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Model comparison

MAI-Thinking-1 vs Qwen3.6-27B

Data verified

Head-to-head evidence from 8 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

N/A
No comparison
53.82/100
2 category wins2 category wins

Public leaderboard positions: MAI-Thinking-1 unranked (Not scored); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. MAI-Thinking-1 and Qwen3.6-27B share 8 comparable benchmark results. 4 of 8 categories are comparable. 5 results are unique to MAI-Thinking-1; 46 to Qwen3.6-27B.

Updated July 23, 2026
Shared results
8
MAI-Thinking-1 only
5
Qwen3.6-27B only
46
Comparable categories
4 / 8

Treat this as a split decision. MAI-Thinking-1 makes more sense if knowledge is the priority; Qwen3.6-27B is the better fit if agentic is the priority or you need the larger 262K context window.

Confidence note. This is a partial-evidence comparison with 8 shared benchmark results across 4 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

MAI-Thinking-1 and Qwen3.6-27B 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.

Qwen3.6-27B gives you the larger context window at 262K, 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 Qwen3.6-27B
CategoryMAI-Thinking-1ΔQwen3.6-27B
KnowledgeMAI-Thinking-172.5Margin← 19.2Qwen3.6-27B53.3
AgenticMAI-Thinking-146.0Margin→ 13.3Qwen3.6-27B59.3
CodingMAI-Thinking-165.5Margin→ 12.0Qwen3.6-27B77.5
MathMAI-Thinking-189.7Margin← 0.5Qwen3.6-27B89.2
MultimodalMAI-Thinking-1Not measuredMarginNo overlapQwen3.6-27B76.7
Inst. FollowingMAI-Thinking-185.0MarginNo overlapQwen3.6-27BNot measured

Decisive benchmark drivers

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

More
A · MAI-Thinking-1B · Qwen3.6-27B

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 46%B 59.3%
    Winner: Qwen3.6-27BΔ 13.3
    Terminal-Bench 2.0: MAI-Thinking-1 scored 46%; Qwen3.6-27B scored 59.3%. Qwen3.6-27B wins this benchmark.

  2. SWE-bench Verified

    Coding
    Source ↗
    A 73.5%B 77.2%
    Winner: Qwen3.6-27BΔ 3.7
    SWE-bench Verified: MAI-Thinking-1 scored 73.5%; Qwen3.6-27B scored 77.2%. Qwen3.6-27B wins this benchmark.

  3. GPQA

    Knowledge
    Source ↗
    A 84.2%B 87.8%
    Winner: Qwen3.6-27BΔ 3.6
    GPQA: MAI-Thinking-1 scored 84.2%; Qwen3.6-27B scored 87.8%. Qwen3.6-27B wins this benchmark.

  4. MMLU-Pro

    Knowledge
    Source ↗
    A 85%B 86.2%
    Winner: Qwen3.6-27BΔ 1.2
    MMLU-Pro: MAI-Thinking-1 scored 85%; Qwen3.6-27B scored 86.2%. Qwen3.6-27B wins this benchmark.

  5. SWE-bench Pro

    Coding
    Source ↗
    A 52.8%B 53.5%
    Winner: Qwen3.6-27BΔ 0.7
    SWE-bench Pro: MAI-Thinking-1 scored 52.8%; Qwen3.6-27B scored 53.5%. Qwen3.6-27B wins this benchmark.

Operational comparison

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

MetricMAI-Thinking-1Qwen3.6-27BComparison
Input / output priceUSD per 1M tokensMAI-Thinking-1Not availableQwen3.6-27B$0 input / $0 outputA complete price comparison is not available.
Generation speedtokens per secondMAI-Thinking-1Not availableQwen3.6-27BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenMAI-Thinking-1Not availableQwen3.6-27BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensMAI-Thinking-1256KQwen3.6-27B262KQwen3.6-27B lists the larger context window.

