Mistral Medium 3.5 vs Qwen3.5 397B-A17B vs Qwen3 Max
Qwen3.5 397B-A17B comes out ahead, 65 to 55 and 50 on our weighted score, and it is the cheaper option too.
Mistral AIMistral Medium 3.5
55/100- ECI141.4
- Price$1.50 / $7.50
- Context262K
- Our pick
Alibaba (Qwen)Qwen3.5 397B-A17B
65/100- ECI146.7
- Price$0.60 / $3.60
- Context262K
- Alibaba (Qwen)
Qwen3 Max
50/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
Qwen3.5 397B-A17B is our pick
Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against Mistral Medium 3.5 (55) and Qwen3 Max (50). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.5 397B-A17BCapabilities Index (ECI): Qwen3.5 397B-A17B 146.7 · Qwen3 Max 142.4 · Mistral Medium 3.5 141.4
- Lowest priceQwen3.5 397B-A17BQwen3.5 397B-A17B $1.35 · Qwen3 Max $2.40 · Mistral Medium 3.5 $3.00 per 1M tokens (3:1 blend)
- Longest contextAbout the sameMistral Medium 3.5 262,144 · Qwen3.5 397B-A17B 262,144 · Qwen3 Max 262,144 tokens
- Widest inputsQwen3.5 397B-A17BMistral Medium 3.5: Text, Images · Qwen3.5 397B-A17B: Text, Images, Audio, Video · Qwen3 Max: Text
- Self-hostingMistral Medium 3.5 and Qwen3.5 397B-A17BPublishes downloadable weights
| Measure | Weight | Mistral Medium 3.5 | Qwen3.5 397B-A17B | Qwen3 Max |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 67 | 74 | 68 |
| Price | 25% | 27 | 44 | 32 |
| Inputs & features | 15% | 70 | 90 | 25 |
| Context window | 10% | 37 | 37 | 37 |
| Overall | 100% | 55/100 | 65/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Medium 3.5Mistral AI | Qwen3.5 397B-A17BAlibaba (Qwen) | Qwen3 MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 141.4 | 146.7 (best) | 142.4 |
| ECI rank | #95 of 148 | #67 of 148 (best) | #91 of 148 |
| GPQA DiamondGraduate-level science questions | — | 86.4% (best) | 72.6% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 31.2% (best) | 19.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 88.9% (best) | 73.3% |
| SimpleQA VerifiedShort factual questions | — | — | 48.8% |
| Price per million tokens | |||
| Input | $1.50 | $0.60 (best) | $1.20 |
| Output | $7.50 | $3.60 (best) | $6.00 |
| Cached input | $0.15 | — | — |
| Blended (3:1) | $3.00 | $1.35 (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 | 262,144 tokens | 262,144 tokens |
| Max output | 262,144 tokens (best) | 65,536 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yeshigh | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | mistral-medium-2604 | qwen3.5-397b-a17b | qwen3-max |
| API providers | 12 | 23 (best) | 16 |
| Released | Apr 29, 2026 | Feb 15, 2026 | Sep 23, 2025 |
| Knowledge cutoff | — | — | 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
- Qwen3.5 397B-A17B$13.20
- Qwen3 Max$24.00
Which should you choose?
Which is better: Mistral Medium 3.5, Qwen3.5 397B-A17B or Qwen3 Max?
Qwen3.5 397B-A17B is the better all-round choice, scoring 65/100 against Mistral Medium 3.5 (55) and Qwen3 Max (50). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Medium 3.5, Qwen3.5 397B-A17B or Qwen3 Max?
Qwen3.5 397B-A17B is cheaper at $0.60 input / $3.60 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 $1.35 per million tokens for Qwen3.5 397B-A17B versus $2.40 for Qwen3 Max (1.8× as much) and $3.00 for Mistral Medium 3.5 (2.2× as much).
Which scores higher on benchmarks?
Qwen3.5 397B-A17B scores higher on the Capabilities Index (ECI): Qwen3.5 397B-A17B 146.7 (#67 of 148), Qwen3 Max 142.4 (#91 of 148) and Mistral Medium 3.5 141.4 (#95 of 148). Their confidence ranges do not overlap (144.8–148.2 vs 140.0–144.6), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Medium 3.5, Qwen3.5 397B-A17B and Qwen3 Max yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 397B-A17B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Mistral Medium 3.5, Qwen3.5 397B-A17B and Qwen3 Max share the same 262,144-token context window. Maximum output per response: Mistral Medium 3.5 up to 262,144, Qwen3.5 397B-A17B up to 65,536, Qwen3 Max up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Mistral Medium 3.5 accepts text and images; Qwen3.5 397B-A17B accepts text, images, audio and video; Qwen3 Max accepts text. Qwen3.5 397B-A17B handles the widest range of inputs.
Are any of these open source?
Mistral Medium 3.5 and Qwen3.5 397B-A17B 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. Qwen3.5 397B-A17B came out Feb 15, 2026; Qwen3 Max came out Sep 23, 2025. Knowledge cutoff: 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.
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