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Model comparison

Claude Opus 4.7 vs Kimi K2.6

Data verified

Head-to-head evidence from 20 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

71.63/100
Margin
14.6pts
← winning
Kimi K2.6
Moonshot AI
57.04/100
0 category wins1 category wins

Verified leaderboard positions: Claude Opus 4.7 unranked; Kimi K2.6 #11

BenchAlign evidence: Claude Opus 4.7 supported; Kimi K2.6 estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 and Kimi K2.6 share 20 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to Claude Opus 4.7; 37 to Kimi K2.6.

Updated July 15, 2026
Shared results
20
Claude Opus 4.7 only
2
Kimi K2.6 only
37
Comparable categories
1 / 8

Pick Kimi K2.6 if you want the stronger benchmark profile. Claude Opus 4.7 only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 7 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

Kimi K2.6 has the cleaner provisional overall profile here, landing at 71 versus 69. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Kimi K2.6's sharpest advantage is in mathematics, where it averages 67.1 against 38.6. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 22.917% to 14.580%.

Claude Opus 4.7 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $0.95 input / $4.00 output per 1M tokens for Kimi K2.6. That is roughly 6.3x on output cost alone. Kimi K2.6 is the reasoning model in the pair, while Claude Opus 4.7 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 4.7 gives you the larger context window at 1M, compared with 256K for Kimi K2.6.

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 scores and score margins for Claude Opus 4.7 and Kimi K2.6
CategoryClaude Opus 4.7ΔKimi K2.6
MathClaude Opus 4.738.6Margin→ 28.5Kimi K2.667.1
AgenticClaude Opus 4.7Not measuredMarginNo overlapKimi K2.673.5
CodingClaude Opus 4.7Not measuredMarginNo overlapKimi K2.664.4
KnowledgeClaude Opus 4.7Not measuredMarginNo overlapKimi K2.642.2
MultimodalClaude Opus 4.7Not measuredMarginNo overlapKimi K2.679.8

Decisive benchmark drivers

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

More
A · Claude Opus 4.7B · Kimi K2.6

  1. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 22.917%B 14.580%
    Winner: Claude Opus 4.7Δ 8.3
    FrontierMath v2 (Tier 4): Claude Opus 4.7 scored 22.917%; Kimi K2.6 scored 14.580%. Claude Opus 4.7 wins this benchmark.

