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Model comparison

MAI-Thinking-1 vs Qwen3.7 Max

Data verified

Head-to-head evidence from 9 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

N/A
No comparison
72.84/100
2 category wins3 category wins

Public leaderboard positions: MAI-Thinking-1 unranked (Not scored); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. MAI-Thinking-1 and Qwen3.7 Max share 9 comparable benchmark results. 5 of 8 categories are comparable. 4 results are unique to MAI-Thinking-1; 49 to Qwen3.7 Max.

Updated July 23, 2026
Shared results
9
MAI-Thinking-1 only
4
Qwen3.7 Max only
49
Comparable categories
5 / 8

Treat this as a split decision. MAI-Thinking-1 makes more sense if knowledge is the priority; Qwen3.7 Max is the better fit if agentic is the priority or you need the larger 1M context window.

Confidence note. This is a partial-evidence comparison with 9 shared benchmark results across 5 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

MAI-Thinking-1 and Qwen3.7 Max 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.

Qwen3.7 Max 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 MAI-Thinking-1 and Qwen3.7 Max
CategoryMAI-Thinking-1ΔQwen3.7 Max
AgenticMAI-Thinking-146.0Margin→ 23.7Qwen3.7 Max69.7
CodingMAI-Thinking-165.5Margin→ 12.4Qwen3.7 Max77.9
KnowledgeMAI-Thinking-172.5Margin← 8.3Qwen3.7 Max64.2
MathMAI-Thinking-189.7Margin→ 7.4Qwen3.7 Max97.1
Inst. FollowingMAI-Thinking-185.0Margin← 0.6Qwen3.7 Max84.4
ReasoningMAI-Thinking-1Not measuredMarginNo overlapQwen3.7 Max90.4
MultilingualMAI-Thinking-1Not measuredMarginNo overlapQwen3.7 Max87.0

Decisive benchmark drivers

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

More
A · MAI-Thinking-1B · Qwen3.7 Max

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 46%B 69.7%
    Winner: Qwen3.7 MaxΔ 23.7
    Terminal-Bench 2.0: MAI-Thinking-1 scored 46%; Qwen3.7 Max scored 69.7%. Qwen3.7 Max wins this benchmark.

  2. HMMT Feb 2026

    Math
    Source ↗
    A 84.9%B 97.1%
    Winner: Qwen3.7 MaxΔ 12.2
    HMMT Feb 2026: MAI-Thinking-1 scored 84.9%; Qwen3.7 Max scored 97.1%. Qwen3.7 Max wins this benchmark.

  3. GPQA

    Knowledge
    Source ↗
    A 84.2%B 92.4%
    Winner: Qwen3.7 MaxΔ 8.2
    GPQA: MAI-Thinking-1 scored 84.2%; Qwen3.7 Max scored 92.4%. Qwen3.7 Max wins this benchmark.

  4. SWE-bench Pro

    Coding
    Source ↗
    A 52.8%B 60.6%
    Winner: Qwen3.7 MaxΔ 7.8
    SWE-bench Pro: MAI-Thinking-1 scored 52.8%; Qwen3.7 Max scored 60.6%. Qwen3.7 Max wins this benchmark.

  5. SWE-bench Verified

    Coding
    Source ↗
    A 73.5%B 80.4%
    Winner: Qwen3.7 MaxΔ 6.9
    SWE-bench Verified: MAI-Thinking-1 scored 73.5%; Qwen3.7 Max scored 80.4%. Qwen3.7 Max wins this benchmark.

Operational comparison

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

MetricMAI-Thinking-1Qwen3.7 MaxComparison
Input / output priceUSD per 1M tokensMAI-Thinking-1Not availableQwen3.7 MaxNot availableA complete price comparison is not available.
Generation speedtokens per secondMAI-Thinking-1Not availableQwen3.7 MaxNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenMAI-Thinking-1Not availableQwen3.7 MaxNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensMAI-Thinking-1256KQwen3.7 Max1MQwen3.7 Max lists the larger context window.

