What are Qwen3.7's benchmark scores?

As of 24 Oct 2026, Qwen3.7 (max effort) scores 60.6 ±3.8 on the BenchLeader Index, strongest in instruction following (78) and weakest in agents & tools (49). That rests on 29 independent benchmark results, and every score on this page links to its publisher.

How does Qwen3.7 rank?

Qwen3.7 (max effort) is #107 of 785 ranked configurations on 24 Oct 2026. 204 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.

How much does Qwen3.7 cost per 1M tokens?

As of 24 Oct 2026, Qwen3.7 costs $2.50 per 1M input tokens and $7.50 per 1M output tokens, $3.75 blended (three input tokens per output token).

Is Qwen3.7 better than GPT-5.6 Sol?

As of 24 Oct 2026, GPT-5.6 Sol (max) leads on quality (68.0 vs 60.6 on the BenchLeader Index), but Qwen3.7 (max) costs 2.1× less, so it is the better buy unless you need the extra quality. The head-to-head page has the benchmark-by-benchmark detail.

When was Qwen3.7 released?

Alibaba released Qwen3.7 on 19 May 2026. BenchLeader has results for it at 3 reasoning-effort settings.

AlibabaReasoning modelCompare with another model

Qwen3.7

Reasoning effort

Qwen3.7 is an Alibaba proprietary reasoning model, released 19 May 2026. Its best configuration (max reasoning effort) ranks #107 of 785 on the BenchLeader Index at 60.6 ±3.8, in the upper half. The ± is the point: 204 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in instruction following (78) and lowest in agents & tools (49). At $3.75 per million tokens blended it is among the most expensive ranked models. Output speed of 201 tokens per second puts it in the fastest quarter, with a first answer in 14.1 s. It has been measured at 3 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 22 Oct 2026.

Blended price: $3.75/M; $2.50 in · $7.50 out
Output speed: 201 tok/s; measured by Artificial Analysis
First answer: 14 s; first token 1.06 s
Context: 1M
Full answer: 17 s; median, reasoning included
Cost per run: $1.15; one full Intelligence Index run
Released: 19 May 2026

How it scores by categoryDashed line = average model (50). One step of 15 = one standard deviation.

Overall index61
Reasoning65
Coding59
Agents & tools49
Maths58
Knowledge63
Instruction following78
Human preference57
Long context65
Composite62

Reasoning-effort configurations

The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.

Effort	Index	Rank	Speed	First answer	Chat reply cost	Categories
no reasoning	–	–	76 tok/s	1.06 s	–
xhigh	–	–	76 tok/s	1.06 s	–
maxbest	60.6	#107	201 tok/s	14 s	$0.0033	Agents & tools 49 · Coding 59 · Composite 62 · Human preference 57 · Instruction following 78 · Knowledge 63 · Long context 65 · Maths 58 · Reasoning 65

How its index has moved

8 Sept 2026 to 23 Oct 2026

The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.

Benchmark results

See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.

Reasoning

Benchmark	no reasoning	max	Source
GPQA Diamond	–	90.9%#35	Epoch AI Benchmarking Hub
SimpleBench	–	70.4%#13	SimpleBench
Arena Hard Prompts	–	1495#41	Arena (LMArena)
LiveBench 1.0 Reasoningnot in index	–	83.3%#43	LiveBench
GPQA Diamond (AA)not in index	–	92.3%#36	Artificial Analysis
Humanity's Last Exam (AA)not in index	–	40.5%#85	Artificial Analysis
GPQA Diamond (Vals)not in index	–	90.2%#25	Vals AI
CritPt	–	13.4%#101	Artificial Analysis
Chess Puzzlesnot in index	–	26.0%#76	Epoch AI Benchmarking Hub
Mystery Game Puzzlesnot in index	26.0%#43	32.0%#30	Epoch AI Benchmarking Hub
LMCAnot in index	–	44.0%#96	Epoch AI Benchmarking Hub
DTBenchnot in index	–	92.3%#70	Epoch AI Benchmarking Hub

Coding

Benchmark	max	Source
SWE-bench Verified (Epoch)	77.3%#7	Epoch AI Benchmarking Hub
SciCode	49.5%#114	SciCode
Arena Coding	1524#28	Arena (LMArena)
Arena WebDev	1515#55	Arena (LMArena)
LiveBench 1.0 Codingnot in index	74.2%#53	LiveBench
SciCode (AA)not in index	49.5%#116	Artificial Analysis
LiveCodeBench	87.1%#18	Vals AI
SWE-bench (Vals)not in index	68.8%#66	Vals AI
Code Migrationnot in index	13.1%#58	Vals AI
Vibe Code Bench v1.1not in index	47.7%#64	Vals AI
ALE-Benchnot in index	1189.4#43	Epoch AI Benchmarking Hub
Terminal-Bench 4.0 (AA)not in index	1.5%#122	Artificial Analysis
Terminal-Bench 2.1 (AA)not in index	74.5%#65	Artificial Analysis
Startrise Frontendnot in index	63.6%#27	Startrise

