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Model comparison

GPT-5.6 Luna vs Qwen3.7 Plus

Data verified

Head-to-head evidence from 22 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

67.17/100
Margin
0.0pts
winning →
67.22/100
2 category wins3 category wins

Public leaderboard positions: GPT-5.6 Luna #22 (Estimated); Qwen3.7 Plus #21 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. GPT-5.6 Luna and Qwen3.7 Plus share 22 comparable benchmark results. 5 of 8 categories are comparable. 19 results are unique to GPT-5.6 Luna; 47 to Qwen3.7 Plus.

Updated July 23, 2026
Shared results
22
GPT-5.6 Luna only
19
Qwen3.7 Plus only
47
Comparable categories
5 / 8

Pick Qwen3.7 Plus if you want the stronger benchmark profile. GPT-5.6 Luna only becomes the better choice if knowledge is the priority.

Confidence note. This is a partial-evidence comparison with 22 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

Qwen3.7 Plus has the cleaner BenchAlign overall profile here, landing at 67.22 versus 67.17. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Qwen3.7 Plus's sharpest advantage is in mathematics, where it averages 92.9 against 73.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 84.7% to 70.3%. GPT-5.6 Luna does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

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 GPT-5.6 Luna and Qwen3.7 Plus
CategoryGPT-5.6 LunaΔQwen3.7 Plus
KnowledgeGPT-5.6 Luna92.3Margin← 32.2Qwen3.7 Plus60.1
MathGPT-5.6 Luna73.6Margin→ 19.3Qwen3.7 Plus92.9
CodingGPT-5.6 Luna62.7Margin→ 12.9Qwen3.7 Plus75.6
AgenticGPT-5.6 Luna84.1Margin← 12.4Qwen3.7 Plus71.7
MultimodalGPT-5.6 Luna78.4Margin→ 3.1Qwen3.7 Plus81.5
ReasoningGPT-5.6 LunaNot measuredMarginNo overlapQwen3.7 Plus91.7
MultilingualGPT-5.6 LunaNot measuredMarginNo overlapQwen3.7 Plus85.4
Inst. FollowingGPT-5.6 LunaNot measuredMarginNo overlapQwen3.7 Plus84.5

Decisive benchmark drivers

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

More
A · GPT-5.6 LunaB · Qwen3.7 Plus

  1. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 84.7%B 70.3%
    Winner: GPT-5.6 LunaΔ 14.4
    Terminal-Bench 2.0: GPT-5.6 Luna scored 84.7%; Qwen3.7 Plus scored 70.3%. GPT-5.6 Luna wins this benchmark.

  2. SWE-bench Pro

    Coding
    Source ↗
    A 62.7%B 57.6%
    Winner: GPT-5.6 LunaΔ 5.1
    SWE-bench Pro: GPT-5.6 Luna scored 62.7%; Qwen3.7 Plus scored 57.6%. GPT-5.6 Luna wins this benchmark.

  3. GPQA

    Knowledge
    Source ↗
    A 92.3%B 90.3%
    Winner: GPT-5.6 LunaΔ 2
    GPQA: GPT-5.6 Luna scored 92.3%; Qwen3.7 Plus scored 90.3%. GPT-5.6 Luna wins this benchmark.

  4. MMMU-Pro

    Multimodal
    Source ↗
    A 78.4%B 79%
    Winner: Qwen3.7 PlusΔ 0.6
    MMMU-Pro: GPT-5.6 Luna scored 78.4%; Qwen3.7 Plus scored 79%. Qwen3.7 Plus wins this benchmark.

Operational comparison

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

MetricGPT-5.6 LunaQwen3.7 PlusComparison
Input / output priceUSD per 1M tokensGPT-5.6 Luna$1 input / $6 outputQwen3.7 PlusNot availableA complete price comparison is not available.
Generation speedtokens per secondGPT-5.6 LunaNot availableQwen3.7 PlusNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGPT-5.6 LunaNot availableQwen3.7 PlusNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGPT-5.6 Luna1MQwen3.7 Plus1MListed context windows are equal.

