Model comparison
Claude 3.5 Sonnet vs Mistral Medium 3.5 128B
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude 3.5 Sonnet #139 (Estimated); 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 3.5 Sonnet and Mistral Medium 3.5 128B share 1 comparable benchmark result. 1 of 8 categories are comparable. 3 results are unique to Claude 3.5 Sonnet; 24 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 1
- Claude 3.5 Sonnet only
- 3
- Mistral Medium 3.5 128B only
- 24
- Comparable categories
- 1 / 8
Treat this as a split decision. Claude 3.5 Sonnet 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 1 shared benchmark result across 1 evidence category; 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 3.5 Sonnet 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 3.5 Sonnet 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 3.5 Sonnet 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 3.5 Sonnet.
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 3.5 Sonnet | Δ | Mistral Medium 3.5 128B |
|---|---|---|---|
| Coding | Claude 3.5 Sonnet49.0 | Margin→ 28.6 | Mistral Medium 3.5 128B77.6 |
| Knowledge | Claude 3.5 Sonnet59.4 | MarginNo overlap | Mistral Medium 3.5 128BNot measured |
| Math | Claude 3.5 Sonnet1.6 | 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 49%B 77.6%Winner: Mistral Medium 3.5 128BΔ 28.6SWE-bench Verified: Claude 3.5 Sonnet scored 49%; Mistral Medium 3.5 128B scored 77.6%. 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 | Claude 3.5 Sonnet | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 3.5 Sonnet$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 3.5 SonnetNot available | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude 3.5 SonnetNot available | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude 3.5 Sonnet200K | Mistral Medium 3.5 128B256K | Mistral Medium 3.5 128B lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | Claude 3.5 Sonnet | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| AA Agentic IndexSource | — | 19.0% | Not comparable |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| GDPval-AASource | — | 21.6% | Not comparable |
| GDPval-AASource | — | 933 | Not comparable |
| Gert LabsSource | — | 39.10% | 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 wins3 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Claude 3.5 Sonnet | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| GPQASource | 59.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 29.9% | Not comparable |
| AA-GPQA DiamondSource | — | 74.8% | Not comparable |
| AA-HLESource | — | 12.8% | Not comparable |
| AA-Omniscience IndexSource | — | -36.3% | Not comparable |
| AA-Omniscience AccuracySource | — | 25.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 82.0% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math2 benchmarks
Multimodal1 benchmarks
| Benchmark | Claude 3.5 Sonnet | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | — | 64.9% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Claude 3.5 Sonnet | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 68.8% | Not comparable |
Frequently Asked Questions (2)
Which is better, Claude 3.5 Sonnet or Mistral Medium 3.5 128B?
Claude 3.5 Sonnet 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 3.5 Sonnet or Mistral Medium 3.5 128B?
Mistral Medium 3.5 128B has the edge for coding in this comparison, averaging 77.6 versus 49. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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