Benchmark Deep Dive

AgenticQwen3.7 Max wins
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
Terminal-Bench 2.0Source 46%69.7%Qwen3.7 Max leads
QwenClawBenchSource —64.3%Not comparable
QwenWebBenchSource —1568Not comparable
Claw-EvalSource —65.2%Not comparable
BFCL v4Source —75.0%Not comparable
MCP AtlasSource —76.4%Not comparable
VITA-BenchSource —47.9%Not comparable
HLE w/ toolsSource —53.5%Not comparable
AA Agentic IndexSource —30.6%Not comparable
τ²-bench resultsSource —94.7%Not comparable
GDPval-AASource —38.7%Not comparable
GDPval-AASource —1273Not comparable
Gert LabsSource —64.27%Not comparable
ResearchClawBenchSource —18.7%Not comparable
AA BriefcaseSource —908Not comparable
AA AutomationBenchSource —25.6%Not comparable
AA EnterpriseOps-GymSource —45.0%Not comparable
AA ITBenchSource —42.5%Not comparable
terminalBenchHardSource —50.8%Not comparable
aaTerminalBench21Source —74.5%Not comparable
AA Harvey LABSource —83.4%Not comparable
CodingQwen3.7 Max wins
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
SWE-bench VerifiedSource 73.5%80.4%Qwen3.7 Max leads
SWE-bench ProSource 52.8%60.6%Qwen3.7 Max leads
Terminal-Bench 2.0Source 46.0%69.7%Qwen3.7 Max leads
SWE MultilingualSource —78.3%Not comparable
NL2RepoSource —47.2%Not comparable
SciCodeSource —53.5%Not comparable
LiveCodeBenchSource —91.6%Not comparable
AA Coding IndexSource —66.0%Not comparable
AA-SciCodeSource —48.8%Not comparable
Reasoning
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
Graphwalks BFS 128KSource 90%—Not comparable
MRCRv2Source —90.4%Not comparable
CritPtSource —13.4%Not comparable
AA-LCRSource —69.0%Not comparable
KnowledgeMAI-Thinking-1 wins
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
GPQASource 84.2%92.4%Qwen3.7 Max leads
GPQA-DSource 84.2%92.4%Qwen3.7 Max leads
MMLU-ProSource 85%89.6%Qwen3.7 Max leads
SimpleQASource 31%—Not comparable
HLESource —41.4%Not comparable
MMLU-ReduxSource —95%Not comparable
SuperGPQASource —73.6%Not comparable
MMMLUSource —90.3%Not comparable
Artificial Analysis Intelligence IndexSource —46.0%Not comparable
AA-GPQA DiamondSource —92.3%Not comparable
AA-HLESource —38.1%Not comparable
AA-Omniscience IndexSource —14.1%Not comparable
AA-Omniscience AccuracySource —30.1%Not comparable
AA-Omniscience Hallucination RateSource —22.9%Not comparable
MathQwen3.7 Max wins
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
AIME 2025Source 97%—Not comparable
AIME26Source 94.5%—Not comparable
HMMT Feb 2026Source 84.9%97.1%Qwen3.7 Max leads
IMOAnswerBenchSource —90.0%Not comparable
ApexSource —44.5%Not comparable
Multilingual
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
MMLU-ProXSource —87%Not comparable
NOVA-63Source —59.0%Not comparable
INCLUDESource —86.2%Not comparable
MAXIFESource —89.2%Not comparable
PolyMathSource —86.5%Not comparable
Multimodal
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
Design Arena WebsiteSource —1293Not comparable
Inst. FollowingMAI-Thinking-1 wins
BenchmarkMAI-Thinking-1Qwen3.7 MaxResult
IFBenchSource 85%79.1%MAI-Thinking-1 leads
IFEvalSource —94.3%Not comparable
AA-IFBenchSource —80.5%Not comparable
Frequently Asked Questions (6)

Which is better, MAI-Thinking-1 or Qwen3.7 Max?

MAI-Thinking-1 and Qwen3.7 Max 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, MAI-Thinking-1 or Qwen3.7 Max?

MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 64.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, MAI-Thinking-1 or Qwen3.7 Max?

Qwen3.7 Max has the edge for coding in this comparison, averaging 77.9 versus 65.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Which is better for math, MAI-Thinking-1 or Qwen3.7 Max?

Qwen3.7 Max has the edge for math in this comparison, averaging 97.1 versus 89.7. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, MAI-Thinking-1 or Qwen3.7 Max?

Qwen3.7 Max has the edge for agentic tasks in this comparison, averaging 69.7 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Which is better for instruction following, MAI-Thinking-1 or Qwen3.7 Max?

MAI-Thinking-1 has the edge for instruction following in this comparison, averaging 85 versus 84.4. Inside this category, IFBench is the benchmark that creates the most daylight between them.

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