  2. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 43.793%B 38.966%
    Winner: Claude Opus 4.7Δ 4.8
    FrontierMath v2 (Tiers 1-3): Claude Opus 4.7 scored 43.793%; Kimi K2.6 scored 38.966%. Claude Opus 4.7 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.7Kimi K2.6Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.7$5 input / $25 outputKimi K2.6$0.95 input / $4 outputKimi K2.6 has the lower combined listed price.
Generation speedtokens per secondClaude Opus 4.7Not availableKimi K2.6Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7Not availableKimi K2.6Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.71MKimi K2.6256KClaude Opus 4.7 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.7Kimi K2.6Result
τ²-bench resultsSource 74%95.9%Kimi K2.6 leads
Gert LabsSource 65.59%56.82%Claude Opus 4.7 leads
ResearchClawBenchSource 20.7%18.0%Claude Opus 4.7 leads
OSWorld 2.0Source 13.9%4.6%Claude Opus 4.7 leads
Terminal-Bench 2.0Source —66.7%Not comparable
BrowseCompSource —83.2%Not comparable
OSWorld-VerifiedSource —73.1%Not comparable
ToolathlonSource —50%Not comparable
MCP AtlasSource —55.9%Not comparable
Claw-EvalSource —62.3%Not comparable
DeepSearchQASource —92.5%Not comparable
WideResearchSource —80.8%Not comparable
AA Agentic IndexSource —30.3%Not comparable
GDPval-AASource —34.5%Not comparable
GDPval-AASource —1190Not comparable
APEX-Agents-AASource —28.5%Not comparable
AA BriefcaseSource —811Not comparable
AA EnterpriseOps-GymSource —38.5%Not comparable
AA ITBenchSource —31.2%Not comparable
AA Tau3 BankingSource —20.6%Not comparable
Coding
BenchmarkClaude Opus 4.7Kimi K2.6Result
Vibe Code BenchSource 71.00%37.89%Claude Opus 4.7 leads
React Native EvalsSource 82.8%—Not comparable
Terminal-Bench HardSource 54.5%43.9%Claude Opus 4.7 leads
AA-SciCodeSource 50.1%53.5%Kimi K2.6 leads
FrontierCodeSource 38.5%—Not comparable
SWE-bench VerifiedSource —80.2%Not comparable
LiveCodeBench v6Source —89.6%Not comparable
SWE-bench ProSource —58.6%Not comparable
SWE MultilingualSource —76.7%Not comparable
SciCodeSource —52.2%Not comparable
Terminal-Bench 2.0Source —66.7%Not comparable
cursorBench31Source —47.6%Not comparable
AA Coding IndexSource —61.8%Not comparable
AA Terminal-Bench 2.1Source —65.9%Not comparable
Reasoning
BenchmarkClaude Opus 4.7Kimi K2.6Result
AA-LCRSource 67.0%69.7%Kimi K2.6 leads
CritPtSource 5.1%8.0%Kimi K2.6 leads
Knowledge
BenchmarkClaude Opus 4.7Kimi K2.6Result
Artificial Analysis Intelligence IndexSource 42.7%44.2%Kimi K2.6 leads
AA-GPQA DiamondSource 88.5%91.1%Kimi K2.6 leads
AA-HLESource 31.2%35.9%Kimi K2.6 leads
AA-Omniscience IndexSource 14.2%6.4%Claude Opus 4.7 leads
AA-Omniscience AccuracySource 43.5%32.8%Claude Opus 4.7 leads
AA-Omniscience Hallucination RateSource 51.9%39.3%Kimi K2.6 leads
GPQASource —90.5%Not comparable
GPQA-DSource —90.5%Not comparable
HLESource —34.7%Not comparable
AA Openness IndexSource —33.3%Not comparable
MathKimi K2.6 wins
BenchmarkClaude Opus 4.7Kimi K2.6Result
FrontierMath v2 (Tiers 1-3)Source 43.793%38.966%Claude Opus 4.7 leads
FrontierMath v2 (Tier 4)Source 22.917%14.580%Claude Opus 4.7 leads
AIME26Source —96.4%Not comparable
HMMT Feb 2026Source —92.7%Not comparable
MMAnswerBenchSource —86.0%Not comparable
Multimodal
BenchmarkClaude Opus 4.7Kimi K2.6Result
AA-MMMU-ProSource 76.4%79.4%Kimi K2.6 leads
Design Arena WebsiteSource 13281310Claude Opus 4.7 leads
MMMU-ProSource —79.4%Not comparable
MMMU-Pro w/ PythonSource —80.1%Not comparable
CharXivSource —80.4%Not comparable
MathVisionSource —87.4%Not comparable
V*Source —96.9%Not comparable
Inst. Following
BenchmarkClaude Opus 4.7Kimi K2.6Result
AA-IFBenchSource 43.6%76.0%Kimi K2.6 leads
Frequently Asked Questions (2)

Which is better, Claude Opus 4.7 or Kimi K2.6?

Kimi K2.6 is ahead on BenchLM's provisional leaderboard, 71 to 69. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 22.917% and 14.580%.

Which is better for math, Claude Opus 4.7 or Kimi K2.6?

Kimi K2.6 has the edge for math in this comparison, averaging 67.1 versus 38.6. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Claude Opus 4.7
API / mo$22,500
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Kimi K2.6
API / mo$3,713
Self-host / mo$18,221
Break-even326M/day
Model the full break-even

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