Mistral Medium 3.5 vs Qwen3-Next 80B-A3B Instruct vs Qwen3 Max
Mistral Medium 3.5 comes out ahead, 42 to 39 and 31 on our weighted score, though Qwen3-Next 80B-A3B Instruct is 3.4× cheaper per token.
- Our pick
Mistral AI
Mistral Medium 3.5
42/100- ECI141.4
- Price$1.50 / $7.50
- Context262K
Alibaba (Qwen)
Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
Alibaba (Qwen)
Qwen3 Max
31/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
Mistral Medium 3.5 is our pick
Mistral Medium 3.5 is the better all-round choice, scoring 42/100 against Qwen3-Next 80B-A3B Instruct (39) and Qwen3 Max (31). It leads on inputs & features. Qwen3-Next 80B-A3B Instruct wins on price. 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-Next 80B-A3B InstructQwen3-Next 80B-A3B Instruct $0.875 · Qwen3 Max $2.40 · Mistral Medium 3.5 $3.00 per 1M tokens (3:1 blend)
- Longest contextMistral Medium 3.5 and Qwen3 MaxMistral Medium 3.5 262,144 · Qwen3 Max 262,144 · Qwen3-Next 80B-A3B Instruct 131,072 tokens
- Widest inputsMistral Medium 3.5Mistral Medium 3.5: Text, Images · Qwen3-Next 80B-A3B Instruct: Text · Qwen3 Max: Text
- Self-hostingMistral Medium 3.5 and Qwen3-Next 80B-A3B InstructPublishes downloadable weights
| Measure | Weight | Mistral Medium 3.5 | Qwen3-Next 80B-A3B Instruct | Qwen3 Max |
|---|---|---|---|---|
| Price | 50% | 27 | 53 | 32 |
| Inputs & features | 30% | 70 | 25 | 25 |
| Context window | 20% | 37 | 24 | 37 |
| Overall | 100% | 42/100 | 39/100 | 31/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 141.4 | — | 142.4 (best) |
| ECI rank | #95 of 148 | — | #91 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | — | 72.6% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 19.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 73.3% |
| SimpleQA VerifiedShort factual questions | — | — | 48.8% |
| Price per million tokens | |||
| Input | $1.50 | $0.50 (best) | $1.20 |
| Output | $7.50 | $2.00 (best) | $6.00 |
| Cached input | $0.15 | — | — |
| Blended (3:1) | $3.00 | $0.875 (best) | $2.40 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 262,144 tokens (best) | 131,072 tokens | 262,144 tokens (best) |
| Max output | 262,144 tokens (best) | 32,768 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeshigh | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | mistral-medium-2604 | qwen3-next-80b-a3b-instruct | qwen3-max |
| API providers | 12 | 13 | 16 (best) |
| Released | Apr 29, 2026 | Sep 2025 | Sep 23, 2025 |
| Knowledge cutoff | — | Apr 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.
Mistral Medium 3.5$30.00
Qwen3-Next 80B-A3B Instruct$9.00
Qwen3 Max$24.00
Which should you choose?
Which is better: Mistral Medium 3.5, Qwen3-Next 80B-A3B Instruct or Qwen3 Max?
Mistral Medium 3.5 is the better all-round choice, scoring 42/100 against Qwen3-Next 80B-A3B Instruct (39) and Qwen3 Max (31). It leads on inputs & features. Qwen3-Next 80B-A3B Instruct wins on price. 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 3.5, Qwen3-Next 80B-A3B Instruct or Qwen3 Max?
Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 input / $2.00 output per million tokens (official Alibaba API price). Qwen3 Max costs $1.20 input / $6.00 output per million tokens (official Alibaba API price); Mistral Medium 3.5 costs $1.50 input / $7.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.875 per million tokens for Qwen3-Next 80B-A3B Instruct versus $2.40 for Qwen3 Max (2.7× as much) and $3.00 for Mistral Medium 3.5 (3.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Mistral Medium 3.5 has an ECI of 141.4, Qwen3-Next 80B-A3B Instruct has not been scored yet and Qwen3 Max has an ECI of 142.4.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Medium 3.5, Qwen3-Next 80B-A3B Instruct and Qwen3 Max 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 3.5 and Qwen3 Max have the largest context windows (262,144 and 262,144 tokens), against 131,072 for Qwen3-Next 80B-A3B Instruct. Maximum output per response: Mistral Medium 3.5 up to 262,144, Qwen3-Next 80B-A3B Instruct up to 32,768, Qwen3 Max up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Mistral Medium 3.5 accepts text and images; Qwen3-Next 80B-A3B Instruct accepts text; Qwen3 Max accepts text. Mistral Medium 3.5 handles the widest range of inputs.
Are any of these open source?
Mistral Medium 3.5 and Qwen3-Next 80B-A3B Instruct publishes its weights and can be self-hosted; Qwen3 Max is proprietary.
Which is newer?
Mistral Medium 3.5 is the newest, released Apr 29, 2026. Qwen3 Max came out Sep 23, 2025; Qwen3-Next 80B-A3B Instruct came out Sep 2025. Knowledge cutoff: Qwen3-Next 80B-A3B Instruct Apr 2025, Qwen3 Max 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.