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Model comparison

Claude Opus 4.6 vs MAI-Thinking-1

Data verified

Head-to-head evidence from 6 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

68.59/100
No comparison
N/A
2 category wins2 category wins

Public leaderboard positions: Claude Opus 4.6 #16 (Supported); MAI-Thinking-1 unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Opus 4.6 and MAI-Thinking-1 share 6 comparable benchmark results. 4 of 8 categories are comparable. 40 results are unique to Claude Opus 4.6; 7 to MAI-Thinking-1.

Updated July 23, 2026
Shared results
6
Claude Opus 4.6 only
40
MAI-Thinking-1 only
7
Comparable categories
4 / 8

Treat this as a split decision. Claude Opus 4.6 makes more sense if agentic is the priority or you need the larger 1M context window; MAI-Thinking-1 is the better fit if mathematics is the priority or you want the stronger reasoning-first profile.

Confidence note. This is a partial-evidence comparison with 6 shared benchmark results across 3 evidence categories; 4 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 and MAI-Thinking-1 finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

MAI-Thinking-1 is the reasoning model in the pair, while Claude Opus 4.6 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 4.6 gives you the larger context window at 1M, compared with 256K for MAI-Thinking-1.

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 MAI-Thinking-1
CategoryClaude Opus 4.6ΔMAI-Thinking-1
MathClaude Opus 4.636.3Margin→ 53.4MAI-Thinking-189.7
AgenticClaude Opus 4.673.0Margin← 27.0MAI-Thinking-146.0
KnowledgeClaude Opus 4.669.1Margin→ 3.4MAI-Thinking-172.5
CodingClaude Opus 4.668.1Margin← 2.6MAI-Thinking-165.5
MultimodalClaude Opus 4.677.3MarginNo overlapMAI-Thinking-1Not measured
Inst. FollowingClaude Opus 4.6Not measuredMarginNo overlapMAI-Thinking-185.0

Decisive benchmark drivers

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

More
A · Claude Opus 4.6B · MAI-Thinking-1

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 65.4%B 46%
    Winner: Claude Opus 4.6Δ 19.4
    Terminal-Bench 2.0: Claude Opus 4.6 scored 65.4%; MAI-Thinking-1 scored 46%. Claude Opus 4.6 wins this benchmark.

  2. SWE-bench Verified

    Coding
    Source ↗
    A 80.8%B 73.5%
    Winner: Claude Opus 4.6Δ 7.3
    SWE-bench Verified: Claude Opus 4.6 scored 80.8%; MAI-Thinking-1 scored 73.5%. Claude Opus 4.6 wins this benchmark.

  3. GPQA

    Knowledge
    Source ↗
    A 91.3%B 84.2%
    Winner: Claude Opus 4.6Δ 7.1
    GPQA: Claude Opus 4.6 scored 91.3%; MAI-Thinking-1 scored 84.2%. Claude Opus 4.6 wins this benchmark.

  4. MMLU-Pro

    Knowledge
    Source ↗
    A 82%B 85%
    Winner: MAI-Thinking-1Δ 3
    MMLU-Pro: Claude Opus 4.6 scored 82%; MAI-Thinking-1 scored 85%. MAI-Thinking-1 wins this benchmark.

  5. SWE-bench Pro

    Coding
    Source ↗
    A 53.4%B 52.8%
    Winner: Claude Opus 4.6Δ 0.6
    SWE-bench Pro: Claude Opus 4.6 scored 53.4%; MAI-Thinking-1 scored 52.8%. Claude Opus 4.6 wins this benchmark.

Operational comparison

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

MetricClaude Opus 4.6MAI-Thinking-1Comparison
Input / output priceUSD per 1M tokensClaude Opus 4.6$5 input / $25 outputMAI-Thinking-1Not availableA complete price comparison is not available.
Generation speedtokens per secondClaude Opus 4.640 tok/sMAI-Thinking-1Not availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Opus 4.61.78 sMAI-Thinking-1Not availableA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Opus 4.61MMAI-Thinking-1256KClaude Opus 4.6 lists the larger context window.