Benchmark Deep Dive

AgenticGPT-5.6 Luna wins
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
Terminal-Bench 2.0Source 84.7%70.3%GPT-5.6 Luna leads
BrowseCompSource 83.3%—Not comparable
OSWorld 2.0Source 45.6%2.8%GPT-5.6 Luna leads
CyberGymSource 77.9%—Not comparable
ExploitGymSource 12.4%—Not comparable
ToolathlonSource 53.4%—Not comparable
AA Agentic IndexSource 45.6%20.8%GPT-5.6 Luna leads
GDPval-AASource 54.2%21.8%GPT-5.6 Luna leads
GDPval-AASource 1584936GPT-5.6 Luna leads
AA Harvey LABSource 87.9%—Not comparable
AA ITBenchSource 40.3%—Not comparable
AA Tau3 BankingSource 27.2%—Not comparable
AA AutomationBenchSource 42.2%—Not comparable
aaTerminalBench21Source 80.9%—Not comparable
APEX-Agents-AASource 35.8%22.4%GPT-5.6 Luna leads
QwenClawBenchSource —61.8%Not comparable
QwenWebBenchSource —1536Not comparable
Claw-EvalSource —62.7%Not comparable
BFCL v4Source —72.9%Not comparable
MCP AtlasSource —73.2%Not comparable
VITA-BenchSource —45.6%Not comparable
DeepPlanningSource —62.3%Not comparable
OSWorld-VerifiedSource —73.3%Not comparable
AndroidWorldSource —81.0%Not comparable
τ²-bench resultsSource —93%Not comparable
CodingQwen3.7 Plus wins
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
SWE-bench ProSource 62.7%57.6%GPT-5.6 Luna leads
Terminal-Bench 2.0Source 84.7%70.3%GPT-5.6 Luna leads
deepSweSource 67.2%—Not comparable
FrontierCode 1.1 ExtendedSource 55.1%—Not comparable
cursorBench32Source 61.1%—Not comparable
AA Coding IndexSource 71.5%55.9%GPT-5.6 Luna leads
AA-SciCodeSource 52.5%45.5%GPT-5.6 Luna leads
SWE-bench VerifiedSource —77.7%Not comparable
SWE MultilingualSource —75.8%Not comparable
NL2RepoSource —41.1%Not comparable
SciCodeSource —51.3%Not comparable
LiveCodeBenchSource —89.6%Not comparable
Reasoning
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
ARC-AGI-3Source 0.2%—Not comparable
AA-LCRSource 74.0%65.0%GPT-5.6 Luna leads
CritPtSource 20.6%9.1%GPT-5.6 Luna leads
MRCRv2Source —91.7%Not comparable
KnowledgeGPT-5.6 Luna wins
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
GPQASource 92.3%90.3%GPT-5.6 Luna leads
GPQA-DSource 92.3%90.3%GPT-5.6 Luna leads
HealthBench ProfessionalSource 55.7%—Not comparable
HealthBench HardSource 32.0%—Not comparable
Artificial Analysis Intelligence IndexSource 51.2%39.0%GPT-5.6 Luna leads
AA-GPQA DiamondSource 91.1%90.0%GPT-5.6 Luna leads
AA-HLESource 37.2%33.4%GPT-5.6 Luna leads
AA-Omniscience IndexSource -11.2%2.4%Qwen3.7 Plus leads
AA-Omniscience AccuracySource 41.5%22.2%GPT-5.6 Luna leads
AA-Omniscience Hallucination RateSource 90.1%25.5%Qwen3.7 Plus leads
HLESource —34.7%Not comparable
MMLU-ProSource —88.5%Not comparable
MMLU-ReduxSource —94.5%Not comparable
SuperGPQASource —71.4%Not comparable
MMMLUSource —89.0%Not comparable
MathQwen3.7 Plus wins
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
FrontierMath (legacy)Source 78.6%—Not comparable
FrontierMath v2 (Tiers 1-3)Source 78.600%—Not comparable
FrontierMath v2 (Tier 4)Source 58.500%—Not comparable
HMMT Feb 2026Source —92.9%Not comparable
IMOAnswerBenchSource —86.0%Not comparable
ApexSource —22.7%Not comparable
Multilingual
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
MMLU-ProXSource —85.4%Not comparable
NOVA-63Source —58.8%Not comparable
INCLUDESource —83.0%Not comparable
MAXIFESource —88.8%Not comparable
PolyMathSource —84.0%Not comparable
MultimodalQwen3.7 Plus wins
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
MMMU-ProSource 78.4%79%Qwen3.7 Plus leads
MMMU-Pro w/ PythonSource 79.5%—Not comparable
AA-MMMU-ProSource 78.6%80.5%Qwen3.7 Plus leads
MathVisionSource —90.3%Not comparable
CharXivSource —85.9%Not comparable
ERQASource —69.8%Not comparable
MedXpertQA (MM)Source —71.0%Not comparable
ScreenSpot ProSource —79.0%Not comparable
SimpleVQASource —81.7%Not comparable
MMSearch-PlusSource —41.4%Not comparable
RealWorldQASource —86.9%Not comparable
OmniDocBench 1.5Source —91.4%Not comparable
OCRBench V2Source —70.7%Not comparable
ODINW13Source —51.1%Not comparable
Video-MME (with subtitle)Source —88.0%Not comparable
VideoMMMUSource —85.4%Not comparable
MLVU (M-Avg)Source —87.4%Not comparable
Design Arena WebsiteSource —1288Not comparable
Inst. Following
BenchmarkGPT-5.6 LunaQwen3.7 PlusResult
IFEvalSource —94.6%Not comparable
IFBenchSource —79.1%Not comparable
AA-IFBenchSource —78.0%Not comparable
Frequently Asked Questions (6)

Which is better, GPT-5.6 Luna or Qwen3.7 Plus?

Qwen3.7 Plus is ahead on BenchLM's BenchAlign leaderboard, 67.22 to 67.17. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 84.7% and 70.3%.

Which is better for knowledge tasks, GPT-5.6 Luna or Qwen3.7 Plus?

GPT-5.6 Luna has the edge for knowledge tasks in this comparison, averaging 92.3 versus 60.1. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.

Which is better for coding, GPT-5.6 Luna or Qwen3.7 Plus?

Qwen3.7 Plus has the edge for coding in this comparison, averaging 75.6 versus 62.7. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for math, GPT-5.6 Luna or Qwen3.7 Plus?

Qwen3.7 Plus has the edge for math in this comparison, averaging 92.9 versus 73.6. GPT-5.6 Luna stays close enough that the answer can still flip depending on your workload.

Which is better for agentic tasks, GPT-5.6 Luna or Qwen3.7 Plus?

GPT-5.6 Luna has the edge for agentic tasks in this comparison, averaging 84.1 versus 71.7. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, GPT-5.6 Luna or Qwen3.7 Plus?

Qwen3.7 Plus has the edge for multimodal and grounded tasks in this comparison, averaging 81.5 versus 78.4. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.

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