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Model comparison

Claude Opus 4.8 vs MiniMax M2.7

Data verified

Head-to-head evidence from 23 shared benchmark results across 6 categories. Overall scores shown here use BenchLM's provisional ranking lane.

85/100
Margin
30.0pts
← winning
55/100
2 category wins0 category wins

Verified leaderboard positions: Claude Opus 4.8 #3; MiniMax M2.7 unranked

Evidence parity. Claude Opus 4.8 and MiniMax M2.7 share 23 comparable benchmark results. 2 of 8 categories are comparable. 30 results are unique to Claude Opus 4.8; 14 to MiniMax M2.7.

Updated July 12, 2026
Shared results
23
Claude Opus 4.8 only
30
MiniMax M2.7 only
14
Comparable categories
2 / 8

Pick Claude Opus 4.8 if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 23 shared benchmark results across 6 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 4.8 is clearly ahead on the provisional aggregate, 85 to 55. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.8's sharpest advantage is in agentic, where it averages 80.3 against 57. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 74.6% to 57%.

Claude Opus 4.8 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 4.8 is the reasoning model in the pair, while MiniMax M2.7 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 4.8 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 4.8 and MiniMax M2.7
CategoryClaude Opus 4.8ΔMiniMax M2.7
AgenticClaude Opus 4.880.3Margin 23.3MiniMax M2.757.0
CodingClaude Opus 4.876.4Margin 22.0MiniMax M2.754.4
KnowledgeClaude Opus 4.862.7MarginNo overlapMiniMax M2.7Not measured
MathClaude Opus 4.853.9MarginNo overlapMiniMax M2.7Not measured
MultimodalClaude Opus 4.877.0MarginNo overlapMiniMax M2.7Not measured

Decisive benchmark drivers

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

More
A · Claude Opus 4.8B · MiniMax M2.7
  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 74.6%B 57%
    Winner: Claude Opus 4.8Δ 17.6
    Terminal-Bench 2.0: Claude Opus 4.8 scored 74.6%; MiniMax M2.7 scored 57%. Claude Opus 4.8 wins this benchmark.
  2. SWE-bench Pro

