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Model comparison

Claude Opus 4.6 vs Mistral Medium 3.5 128B

Data verified

Head-to-head evidence from 14 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

67.76/100
No comparison
N/A
0 category wins1 category wins

Public leaderboard positions: Claude Opus 4.6 #20 (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 Opus 4.6 and Mistral Medium 3.5 128B share 14 comparable benchmark results. 1 of 8 categories are comparable. 32 results are unique to Claude Opus 4.6; 11 to Mistral Medium 3.5 128B.

Updated July 27, 2026
Shared results
14
Claude Opus 4.6 only
32
Mistral Medium 3.5 128B only
11
Comparable categories
1 / 8

Treat this as a split decision. Claude Opus 4.6 makes more sense if you need the larger 1M context window or 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 Opus 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 Opus 4.6 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $1.50 input / $7.50 output per 1M tokens for Mistral Medium 3.5 128B. That is roughly 3.3x on output cost alone. Mistral Medium 3.5 128B is the reasoning model in the pair, while Claude Opus 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. Claude Opus 4.6 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 scores and score margins for Claude Opus 4.6 and Mistral Medium 3.5 128B
CategoryClaude Opus 4.6ΔMistral Medium 3.5 128B
CodingClaude Opus 4.668.1Margin→ 9.5Mistral Medium 3.5 128B77.6
AgenticClaude Opus 4.673.0MarginNo overlapMistral Medium 3.5 128BNot measured
KnowledgeClaude Opus 4.669.1MarginNo overlapMistral Medium 3.5 128BNot measured
MathClaude Opus 4.636.3MarginNo overlapMistral Medium 3.5 128BNot measured
MultimodalClaude Opus 4.677.3MarginNo overlapMistral Medium 3.5 128BNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Claude Opus 4.6B · Mistral Medium 3.5 128B

  1. SWE-bench Verified

    Coding
    Source ↗
    A 80.8%B 77.6%
    Winner: Claude Opus 4.6Δ 3.2
    SWE-bench Verified: Claude Opus 4.6 scored 80.8%; Mistral Medium 3.5 128B scored 77.6%. Claude Opus 4.6 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricClaude Opus 4.6Mistral Medium 3.5 128BComparison
Input / output priceUSD per 1M tokensClaude Opus 4.6$5 input / $25 outputMistral Medium 3.5 128B$1.5 input / $7.5 outputMistral Medium 3.5 128B has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.640 tok/sMistral Medium 3.5 128BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.61.78 sMistral Medium 3.5 128BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.61MMistral Medium 3.5 128B256KClaude Opus 4.6 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.6Mistral Medium 3.5 128BResult
Terminal-Bench 2.0Source 65.4%—Not comparable
BrowseCompSource 83.7%—Not comparable
OSWorld-VerifiedSource 72.7%—Not comparable
τ²-bench resultsSource 84.8%94.2%Mistral Medium 3.5 128B leads
Claw-EvalSource 70.4%—Not comparable
DeepSearchQASource 73.7%—Not comparable
CyberGymSource 66.6%—Not comparable
Gert LabsSource 61.85%39.10%Claude Opus 4.6 leads
ResearchClawBenchSource 19.9%—Not comparable
JobBenchSource 36.7%—Not comparable
τ³-bench resultsSource —91.4%Not comparable
AA Agentic IndexSource —19.0%Not comparable
GDPval-AASource —21.6%Not comparable
GDPval-AASource —933Not comparable
AA EnterpriseOps-GymSource —33.7%Not comparable
AA Harvey LABSource —69.1%Not comparable
terminalBenchHardSource —33.3%Not comparable
AA BriefcaseSource —516Not comparable
AA Tau3 BankingSource —14.4%Not comparable
CodingMistral Medium 3.5 128B wins
BenchmarkClaude Opus 4.6Mistral Medium 3.5 128BResult
SWE-bench VerifiedSource 80.8%77.6%Claude Opus 4.6 leads
SWE-bench Verified*Source 75.6%—Not comparable
LiveCodeBench ProSource 70.7%—Not comparable
SWE-bench ProSource 53.4%—Not comparable
SWE-RebenchSource 65.3%—Not comparable
React Native EvalsSource 84.1%—Not comparable
Vibe Code BenchSource 57.57%—Not comparable
AA-SciCodeSource 45.7%39.6%Claude Opus 4.6 leads
FrontierCode 1.1 MainSource 26.9%—Not comparable
AA Coding IndexSource —46.9%Not comparable
Reasoning
BenchmarkClaude Opus 4.6Mistral Medium 3.5 128BResult
AA-LCRSource 58.3%61.0%Mistral Medium 3.5 128B leads
CritPtSource 2.8%0.0%Claude Opus 4.6 leads
Knowledge
BenchmarkClaude Opus 4.6Mistral Medium 3.5 128BResult
GPQASource 91.3%—Not comparable
GPQA-DSource 89.2%—Not comparable
SuperGPQASource 95%—Not comparable
MMLU-ProSource 82%—Not comparable
MMLU-Pro (Arcee)Source 89.1%—Not comparable
HLESource 53%—Not comparable
HLE w/o toolsSource 40%—Not comparable
HealthBench HardSource 14.8%—Not comparable
MedXpertQA (Text)Source 52.1%—Not comparable
Artificial Analysis Intelligence IndexSource 37.8%29.9%Claude Opus 4.6 leads
AA-GPQA DiamondSource 84.0%74.8%Claude Opus 4.6 leads
AA-HLESource 18.6%12.8%Claude Opus 4.6 leads
AA-Omniscience IndexSource 3.5%-36.3%Claude Opus 4.6 leads
AA-Omniscience AccuracySource 45.2%25.1%Claude Opus 4.6 leads
AA-Omniscience Hallucination RateSource 76.0%82.0%Claude Opus 4.6 leads
AA Openness IndexSource —33.3%Not comparable
Math
BenchmarkClaude Opus 4.6Mistral Medium 3.5 128BResult
AIME25 (Arcee)Source 99.8%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 40.700%—Not comparable
FrontierMath v2 (Tier 4)Source 22.900%—Not comparable
Multimodal
BenchmarkClaude Opus 4.6Mistral Medium 3.5 128BResult
MMMU-ProSource 77.3%—Not comparable
ERQASource 51.6%—Not comparable
ScreenSpot ProSource 83.1%—Not comparable
MedXpertQA (MM)Source 64.8%—Not comparable
AA-MMMU-ProSource 72.5%64.9%Claude Opus 4.6 leads
Design Arena WebsiteSource 1319—Not comparable
Inst. Following
BenchmarkClaude Opus 4.6Mistral Medium 3.5 128BResult
AA-IFBenchSource 44.6%68.8%Mistral Medium 3.5 128B leads
Frequently Asked Questions (2)

Which is better, Claude Opus 4.6 or Mistral Medium 3.5 128B?

Claude Opus 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 Opus 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 68.1. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.

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