Qwen3-Next 80B-A3B Instruct vs Mistral Large 3 vs GLM-4.5V
Too close to call on our weighted score (Mistral Large 3 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
Mistral AIMistral Large 3
50/100- ECI—
- Price$0.50 / $1.50
- Context262K
Z.ai (Zhipu)GLM-4.5V
49/100- ECI—
- Price$0.60 / $1.80
- Context64K
Too close to call
It is close. Our weighted score puts them within a point (Mistral Large 3 50/100, GLM-4.5V 49/100, Qwen3-Next 80B-A3B Instruct 39/100), so choose by what matters most for your work: Mistral Large 3 on price and Mistral Large 3 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 Large 3Mistral Large 3 $0.75 · Qwen3-Next 80B-A3B Instruct $0.875 · GLM-4.5V $0.90 per 1M tokens (3:1 blend)
- Longest contextMistral Large 3Mistral Large 3 262,144 · Qwen3-Next 80B-A3B Instruct 131,072 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VQwen3-Next 80B-A3B Instruct: Text · Mistral Large 3: Text, Images · GLM-4.5V: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3-Next 80B-A3B Instruct | Mistral Large 3 | GLM-4.5V |
|---|---|---|---|---|
| Price | 50% | 53 | 56 | 52 |
| Inputs & features | 30% | 25 | 50 | 70 |
| Context window | 20% | 24 | 37 | 12 |
| Overall | 100% | 39/100 | 50/100 | 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 | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) | Mistral Large 3Mistral AI | GLM-4.5VZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.50 (best) | $0.50 (best) | $0.60 |
| Output | $2.00 | $1.50 (best) | $1.80 |
| Cached input | — | $0.05 | — |
| Blended (3:1) | $0.875 | $0.75 (best) | $0.90 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Mistral API | Official Z.AI API |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 64,000 tokens |
| Max output | 32,768 tokens | 262,144 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | No | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | qwen3-next-80b-a3b-instruct | mistral-large-2512 | glm-4.5v |
| API providers | 13 (best) | 13 (best) | 11 |
| Released | Sep 2025 | Dec 2, 2025 | Aug 11, 2025 |
| Knowledge cutoff | Apr 2025 | Nov 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.
- Qwen3-Next 80B-A3B Instruct$9.00
- Mistral Large 3$8.00
- GLM-4.5V$9.60
Which should you choose?
Which is better: Qwen3-Next 80B-A3B Instruct, Mistral Large 3 or GLM-4.5V?
It is close. Our weighted score puts them within a point (Mistral Large 3 50/100, GLM-4.5V 49/100, Qwen3-Next 80B-A3B Instruct 39/100), so choose by what matters most for your work: Mistral Large 3 on price and Mistral Large 3 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, Mistral Large 3 or GLM-4.5V?
Mistral Large 3 is cheaper at $0.50 input / $1.50 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 $0.75 per million tokens for Mistral Large 3 versus $0.875 for Qwen3-Next 80B-A3B Instruct (1.2× as much) and $0.90 for GLM-4.5V (1.2× 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, Mistral Large 3 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 Qwen3-Next 80B-A3B Instruct, Mistral Large 3 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?
Mistral Large 3 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, Mistral Large 3 up to 262,144, GLM-4.5V up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Qwen3-Next 80B-A3B Instruct accepts text; Mistral Large 3 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?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Mistral Large 3 is the newest, released Dec 2, 2025. Qwen3-Next 80B-A3B Instruct came out Sep 2025; GLM-4.5V came out Aug 11, 2025. Knowledge cutoff: Qwen3-Next 80B-A3B Instruct Apr 2025, Mistral Large 3 Nov 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.
