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Model comparison

Claude Opus 4.6 (Adaptive) vs Claude Opus 4.8

Data verified

Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.18/100
Margin
14.2pts
winning →
78.34/100
0 category wins0 category wins

Public leaderboard positions: Claude Opus 4.6 (Adaptive) #35 (Estimated); Claude Opus 4.8 #5 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 (Adaptive) and Claude Opus 4.8 share 12 comparable benchmark results. 0 of 8 categories are comparable. 4 results are unique to Claude Opus 4.6 (Adaptive); 41 to Claude Opus 4.8.

Updated July 23, 2026
Shared results
12
Claude Opus 4.6 (Adaptive) only
4
Claude Opus 4.8 only
41
Comparable categories
0 / 8

Benchmark data for Claude Opus 4.6 (Adaptive) and Claude Opus 4.8 is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

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 (Adaptive) and Claude Opus 4.8
CategoryClaude Opus 4.6 (Adaptive)ΔClaude Opus 4.8
AgenticClaude Opus 4.6 (Adaptive)Not measuredMarginNo overlapClaude Opus 4.880.3
CodingClaude Opus 4.6 (Adaptive)Not measuredMarginNo overlapClaude Opus 4.881.1
KnowledgeClaude Opus 4.6 (Adaptive)Not measuredMarginNo overlapClaude Opus 4.862.7
MathClaude Opus 4.6 (Adaptive)Not measuredMarginNo overlapClaude Opus 4.853.9
MultimodalClaude Opus 4.6 (Adaptive)Not measuredMarginNo overlapClaude Opus 4.877.0

Operational comparison

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

MetricClaude Opus 4.6 (Adaptive)Claude Opus 4.8Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.6 (Adaptive)Not availableClaude Opus 4.8$5 input / $25 outputA complete price comparison is not available.
Generation speedtokens per secondClaude Opus 4.6 (Adaptive)Not availableClaude Opus 4.8Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.6 (Adaptive)Not availableClaude Opus 4.8Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.6 (Adaptive)1MClaude Opus 4.81MListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
APEX-Agents-AASource 33.0%Not comparable
τ²-bench resultsSource 92.1%94.4%Claude Opus 4.8 leads
Terminal-Bench 2.0Source 74.6%Not comparable
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 1594Not comparable
MCP AtlasSource 82.2%Not comparable
ToolathlonSource 59.9%Not comparable
Gert LabsSource 72.97%Not comparable
AA Agentic IndexSource 47.2%Not comparable
GDPval-AASource 54.7%Not comparable
ResearchClawBenchSource 21.1%Not comparable
OSWorld 2.0Source 20.6%Not comparable
AA BriefcaseSource 1347Not comparable
AA AutomationBenchSource 48.5%Not comparable
AA EnterpriseOps-GymSource 44.0%Not comparable
AA Harvey LABSource 91.1%Not comparable
AA Tau3 BankingSource 27.6%Not comparable
terminalBenchHardSource 58.3%Not comparable
aaTerminalBench21Source 84.6%Not comparable
Coding
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
Vibe Code BenchSource 53.50%Not comparable
AA-SciCodeSource 51.9%53.5%Claude Opus 4.8 leads
SWE-bench VerifiedSource 88.6%Not comparable
SWE-bench ProSource 69.2%Not comparable
SWE MultilingualSource 84.4%Not comparable
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%Not comparable
FrontierCode 1.1 MainSource 46.5%Not comparable
Reasoning
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
AA-LCRSource 70.7%67.7%Claude Opus 4.6 (Adaptive) leads
CritPtSource 12.6%20.9%Claude Opus 4.8 leads
Knowledge
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
Artificial Analysis Intelligence IndexSource 43.7%55.7%Claude Opus 4.8 leads
AA-GPQA DiamondSource 89.6%92.0%Claude Opus 4.8 leads
AA-HLESource 36.7%45.7%Claude Opus 4.8 leads
AA-Omniscience IndexSource 13.5%27.4%Claude Opus 4.8 leads
AA-Omniscience AccuracySource 46.4%46.6%Claude Opus 4.8 leads
AA-Omniscience Hallucination RateSource 61.3%35.9%Claude Opus 4.8 leads
GPQASource 93.6%Not comparable
GPQA-DSource 93.6%Not comparable
HLESource 57.9%Not comparable
HLE w/o toolsSource 49.8%Not comparable
Math
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
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
Multilingual
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
AA Global-MMLU-LiteSource 92.2%Not comparable
INCLUDESource 87.6%Not comparable
Multimodal
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
AA-MMMU-ProSource 75.4%Not comparable
Design Arena WebsiteSource 13251270Claude Opus 4.6 (Adaptive) leads
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
Inst. Following
BenchmarkClaude Opus 4.6 (Adaptive)Claude Opus 4.8Result
AA-IFBenchSource 53.1%62.2%Claude Opus 4.8 leads
Frequently Asked Questions (3)

Can I compare Claude Opus 4.6 (Adaptive) and Claude Opus 4.8 on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Claude Opus 4.6 (Adaptive) and Claude Opus 4.8 today?

Claude Opus 4.8: $5.00 input / $25.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 23, 2026

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