3-Next 80B-A3B Instruct $0.875 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextMistral Medium 3.1Mistral Medium 3.1 262,144 · Qwen3-Next 80B-A3B Instruct 131,072 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VQwen3-Next 80B-A3B Instruct: Text · GLM-4.5V: Text, Images, Video · Mistral Medium 3.1: Text, Images
- Self-hostingQwen3-Next 80B-A3B Instruct and GLM-4.5VPublishes downloadable weights
| Measure | Weight | Qwen3-Next 80B-A3B Instruct | GLM-4.5V | Mistral Medium 3.1 |
|---|---|---|---|---|
| Price | 50% | 53 | 52 | 54 |
| Inputs & features | 30% | 25 | 70 | 50 |
| Context window | 20% | 24 | 12 | 37 |
| Overall | 100% | 39/100 | 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 | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) | GLM-4.5VZ.ai (Zhipu) | Mistral Medium 3.1Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 | $0.60 | $0.40 (best) |
| Output | $2.00 | $1.80 (best) | $2.00 |
| Cached input | — | — | — |
| Blended (3:1) | $0.875 | $0.90 | $0.80 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Z.AI API | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens | 64,000 tokens | 262,144 tokens (best) |
| Max output | 32,768 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 | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | qwen3-next-80b-a3b-instruct | glm-4.5v | mistral-medium-2508 |
| API providers | 13 (best) | 11 | 1 |
| Released | Sep 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.
- Qwen3-Next 80B-A3B Instruct$9.00
- GLM-4.5V$9.60
- Mistral Medium 3.1$8.00
Which should you choose?
Which is better: Qwen3-Next 80B-A3B Instruct, 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, Qwen3-Next 80B-A3B Instruct 39/100), so choose by what matters most for your work: Mistral Medium 3.1 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, Qwen3-Next 80B-A3B Instruct, GLM-4.5V or Mistral Medium 3.1?
Mistral Medium 3.1 is cheaper at $0.40 input / $2.00 output per million tokens (official Mistral API price). Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba 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 $0.80 per million tokens for Mistral Medium 3.1 versus $0.875 for Qwen3-Next 80B-A3B Instruct (1.1× as much) and $0.90 for GLM-4.5V (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3-Next 80B-A3B Instruct 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 Qwen3-Next 80B-A3B Instruct, 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 Qwen3-Next 80B-A3B Instruct and 64,000 for GLM-4.5V. Maximum output per response: Qwen3-Next 80B-A3B Instruct up to 32,768, GLM-4.5V up to 16,384, Mistral Medium 3.1 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Qwen3-Next 80B-A3B Instruct 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?
Qwen3-Next 80B-A3B Instruct and GLM-4.5V publishes its weights and can be self-hosted; Mistral Medium 3.1 is proprietary.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. Mistral Medium 3.1 came out Aug 12, 2025; GLM-4.5V came out Aug 11, 2025. Knowledge cutoff: Qwen3-Next 80B-A3B Instruct 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.