    Coding
    Source ↗
    A 69.2%B 56.2%
    Winner: Claude Opus 4.8Δ 13
    SWE-bench Pro: Claude Opus 4.8 scored 69.2%; MiniMax M2.7 scored 56.2%. Claude Opus 4.8 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.8MiniMax M2.7Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.8$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 4.8Not availableMiniMax M2.745 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.8Not availableMiniMax M2.72.53 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.81MMiniMax M2.7200KClaude Opus 4.8 lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.8 wins
BenchmarkClaude Opus 4.8MiniMax M2.7Result
Terminal-Bench 2.0Source 74.6%57%Claude Opus 4.8 leads
BrowseCompSource 84.3%Not comparable
DeepSearchQASource 93.1%Not comparable
OSWorld-VerifiedSource 83.4%Not comparable
Finance Agent v2Source 53.9%Not comparable
GDPval-AASource 16001160Claude Opus 4.8 leads
MCP AtlasSource 82.2%Not comparable
ToolathlonSource 59.9%46.3%Claude Opus 4.8 leads
Gert LabsSource 72.97%40.40%Claude Opus 4.8 leads
AA Agentic IndexSource 47.2%25.6%Claude Opus 4.8 leads
Tau2-TelecomSource 94.4%84.8%Claude Opus 4.8 leads
GDPval-AASource 55.0%33.0%Claude Opus 4.8 leads
ResearchClawBenchSource 21.1%Not comparable
OSWorld 2.0Source 20.6%Not comparable
AA BriefcaseSource 1354Not comparable
AA AutomationBenchSource 48.5%Not comparable
AA EnterpriseOps-GymSource 44.0%Not comparable
AA Harvey LABSource 7.5%Not comparable
AA Tau3 BankingSource 27.6%Not comparable
MLE-Bench LiteSource 66.6%Not comparable
MM-ClawBenchSource 62.7%Not comparable
Claw-EvalSource 48.7%Not comparable
APEX-Agents-AASource 10.6%Not comparable
CodingClaude Opus 4.8 wins
BenchmarkClaude Opus 4.8MiniMax M2.7Result
SWE-bench VerifiedSource 88.6%Not comparable
SWE-bench ProSource 69.2%56.2%Claude Opus 4.8 leads
SWE MultilingualSource 84.4%76.5%Claude Opus 4.8 leads
SWE MultimodalSource 38.4%Not comparable
Terminal-Bench 2.0Source 74.6%Not comparable
cursorBench31Source 58.4%Not comparable
cursorBench32Source 62.3%Not comparable
AA Coding IndexSource 74.3%52.6%Claude Opus 4.8 leads
Terminal-Bench HardSource 58.3%39.4%Claude Opus 4.8 leads
AA-SciCodeSource 53.5%47.0%Claude Opus 4.8 leads
FrontierCodeSource 46.5%Not comparable
AA Terminal-Bench 2.1Source 84.6%Not comparable
SWE-bench Verified*Source 75.4%Not comparable
SWE-RebenchSource 51.9%Not comparable
Multi-SWE BenchSource 52.7%Not comparable
VIBE-ProSource 55.6%Not comparable
NL2RepoSource 39.8%Not comparable
Vibe Code BenchSource 27.04%Not comparable
React Native EvalsSource 71.4%Not comparable
Reasoning
BenchmarkClaude Opus 4.8MiniMax M2.7Result
AA-LCRSource 67.7%68.7%MiniMax M2.7 leads
CritPtSource 20.9%0.6%Claude Opus 4.8 leads
Knowledge
BenchmarkClaude Opus 4.8MiniMax M2.7Result
GPQASource 93.6%Not comparable
GPQA-DSource 93.6%87.0%Claude Opus 4.8 leads
HLESource 57.9%Not comparable
HLE w/o toolsSource 49.8%Not comparable
Artificial Analysis Intelligence IndexSource 55.7%38.1%Claude Opus 4.8 leads
AA-GPQA DiamondSource 92.0%87.4%Claude Opus 4.8 leads
AA-HLESource 45.7%28.1%Claude Opus 4.8 leads
AA-Omniscience IndexSource 27.4%0.7%Claude Opus 4.8 leads
AA-Omniscience AccuracySource 46.6%26.1%Claude Opus 4.8 leads
AA-Omniscience Hallucination RateSource 35.9%34.4%MiniMax M2.7 leads
MMLU-Pro (Arcee)Source 80.8%Not comparable
Math
BenchmarkClaude Opus 4.8MiniMax M2.7Result
USAMO 2026Source 96.7%Not comparable
FrontierMath v2 (Tiers 1-3)Source 47.241%Not comparable
FrontierMath v2 (Tier 4)Source 31.250%Not comparable
AIME25 (Arcee)Source 80.0%Not comparable
Multilingual
BenchmarkClaude Opus 4.8MiniMax M2.7Result
INCLUDESource 87.6%Not comparable
Multimodal
BenchmarkClaude Opus 4.8MiniMax M2.7Result
OfficeQA ProSource 66.2%Not comparable
ScreenSpot ProSource 87.9%Not comparable
CharXivSource 89.9%Not comparable
CharXiv w/o toolsSource 80.5%Not comparable
Design Arena WebsiteSource 12811287MiniMax M2.7 leads
GDPval-AASource 1495Not comparable
Inst. Following
BenchmarkClaude Opus 4.8MiniMax M2.7Result
AA-IFBenchSource 62.2%75.7%MiniMax M2.7 leads
Frequently Asked Questions (3)

Which is better, Claude Opus 4.8 or MiniMax M2.7?

Claude Opus 4.8 is ahead on BenchLM's provisional leaderboard, 85 to 55. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 74.6% and 57%.

Which is better for coding, Claude Opus 4.8 or MiniMax M2.7?

Claude Opus 4.8 has the edge for coding in this comparison, averaging 76.4 versus 54.4. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Claude Opus 4.8 or MiniMax M2.7?

Claude Opus 4.8 has the edge for agentic tasks in this comparison, averaging 80.3 versus 57. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

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Last updated: July 12, 2026

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