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Model comparison

Claude Opus 4.6 vs MiniMax M2.7

Data verified

Head-to-head evidence from 23 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

68.59/100
Margin
4.5pts
← winning
64.11/100
2 category wins0 category wins

Public leaderboard positions: Claude Opus 4.6 #16 (Supported); MiniMax M2.7 #36 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 and MiniMax M2.7 share 23 comparable benchmark results. 2 of 8 categories are comparable. 23 results are unique to Claude Opus 4.6; 12 to MiniMax M2.7.

Updated July 23, 2026
Shared results
23
Claude Opus 4.6 only
23
MiniMax M2.7 only
12
Comparable categories
2 / 8

Pick Claude Opus 4.6 if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 7 evidence categories; 2 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 is clearly ahead on the BenchAlign aggregate, 68.59 to 64.11. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.6's sharpest advantage is in agentic, where it averages 73 against 57. The single biggest benchmark swing on the page is SWE-Rebench, 65.3% to 51.9%.

Claude Opus 4.6 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 20.8x on output cost alone. Claude Opus 4.6 gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.

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 MiniMax M2.7
CategoryClaude Opus 4.6ΔMiniMax M2.7
AgenticClaude Opus 4.673.0Margin← 16.0MiniMax M2.757.0
CodingClaude Opus 4.668.1Margin← 14.8MiniMax M2.753.3
KnowledgeClaude Opus 4.669.1MarginNo overlapMiniMax M2.7Not measured
MathClaude Opus 4.636.3MarginNo overlapMiniMax M2.7Not measured
MultimodalClaude Opus 4.677.3MarginNo overlapMiniMax M2.7Not measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.6B · MiniMax M2.7

  1. SWE-Rebench

    Coding
    Source ↗
    A 65.3%B 51.9%
    Winner: Claude Opus 4.6Δ 13.4
    SWE-Rebench: Claude Opus 4.6 scored 65.3%; MiniMax M2.7 scored 51.9%. Claude Opus 4.6 wins this benchmark.

  2. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 65.4%B 57%
    Winner: Claude Opus 4.6Δ 8.4
    Terminal-Bench 2.0: Claude Opus 4.6 scored 65.4%; MiniMax M2.7 scored 57%. Claude Opus 4.6 wins this benchmark.

  3. SWE-bench Pro

    Coding
    Source ↗
    A 53.4%B 56.2%
    Winner: MiniMax M2.7Δ 2.8
    SWE-bench Pro: Claude Opus 4.6 scored 53.4%; MiniMax M2.7 scored 56.2%. MiniMax M2.7 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.6MiniMax M2.7Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.6$5 input / $25 outputMiniMax M2.7$0.3 input / $1.2 outputMiniMax M2.7 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.640 tok/sMiniMax M2.745 tok/sMiniMax M2.7 has the higher measured throughput.
First-answer latencyseconds to first tokenClaude Opus 4.61.78 sMiniMax M2.72.53 sClaude Opus 4.6 reaches the first token sooner.
Context windowmaximum listed tokensClaude Opus 4.61MMiniMax M2.7200KClaude Opus 4.6 lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6MiniMax M2.7Result
Terminal-Bench 2.0Source 65.4%57%Claude Opus 4.6 leads
BrowseCompSource 83.7%—Not comparable
OSWorld-VerifiedSource 72.7%—Not comparable
τ²-bench resultsSource 84.8%84.8%Tie
Claw-EvalSource 70.4%48.7%Claude Opus 4.6 leads
DeepSearchQASource 73.7%—Not comparable
CyberGymSource 66.6%—Not comparable
Gert LabsSource 61.85%40.40%Claude Opus 4.6 leads
ResearchClawBenchSource 19.9%—Not comparable
JobBenchSource 36.7%—Not comparable
ToolathlonSource —46.3%Not comparable
MLE-Bench LiteSource —66.6%Not comparable
MM-ClawBenchSource —62.7%Not comparable
AA Agentic IndexSource —25.6%Not comparable
APEX-Agents-AASource —10.6%Not comparable
GDPval-AASource —32.9%Not comparable
GDPval-AASource —1158Not comparable
CodingClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6MiniMax M2.7Result
SWE-bench VerifiedSource 80.8%—Not comparable
SWE-bench Verified*Source 75.6%75.4%Claude Opus 4.6 leads
LiveCodeBench ProSource 70.7%—Not comparable
SWE-bench ProSource 53.4%56.2%MiniMax M2.7 leads
SWE-RebenchSource 65.3%51.9%Claude Opus 4.6 leads
React Native EvalsSource 84.1%71.4%Claude Opus 4.6 leads
Vibe Code BenchSource 57.57%27.04%Claude Opus 4.6 leads
AA-SciCodeSource 45.7%47.0%MiniMax M2.7 leads
FrontierCode 1.1 MainSource 26.9%—Not comparable
SWE MultilingualSource —76.5%Not comparable
Multi-SWE BenchSource —52.7%Not comparable
VIBE-ProSource —55.6%Not comparable
NL2RepoSource —39.8%Not comparable
AA Coding IndexSource —52.6%Not comparable
Reasoning
BenchmarkClaude Opus 4.6MiniMax M2.7Result
AA-LCRSource 58.3%68.7%MiniMax M2.7 leads
CritPtSource 2.8%0.6%Claude Opus 4.6 leads
Knowledge
BenchmarkClaude Opus 4.6MiniMax M2.7Result
GPQASource 91.3%—Not comparable
GPQA-DSource 89.2%87.0%Claude Opus 4.6 leads
SuperGPQASource 95%—Not comparable
MMLU-ProSource 82%—Not comparable
MMLU-Pro (Arcee)Source 89.1%80.8%Claude Opus 4.6 leads
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%38.1%MiniMax M2.7 leads
AA-GPQA DiamondSource 84.0%87.4%MiniMax M2.7 leads
AA-HLESource 18.6%28.1%MiniMax M2.7 leads
AA-Omniscience IndexSource 3.5%0.7%Claude Opus 4.6 leads
AA-Omniscience AccuracySource 45.2%26.1%Claude Opus 4.6 leads
AA-Omniscience Hallucination RateSource 76.0%34.4%MiniMax M2.7 leads
Math
BenchmarkClaude Opus 4.6MiniMax M2.7Result
AIME25 (Arcee)Source 99.8%80.0%Claude Opus 4.6 leads
FrontierMath v2 (Tiers 1-3)Source 40.700%—Not comparable
FrontierMath v2 (Tier 4)Source 22.900%—Not comparable
Multimodal
BenchmarkClaude Opus 4.6MiniMax M2.7Result
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%—Not comparable
Design Arena WebsiteSource 13251275Claude Opus 4.6 leads
Inst. Following
BenchmarkClaude Opus 4.6MiniMax M2.7Result
AA-IFBenchSource 44.6%75.7%MiniMax M2.7 leads
Frequently Asked Questions (3)

Which is better, Claude Opus 4.6 or MiniMax M2.7?

Claude Opus 4.6 is ahead on BenchLM's BenchAlign leaderboard, 68.59 to 64.11. The biggest single separator in this matchup is SWE-Rebench, where the scores are 65.3% and 51.9%.

Which is better for coding, Claude Opus 4.6 or MiniMax M2.7?

Claude Opus 4.6 has the edge for coding in this comparison, averaging 68.1 versus 53.3. Inside this category, Vibe Code Bench is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.6 or MiniMax M2.7?

Claude Opus 4.6 has the edge for agentic tasks in this comparison, averaging 73 versus 57. Inside this category, Claw-Eval is the benchmark that creates the most daylight between them.

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