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Model comparison

Claude Opus 4.7 (Adaptive) vs Ling 2.6 Flash

Data verified

Head-to-head evidence from 16 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

66.27/100
Margin
22.4pts
← winning
Ling 2.6 Flash
InclusionAI
43.87/100
2 category wins0 category wins

Public leaderboard positions: Claude Opus 4.7 (Adaptive) #27 (Estimated); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.7 (Adaptive) and Ling 2.6 Flash share 16 comparable benchmark results. 2 of 8 categories are comparable. 22 results are unique to Claude Opus 4.7 (Adaptive); 2 to Ling 2.6 Flash.

Updated July 23, 2026
Shared results
16
Claude Opus 4.7 (Adaptive) only
22
Ling 2.6 Flash only
2
Comparable categories
2 / 8

Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 16 shared benchmark results across 5 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 4.7 (Adaptive) is clearly ahead on the BenchAlign aggregate, 66.27 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Opus 4.7 (Adaptive)'s sharpest advantage is in coding, where it averages 78.6 against 27. The single biggest benchmark swing on the page is GPQA, 94.2% to 59%.

Claude Opus 4.7 (Adaptive) is the reasoning model in the pair, while Ling 2.6 Flash 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 (Adaptive) gives you the larger context window at 1M, compared with 262K for Ling 2.6 Flash.

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 (Adaptive) and Ling 2.6 Flash
CategoryClaude Opus 4.7 (Adaptive)ΔLing 2.6 Flash
CodingClaude Opus 4.7 (Adaptive)78.6Margin← 51.6Ling 2.6 Flash27.0
KnowledgeClaude Opus 4.7 (Adaptive)60.0Margin← 1.0Ling 2.6 Flash59.0
AgenticClaude Opus 4.7 (Adaptive)75.1MarginNo overlapLing 2.6 FlashNot measured
ReasoningClaude Opus 4.7 (Adaptive)75.8MarginNo overlapLing 2.6 FlashNot measured
MultimodalClaude Opus 4.7 (Adaptive)65.1MarginNo overlapLing 2.6 FlashNot measured
Inst. FollowingClaude Opus 4.7 (Adaptive)Not measuredMarginNo overlapLing 2.6 Flash57.0

Decisive benchmark drivers

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

More
A · Claude Opus 4.7 (Adaptive)B · Ling 2.6 Flash

  1. GPQA

    Knowledge
    Source ↗
    A 94.2%B 59%
    Winner: Claude Opus 4.7 (Adaptive)Δ 35.2
    GPQA: Claude Opus 4.7 (Adaptive) scored 94.2%; Ling 2.6 Flash scored 59%. Claude Opus 4.7 (Adaptive) wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.7 (Adaptive)Ling 2.6 FlashComparison
Input / output priceUSD per 1M tokensClaude Opus 4.7 (Adaptive)$5 input / $25 outputLing 2.6 FlashNot availableA complete price comparison is not available.
Generation speedtokens per secondClaude Opus 4.7 (Adaptive)Not availableLing 2.6 Flash209.5 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.7 (Adaptive)Not availableLing 2.6 Flash1.07 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.7 (Adaptive)1MLing 2.6 Flash262KClaude Opus 4.7 (Adaptive) lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.7 (Adaptive)Ling 2.6 FlashResult
Terminal-Bench 2.0Source 69.4%—Not comparable
BrowseCompSource 79.3%—Not comparable
MCP AtlasSource 77.3%—Not comparable
OSWorld-VerifiedSource 78%—Not comparable
CyberGymSource 73.1%—Not comparable
AA Agentic IndexSource 44.4%2.3%Claude Opus 4.7 (Adaptive) leads
τ²-bench resultsSource 88.6%86%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 49.8%2.2%Claude Opus 4.7 (Adaptive) leads
GDPval-AASource 1495545Claude Opus 4.7 (Adaptive) leads
OSWorld 2.0Source 18.2%—Not comparable
JobBenchSource 45.9%—Not comparable
AA ITBenchSource 46.7%—Not comparable
CodingClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Ling 2.6 FlashResult
SWE-bench VerifiedSource 87.6%—Not comparable
SWE-bench ProSource 64.3%—Not comparable
Terminal-Bench 2.0Source 69.4%—Not comparable
AA Coding IndexSource 73.6%25.3%Claude Opus 4.7 (Adaptive) leads
AA-SciCodeSource 54.5%27.1%Claude Opus 4.7 (Adaptive) leads
SciCodeSource —27%Not comparable
Reasoning
BenchmarkClaude Opus 4.7 (Adaptive)Ling 2.6 FlashResult
MRCR v2 128K-256KSource 59.2%—Not comparable
ARC-AGI-2Source 75.8%—Not comparable
AA-LCRSource 70.3%25.0%Claude Opus 4.7 (Adaptive) leads
CritPtSource 12.0%0.0%Claude Opus 4.7 (Adaptive) leads
KnowledgeClaude Opus 4.7 (Adaptive) wins
BenchmarkClaude Opus 4.7 (Adaptive)Ling 2.6 FlashResult
GPQASource 94.2%59%Claude Opus 4.7 (Adaptive) leads
GPQA-DSource 94.2%—Not comparable
HLESource 54.7%—Not comparable
HLE w/o toolsSource 46.9%—Not comparable
Artificial Analysis Intelligence IndexSource 53.5%14.1%Claude Opus 4.7 (Adaptive) leads
AA-GPQA DiamondSource 91.4%59.3%Claude Opus 4.7 (Adaptive) leads
AA-HLESource 39.6%6.2%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience IndexSource 26.2%-65.7%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience AccuracySource 45.8%15.4%Claude Opus 4.7 (Adaptive) leads
AA-Omniscience Hallucination RateSource 36.2%95.8%Claude Opus 4.7 (Adaptive) leads
Math
BenchmarkClaude Opus 4.7 (Adaptive)Ling 2.6 FlashResult
FrontierMath (legacy)Source 43.8%—Not comparable
Multimodal
BenchmarkClaude Opus 4.7 (Adaptive)Ling 2.6 FlashResult
OfficeQA ProSource 43.6%—Not comparable
CharXivSource 91%—Not comparable
CharXiv w/o toolsSource 82.1%—Not comparable
AA-MMMU-ProSource 78.8%—Not comparable
Design Arena WebsiteSource 1325—Not comparable
Inst. Following
BenchmarkClaude Opus 4.7 (Adaptive)Ling 2.6 FlashResult
AA-IFBenchSource 58.6%57.4%Claude Opus 4.7 (Adaptive) leads
IFBenchSource —57%Not comparable
Frequently Asked Questions (3)

Which is better, Claude Opus 4.7 (Adaptive) or Ling 2.6 Flash?

Claude Opus 4.7 (Adaptive) is ahead on BenchLM's BenchAlign leaderboard, 66.27 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 94.2% and 59%.

Which is better for knowledge tasks, Claude Opus 4.7 (Adaptive) or Ling 2.6 Flash?

Claude Opus 4.7 (Adaptive) has the edge for knowledge tasks in this comparison, averaging 60 versus 59. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.7 (Adaptive) or Ling 2.6 Flash?

Claude Opus 4.7 (Adaptive) has the edge for coding in this comparison, averaging 78.6 versus 27. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

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