Benchmark Deep Dive

AgenticQwen3.6-27B wins
BenchmarkMAI-Thinking-1Qwen3.6-27BResult
Terminal-Bench 2.0Source 46%59.3%Qwen3.6-27B leads
Claw-EvalSource —72.4%Not comparable
QwenClawBenchSource —53.4%Not comparable
QwenWebBenchSource —1487Not comparable
AndroidWorldSource —70.3%Not comparable
AA Agentic IndexSource —27.0%Not comparable
τ²-bench resultsSource —94.2%Not comparable
GDPval-AASource —32.0%Not comparable
GDPval-AASource —1140Not comparable
Gert LabsSource —54.84%Not comparable
CodingQwen3.6-27B wins
BenchmarkMAI-Thinking-1Qwen3.6-27BResult
SWE-bench VerifiedSource 73.5%77.2%Qwen3.6-27B leads
SWE-bench ProSource 52.8%53.5%Qwen3.6-27B leads
Terminal-Bench 2.0Source 46.0%59.3%Qwen3.6-27B leads
SWE MultilingualSource —71.3%Not comparable
LiveCodeBenchSource —83.9%Not comparable
NL2RepoSource —36.2%Not comparable
AA Coding IndexSource —53.7%Not comparable
AA-SciCodeSource —39.8%Not comparable
Reasoning
BenchmarkMAI-Thinking-1Qwen3.6-27BResult
Graphwalks BFS 128KSource 90%—Not comparable
AA-LCRSource —68.7%Not comparable
CritPtSource —1.1%Not comparable
KnowledgeMAI-Thinking-1 wins
BenchmarkMAI-Thinking-1Qwen3.6-27BResult
GPQASource 84.2%87.8%Qwen3.6-27B leads
GPQA-DSource 84.2%—Not comparable
MMLU-ProSource 85%86.2%Qwen3.6-27B leads
SimpleQASource 31%—Not comparable
MMLU-ReduxSource —93.5%Not comparable
SuperGPQASource —66%Not comparable
C-EvalSource —91.4%Not comparable
HLESource —24%Not comparable
Artificial Analysis Intelligence IndexSource —37.0%Not comparable
AA-GPQA DiamondSource —84.2%Not comparable
AA-HLESource —21.6%Not comparable
AA-Omniscience IndexSource —-19.8%Not comparable
AA-Omniscience AccuracySource —19.2%Not comparable
AA-Omniscience Hallucination RateSource —48.3%Not comparable
MathMAI-Thinking-1 wins
BenchmarkMAI-Thinking-1Qwen3.6-27BResult
AIME 2025Source 97%—Not comparable
AIME26Source 94.5%94.1%MAI-Thinking-1 leads
HMMT Feb 2026Source 84.9%84.3%MAI-Thinking-1 leads
HMMT Feb 2025Source —93.8%Not comparable
HMMT Nov 2025Source —90.7%Not comparable
MMAnswerBenchSource —80.8%Not comparable
Multimodal
BenchmarkMAI-Thinking-1Qwen3.6-27BResult
MMMUSource —82.9%Not comparable
MMMU-ProSource —75.8%Not comparable
RealWorldQASource —84.1%Not comparable
DynaMathSource —85.6%Not comparable
MStarSource —81.4%Not comparable
SimpleVQASource —56.1%Not comparable
CharXivSource —78.4%Not comparable
CC-OCRSource —81.2%Not comparable
CountBenchSource —97.8%Not comparable
RefCOCO (avg)Source —92.5%Not comparable
ERQASource —62.5%Not comparable
Video-MME (with subtitle)Source —87.7%Not comparable
VideoMMMUSource —84.4%Not comparable
MLVU (M-Avg)Source —86.6%Not comparable
V*Source —94.7%Not comparable
AA-MMMU-ProSource —74.6%Not comparable
Inst. Following
BenchmarkMAI-Thinking-1Qwen3.6-27BResult
IFBenchSource 85%—Not comparable
AA-IFBenchSource —67.6%Not comparable
Frequently Asked Questions (5)

Which is better, MAI-Thinking-1 or Qwen3.6-27B?

MAI-Thinking-1 and Qwen3.6-27B 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 Qwen3.6-27B?

MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 72.5 versus 53.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, MAI-Thinking-1 or Qwen3.6-27B?

Qwen3.6-27B has the edge for coding in this comparison, averaging 77.5 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 Qwen3.6-27B?

MAI-Thinking-1 has the edge for math in this comparison, averaging 89.7 versus 89.2. 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 Qwen3.6-27B?

Qwen3.6-27B has the edge for agentic tasks in this comparison, averaging 59.3 versus 46. Inside this category, Terminal-Bench 2.0 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.

MAI-Thinking-1
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Qwen3.6-27B
API / mo$0
Self-host / mo$429
Break-even—
Model the full break-even

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