Model comparison
Mistral Medium 3.5 128B vs Qwen3.5 397B
Head-to-head evidence from 19 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Mistral Medium 3.5 128B unranked (Not scored); Qwen3.5 397B #78 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Mistral Medium 3.5 128B and Qwen3.5 397B share 19 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to Mistral Medium 3.5 128B; 36 to Qwen3.5 397B.
Updated July 27, 2026- Shared results
- 19
- Mistral Medium 3.5 128B only
- 6
- Qwen3.5 397B only
- 36
- Comparable categories
- 1 / 8
Treat this as a split decision. Mistral Medium 3.5 128B makes more sense if coding is the priority or you need the larger 256K context window; Qwen3.5 397B is the better fit if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 19 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Mistral Medium 3.5 128B and Qwen3.5 397B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Mistral Medium 3.5 128B is also the more expensive model on tokens at $1.50 input / $7.50 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. That is roughly 2.1x on output cost alone. Mistral Medium 3.5 128B is the reasoning model in the pair, while Qwen3.5 397B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Mistral Medium 3.5 128B gives you the larger context window at 256K, compared with 128K for Qwen3.5 397B.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Mistral Medium 3.5 128B | Δ | Qwen3.5 397B |
|---|---|---|---|
| Coding | Mistral Medium 3.5 128B77.6 | Margin← 11.1 | Qwen3.5 397B66.5 |
| Agentic | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.5 397B56.5 |
| Reasoning | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.5 397B63.2 |
| Knowledge | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.5 397B56.6 |
| Math | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.5 397B90.6 |
| Multilingual | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.5 397B84.7 |
| Multimodal | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.5 397B79.6 |
| Inst. Following | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.5 397B92.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 77.6%B 76.2%Winner: Mistral Medium 3.5 128BΔ 1.4SWE-bench Verified: Mistral Medium 3.5 128B scored 77.6%; Qwen3.5 397B scored 76.2%. Mistral Medium 3.5 128B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Mistral Medium 3.5 128B | Qwen3.5 397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Mistral Medium 3.5 128B$1.5 input / $7.5 output | Qwen3.5 397B$0.6 input / $3.6 output | Qwen3.5 397B has the lower combined listed price. |
| Generation speedtokens per second | Mistral Medium 3.5 128BNot available | Qwen3.5 397B96 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Mistral Medium 3.5 128BNot available | Qwen3.5 397B2.44 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Mistral Medium 3.5 128B256K | Qwen3.5 397B128K | Mistral Medium 3.5 128B lists the larger context window. |
Benchmark Deep Dive
Agentic23 benchmarks
| Benchmark | Mistral Medium 3.5 128B | Qwen3.5 397B | Result |
|---|---|---|---|
| τ³-bench resultsSource | 91.4% | 68.4% | Mistral Medium 3.5 128B leads |
| AA Agentic IndexSource | 19.0% | 19.9% | Qwen3.5 397B leads |
| τ²-bench resultsSource | 94.2% | 95.6% | Qwen3.5 397B leads |
| GDPval-AASource | 21.6% | 23.1% | Qwen3.5 397B leads |
| GDPval-AASource | 933 | 962 | Qwen3.5 397B leads |
| Gert LabsSource | 39.10% | 46.76% | Qwen3.5 397B leads |
| AA EnterpriseOps-GymSource | 33.7% | — | Not comparable |
| AA Harvey LABSource | 69.1% | — | Not comparable |
| terminalBenchHardSource | 33.3% | — | Not comparable |
| AA BriefcaseSource | 516 | — | Not comparable |
| AA Tau3 BankingSource | 14.4% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 52.5% | Not comparable |
| BrowseCompSource | — | 62% | Not comparable |
| Claw-EvalSource | — | 56.8% | Not comparable |
| QwenClawBenchSource | — | 51.8% | Not comparable |
| VITA-BenchSource | — | 43.7% | Not comparable |
| DeepPlanningSource | — | 37.6% | Not comparable |
| ToolathlonSource | — | 36.3% | Not comparable |
| MCP AtlasSource | — | 46.1% | Not comparable |
| MCP-TasksSource | — | 74.2% | Not comparable |
| WideResearchSource | — | 74.0% | Not comparable |
| ResearchClawBenchSource | — | 14.2% | Not comparable |
| APEX-Agents-AASource | — | 15.3% | Not comparable |
CodingMistral Medium 3.5 128B wins5 benchmarks
Reasoning4 benchmarks
Knowledge13 benchmarks
| Benchmark | Mistral Medium 3.5 128B | Qwen3.5 397B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 29.9% | 33.7% | Qwen3.5 397B leads |
| AA-GPQA DiamondSource | 74.8% | 89.3% | Qwen3.5 397B leads |
| AA-HLESource | 12.8% | 27.3% | Qwen3.5 397B leads |
| AA-Omniscience IndexSource | -36.3% | -29.8% | Qwen3.5 397B leads |
| AA-Omniscience AccuracySource | 25.1% | 31.4% | Qwen3.5 397B leads |
| AA-Omniscience Hallucination RateSource | 82.0% | 89.1% | Mistral Medium 3.5 128B leads |
| AA Openness IndexSource | 33.3% | — | Not comparable |
| GPQASource | — | 88.4% | Not comparable |
| SuperGPQASource | — | 70.4% | Not comparable |
| MMLU-ProSource | — | 87.8% | Not comparable |
| MMLU-ReduxSource | — | 94.9% | Not comparable |
| C-EvalSource | — | 93% | Not comparable |
| HLESource | — | 28.7% | Not comparable |
Math5 benchmarks
Multilingual2 benchmarks
Multimodal7 benchmarks
| Benchmark | Mistral Medium 3.5 128B | Qwen3.5 397B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 64.9% | 77.3% | Qwen3.5 397B leads |
| MMMU-ProSource | — | 79% | Not comparable |
| MathVisionSource | — | 88.6% | Not comparable |
| CharXivSource | — | 80.8% | Not comparable |
| VideoMMMUSource | — | 84.7% | Not comparable |
| ScreenSpot ProSource | — | 65.6% | Not comparable |
| V*Source | — | 95.8% | Not comparable |
Frequently Asked Questions (2)
Which is better, Mistral Medium 3.5 128B or Qwen3.5 397B?
Mistral Medium 3.5 128B and Qwen3.5 397B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for coding, Mistral Medium 3.5 128B or Qwen3.5 397B?
Mistral Medium 3.5 128B has the edge for coding in this comparison, averaging 77.6 versus 66.5. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Related Comparisons
Explore More
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
One email each week. Unsubscribe anytime.