Model comparison
Mistral Medium 3.5 128B vs Qwen3.7 Max
Head-to-head evidence from 21 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Mistral Medium 3.5 128B unranked (Not scored); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Mistral Medium 3.5 128B and Qwen3.7 Max share 21 comparable benchmark results. 1 of 8 categories are comparable. 4 results are unique to Mistral Medium 3.5 128B; 37 to Qwen3.7 Max.
Updated July 23, 2026- Shared results
- 21
- Mistral Medium 3.5 128B only
- 4
- Qwen3.7 Max only
- 37
- Comparable categories
- 1 / 8
Treat this as a split decision. Mistral Medium 3.5 128B makes more sense if its workflow fits your team better; Qwen3.7 Max is the better fit if coding is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 21 shared benchmark results across 5 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 Qwen3.7 Max 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.
Qwen3.7 Max gives you the larger context window at 1M, compared with 256K for Mistral Medium 3.5 128B.
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 | Qwen3.7 Max |
|---|---|---|---|
| Coding | Mistral Medium 3.5 128B77.6 | Margin→ 0.3 | Qwen3.7 Max77.9 |
| Agentic | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.7 Max69.7 |
| Reasoning | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.7 Max90.4 |
| Knowledge | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.7 Max64.2 |
| Math | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.7 Max97.1 |
| Multilingual | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.7 Max87.0 |
| Inst. Following | Mistral Medium 3.5 128BNot measured | MarginNo overlap | Qwen3.7 Max84.4 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 77.6%B 80.4%Winner: Qwen3.7 MaxΔ 2.8SWE-bench Verified: Mistral Medium 3.5 128B scored 77.6%; Qwen3.7 Max scored 80.4%. Qwen3.7 Max 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 | Qwen3.7 Max | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Mistral Medium 3.5 128B$1.5 input / $7.5 output | Qwen3.7 MaxNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Mistral Medium 3.5 128BNot available | Qwen3.7 MaxNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Mistral Medium 3.5 128BNot available | Qwen3.7 MaxNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Mistral Medium 3.5 128B256K | Qwen3.7 Max1M | Qwen3.7 Max lists the larger context window. |
Benchmark Deep Dive
Agentic23 benchmarks
| Benchmark | Mistral Medium 3.5 128B | Qwen3.7 Max | Result |
|---|---|---|---|
| τ³-bench resultsSource | 91.4% | — | Not comparable |
| AA Agentic IndexSource | 19.0% | 30.6% | Qwen3.7 Max leads |
| τ²-bench resultsSource | 94.2% | 94.7% | Qwen3.7 Max leads |
| GDPval-AASource | 21.4% | 38.7% | Qwen3.7 Max leads |
| GDPval-AASource | 929 | 1273 | Qwen3.7 Max leads |
| Gert LabsSource | 39.10% | 64.27% | Qwen3.7 Max leads |
| AA BriefcaseSource | 506 | 908 | Qwen3.7 Max leads |
| AA EnterpriseOps-GymSource | 33.7% | 45.0% | Qwen3.7 Max leads |
| AA Harvey LABSource | 69.1% | 83.4% | Qwen3.7 Max leads |
| AA Tau3 BankingSource | 14.4% | — | Not comparable |
| terminalBenchHardSource | 33.3% | 50.8% | Qwen3.7 Max leads |
| Terminal-Bench 2.0Source | — | 69.7% | Not comparable |
| QwenClawBenchSource | — | 64.3% | Not comparable |
| QwenWebBenchSource | — | 1568 | Not comparable |
| Claw-EvalSource | — | 65.2% | Not comparable |
| BFCL v4Source | — | 75.0% | Not comparable |
| MCP AtlasSource | — | 76.4% | Not comparable |
| VITA-BenchSource | — | 47.9% | Not comparable |
| HLE w/ toolsSource | — | 53.5% | Not comparable |
| ResearchClawBenchSource | — | 18.7% | Not comparable |
| AA AutomationBenchSource | — | 25.6% | Not comparable |
| AA ITBenchSource | — | 42.5% | Not comparable |
| aaTerminalBench21Source | — | 74.5% | Not comparable |
CodingQwen3.7 Max wins9 benchmarks
| Benchmark | Mistral Medium 3.5 128B | Qwen3.7 Max | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.6% | 80.4% | Qwen3.7 Max leads |
| AA Coding IndexSource | 46.9% | 66.0% | Qwen3.7 Max leads |
| AA-SciCodeSource | 39.6% | 48.8% | Qwen3.7 Max leads |
| SWE-bench ProSource | — | 60.6% | Not comparable |
| SWE MultilingualSource | — | 78.3% | Not comparable |
| NL2RepoSource | — | 47.2% | Not comparable |
| SciCodeSource | — | 53.5% | Not comparable |
| LiveCodeBenchSource | — | 91.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 69.7% | Not comparable |
Reasoning3 benchmarks
Knowledge14 benchmarks
| Benchmark | Mistral Medium 3.5 128B | Qwen3.7 Max | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 29.9% | 46.0% | Qwen3.7 Max leads |
| AA-GPQA DiamondSource | 74.8% | 92.3% | Qwen3.7 Max leads |
| AA-HLESource | 12.8% | 38.1% | Qwen3.7 Max leads |
| AA-Omniscience IndexSource | -36.3% | 14.1% | Qwen3.7 Max leads |
| AA-Omniscience AccuracySource | 25.1% | 30.1% | Qwen3.7 Max leads |
| AA-Omniscience Hallucination RateSource | 82.0% | 22.9% | Qwen3.7 Max leads |
| AA Openness IndexSource | 33.3% | — | Not comparable |
| GPQASource | — | 92.4% | Not comparable |
| GPQA-DSource | — | 92.4% | Not comparable |
| HLESource | — | 41.4% | Not comparable |
| MMLU-ProSource | — | 89.6% | Not comparable |
| MMLU-ReduxSource | — | 95% | Not comparable |
| SuperGPQASource | — | 73.6% | Not comparable |
| MMMLUSource | — | 90.3% | Not comparable |
Math3 benchmarks
Multilingual5 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (2)
Which is better, Mistral Medium 3.5 128B or Qwen3.7 Max?
Mistral Medium 3.5 128B and Qwen3.7 Max 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 Qwen3.7 Max?
Qwen3.7 Max has the edge for coding in this comparison, averaging 77.9 versus 77.6. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
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