Model comparison
Claude Sonnet 4.6 vs Mistral Medium 3.5 128B
Head-to-head evidence from 14 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Sonnet 4.6 #35 (Supported); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Sonnet 4.6 and Mistral Medium 3.5 128B share 14 comparable benchmark results. 1 of 8 categories are comparable. 19 results are unique to Claude Sonnet 4.6; 11 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 14
- Claude Sonnet 4.6 only
- 19
- Mistral Medium 3.5 128B only
- 11
- Comparable categories
- 1 / 8
Treat this as a split decision. Claude Sonnet 4.6 makes more sense if you would rather avoid the extra latency and token burn of a reasoning model; Mistral Medium 3.5 128B is the better fit if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 14 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
Claude Sonnet 4.6 and Mistral Medium 3.5 128B 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.
Claude Sonnet 4.6 is also the more expensive model on tokens at $3.00 input / $15.00 output per 1M tokens, versus $1.50 input / $7.50 output per 1M tokens for Mistral Medium 3.5 128B. That is roughly 2.0x on output cost alone. Mistral Medium 3.5 128B is the reasoning model in the pair, while Claude Sonnet 4.6 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 200K for Claude Sonnet 4.6.
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 | Claude Sonnet 4.6 | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Coding | Claude Sonnet 4.669.1 | Margin→ 8.5 | Mistral Medium 3.5 128B77.6 |
| Agentic | Claude Sonnet 4.665.2 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Knowledge | Claude Sonnet 4.666.0 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Math | Claude Sonnet 4.626.4 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Multimodal | Claude Sonnet 4.677.4 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 79.6%B 77.6%Winner: Claude Sonnet 4.6Δ 2SWE-bench Verified: Claude Sonnet 4.6 scored 79.6%; Mistral Medium 3.5 128B scored 77.6%. Claude Sonnet 4.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Sonnet 4.6 | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Sonnet 4.6$3 input / $15 output | Mistral Medium 3.5 128B$1.5 input / $7.5 output | Mistral Medium 3.5 128B has the lower combined listed price. |
| Generation speedtokens per second | Claude Sonnet 4.644 tok/s | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Sonnet 4.61.48 s | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Sonnet 4.6200K | Mistral Medium 3.5 128B256K | Mistral Medium 3.5 128B lists the larger context window. |
Benchmark Deep Dive
Agentic17 benchmarks
| Benchmark | Claude Sonnet 4.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 59.1% | — | Not comparable |
| OSWorld-VerifiedSource | 72.1% | — | Not comparable |
| Claw-EvalSource | 67.8% | — | Not comparable |
| CyberGymSource | 65.2% | — | Not comparable |
| τ²-bench resultsSource | 79.5% | 94.2% | Mistral Medium 3.5 128B leads |
| Gert LabsSource | 62.92% | 39.10% | Claude Sonnet 4.6 leads |
| OSWorld 2.0Source | 8.3% | — | Not comparable |
| JobBenchSource | 36.9% | — | Not comparable |
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| AA Agentic IndexSource | — | 19.0% | Not comparable |
| GDPval-AASource | — | 21.6% | Not comparable |
| GDPval-AASource | — | 933 | Not comparable |
| 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 |
CodingMistral Medium 3.5 128B wins8 benchmarks
| Benchmark | Claude Sonnet 4.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 79.6% | 77.6% | Claude Sonnet 4.6 leads |
| SWE-RebenchSource | 60.7% | — | Not comparable |
| React Native EvalsSource | 80.6% | — | Not comparable |
| Vibe Code BenchSource | 51.48% | — | Not comparable |
| cursorBench31Source | 48.8% | — | Not comparable |
| AA-SciCodeSource | 46.9% | 39.6% | Claude Sonnet 4.6 leads |
| FrontierCode 1.1 MainSource | 24.3% | — | Not comparable |
| AA Coding IndexSource | — | 46.9% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Claude Sonnet 4.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| GPQASource | 89.9% | — | Not comparable |
| SuperGPQASource | 95% | — | Not comparable |
| MMLU-ProSource | 79.2% | — | Not comparable |
| HLESource | 49% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 35.9% | 29.9% | Claude Sonnet 4.6 leads |
| AA-GPQA DiamondSource | 79.9% | 74.8% | Claude Sonnet 4.6 leads |
| AA-HLESource | 13.2% | 12.8% | Claude Sonnet 4.6 leads |
| AA-Omniscience IndexSource | -2.9% | -36.3% | Claude Sonnet 4.6 leads |
| AA-Omniscience AccuracySource | 38.0% | 25.1% | Claude Sonnet 4.6 leads |
| AA-Omniscience Hallucination RateSource | 65.9% | 82.0% | Claude Sonnet 4.6 leads |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math2 benchmarks
Multimodal3 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Sonnet 4.6 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | 41.2% | 68.8% | Mistral Medium 3.5 128B leads |
Frequently Asked Questions (2)
Which is better, Claude Sonnet 4.6 or Mistral Medium 3.5 128B?
Claude Sonnet 4.6 and Mistral Medium 3.5 128B 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, Claude Sonnet 4.6 or Mistral Medium 3.5 128B?
Mistral Medium 3.5 128B has the edge for coding in this comparison, averaging 77.6 versus 69.1. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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