Benchmark Deep Dive

AgenticClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6MAI-Thinking-1Result
Terminal-Bench 2.0Source 65.4%46%Claude Opus 4.6 leads
BrowseCompSource 83.7%—Not comparable
OSWorld-VerifiedSource 72.7%—Not comparable
τ²-bench resultsSource 84.8%—Not comparable
Claw-EvalSource 70.4%—Not comparable
DeepSearchQASource 73.7%—Not comparable
CyberGymSource 66.6%—Not comparable
Gert LabsSource 61.85%—Not comparable
ResearchClawBenchSource 19.9%—Not comparable
JobBenchSource 36.7%—Not comparable
CodingClaude Opus 4.6 wins
BenchmarkClaude Opus 4.6MAI-Thinking-1Result
SWE-bench VerifiedSource 80.8%73.5%Claude Opus 4.6 leads
SWE-bench Verified*Source 75.6%—Not comparable
LiveCodeBench ProSource 70.7%—Not comparable
SWE-bench ProSource 53.4%52.8%Claude Opus 4.6 leads
SWE-RebenchSource 65.3%—Not comparable
React Native EvalsSource 84.1%—Not comparable
Vibe Code BenchSource 57.57%—Not comparable
AA-SciCodeSource 45.7%—Not comparable
FrontierCode 1.1 MainSource 26.9%—Not comparable
Terminal-Bench 2.0Source —46.0%Not comparable
Reasoning
BenchmarkClaude Opus 4.6MAI-Thinking-1Result
AA-LCRSource 58.3%—Not comparable
CritPtSource 2.8%—Not comparable
Graphwalks BFS 128KSource —90%Not comparable
KnowledgeMAI-Thinking-1 wins
BenchmarkClaude Opus 4.6MAI-Thinking-1Result
GPQASource 91.3%84.2%Claude Opus 4.6 leads
GPQA-DSource 89.2%84.2%Claude Opus 4.6 leads
SuperGPQASource 95%—Not comparable
MMLU-ProSource 82%85%MAI-Thinking-1 leads
MMLU-Pro (Arcee)Source 89.1%—Not comparable
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%—Not comparable
AA-GPQA DiamondSource 84.0%—Not comparable
AA-HLESource 18.6%—Not comparable
AA-Omniscience IndexSource 3.5%—Not comparable
AA-Omniscience AccuracySource 45.2%—Not comparable
AA-Omniscience Hallucination RateSource 76.0%—Not comparable
SimpleQASource —31%Not comparable
MathMAI-Thinking-1 wins
BenchmarkClaude Opus 4.6MAI-Thinking-1Result
AIME25 (Arcee)Source 99.8%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 40.700%—Not comparable
FrontierMath v2 (Tier 4)Source 22.900%—Not comparable
AIME 2025Source —97%Not comparable
AIME26Source —94.5%Not comparable
HMMT Feb 2026Source —84.9%Not comparable
Multimodal
BenchmarkClaude Opus 4.6MAI-Thinking-1Result
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 1325—Not comparable
Inst. Following
BenchmarkClaude Opus 4.6MAI-Thinking-1Result
AA-IFBenchSource 44.6%—Not comparable
IFBenchSource —85%Not comparable
Frequently Asked Questions (5)

Which is better, Claude Opus 4.6 or MAI-Thinking-1?

Claude Opus 4.6 and MAI-Thinking-1 are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, Claude Opus 4.6 or MAI-Thinking-1?

MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 69.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Opus 4.6 or MAI-Thinking-1?

Claude Opus 4.6 has the edge for coding in this comparison, averaging 68.1 versus 65.5. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for math, Claude Opus 4.6 or MAI-Thinking-1?

MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 36.3. Claude Opus 4.6 stays close enough that the answer can still flip depending on your workload.

Which is better for agentic tasks, Claude Opus 4.6 or MAI-Thinking-1?

Claude Opus 4.6 has the edge for agentic tasks in this comparison, averaging 73 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

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