Agents & tools

Benchmark	max	Source
Arena Agent	-6.2#41	Arena (LMArena)
LiveBench Agentic Codingnot in index	43.6%#56	LiveBench
Terminal-Bench Hard	50.8%#22	Artificial Analysis
τ²-Bench Telecom (AA)not in index	94.7%#29	Artificial Analysis
Terminal-Bench 2.1 (Vals)	61.0%#39	Vals AI
τ³-Banking (AA)	11.8%#136	Artificial Analysis
ITBench SRE (AA)not in index	42.5%#15	Artificial Analysis
Analyst Agent (AA)not in index	18.8%#37	Artificial Analysis
Finance Agent v2not in index	47.8%#52	Vals AI
Harvey's Legal Agent Benchmark v1not in index	1.7%#48	Vals AI
Legal Research Benchnot in index	25.5%#55	Vals AI
Tax Agent Benchnot in index	15.8%#51	Vals AI
Terminal-Bench 2.0 (Vals)not in index	59.2%#9	Vals AI
GBAEvalnot in index	0.4%#20	Epoch AI Benchmarking Hub
AutomationBenchnot in index	23.0%#130	Artificial Analysis
GDP.pdf (AA)not in index	8.6%#140	Artificial Analysis
EnterpriseOps-Gymnot in index	45.0%#14	Artificial Analysis

Maths

Benchmark	max	Source
FrontierMath Tiers 1–3	64.6%#37	Epoch AI Benchmarking Hub
FrontierMath Tier 4	34.1%#35	Epoch AI Benchmarking Hub
OTIS Mock AIME	95.6%#44	Epoch AI Benchmarking Hub
ProofBench	26.0%#44	Vals AI
LiveBench Mathematicsnot in index	85.3%#54	LiveBench
Arena Maths	1484#35	Arena (LMArena)

Knowledge

Benchmark	xhigh	max	Source
SimpleQA Verified	–	55.8%#21	Epoch AI Benchmarking Hub
LiveBench 1.0 Data Analysisnot in index	–	71.8%#46	LiveBench
AA-Omniscience	–	13.5#89	Artificial Analysis
MMLU-Pro	–	89.3%#12	Vals AI
LegalBench	–	84.9%#28	Vals AI
CorpFin	–	63.7%#41	Vals AI
TaxEval	–	75.3%#19	Vals AI
Excel Modeling Benchmarknot in index	–	57.0%#42	Vals AI
MedCodenot in index	–	38.8%#67	Vals AI
MedScribenot in index	–	79.4%#61	Vals AI
DrugDiscoveryBenchnot in index	29.3%#16	–	Scale AI SEAL
EBR-benchnot in index	–	9.5%#22	Epoch AI Benchmarking Hub
AA-Omniscience: accuracynot in index	–	31.1%#174	Artificial Analysis
AA-Omniscience: non-hallucinationnot in index	–	74.4%#25	Artificial Analysis

Instruction following

Benchmark	max	Source
LiveBench Languagenot in index	79.7%#33	LiveBench
LiveBench Instruction Followingnot in index	74.0%#14	LiveBench
IFBench	80.5%#7	Artificial Analysis
Arena Instruction Followingnot in index	1466#43	Arena (LMArena)

Human preference

Benchmark	max	Source
Arena Text	1474#40	Arena (LMArena)
EQ-Bench 4	1110#22	EQ-Bench
Arena Creative Writingnot in index	1438#59	Arena (LMArena)
Arena Multi-turnnot in index	1482#36	Arena (LMArena)
Arena Longer Queriesnot in index	1491#26	Arena (LMArena)

Long context

Benchmark	max	Source	Trend
AA-LCR	79.0%#106	Artificial Analysis
MLCRnot in index	14.4%#84	Artificial Analysis

Composite

Benchmark	max	Source
Epoch Capabilities Indexnot in index	154.0#44	Epoch AI Benchmarking Hub
LiveBench 1.0not in index	73.1%#47	LiveBench
AA Intelligence Index v4.3.2	29.5#128	Artificial Analysis

Where to run it

Every provider serving this model through OpenRouter, with throughput and first-token latency measured on live traffic over the last 30 minutes and each provider’s own price. Purple marks the best in each column.

Provider	Speed	First token	Input $/M	Output $/M	Context	Quantisation
Alibaba Cloud Int.	70 tok/s	1.06 s	$1.48	$4.42	1M	–
Alibaba Cloud Int.	69 tok/s	1.17 s	$2.00	$6.00	1M	–

What a task costs

Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.500 per 1M. Reasoning tokens are not modelled.

Workload	Tokens in / out	Cost	With caching	Time
Chat reply	400 / 300	$0.0033	$0.0027	15.6 s
Summarize a 30-page report	12,000 / 600	$0.035	$0.017	17.1 s
Code edit	6,000 / 1,500	$0.026	$0.017	21.6 s
Agentic coding session	60,000 / 4,000	$0.180	$0.090	34.0 s
Structured extraction	2,000 / 200	$0.0065	$0.0035	15.1 s

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Questions people ask

What are Qwen3.7's benchmark scores?: As of 24 Oct 2026, Qwen3.7 (max effort) scores 60.6 ±3.8 on the BenchLeader Index, strongest in instruction following (78) and weakest in agents & tools (49). That rests on 29 independent benchmark results, and every score on this page links to its publisher.
How does Qwen3.7 rank?: Qwen3.7 (max effort) is #107 of 785 ranked configurations on 24 Oct 2026. 204 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.
How much does Qwen3.7 cost per 1M tokens?: As of 24 Oct 2026, Qwen3.7 costs $2.50 per 1M input tokens and $7.50 per 1M output tokens, $3.75 blended (three input tokens per output token).
Is Qwen3.7 better than GPT-5.6 Sol?: As of 24 Oct 2026, GPT-5.6 Sol (max) leads on quality (68.0 vs 60.6 on the BenchLeader Index), but Qwen3.7 (max) costs 2.1× less, so it is the better buy unless you need the extra quality. The head-to-head page has the benchmark-by-benchmark detail.
When was Qwen3.7 released?: Alibaba released Qwen3.7 on 19 May 2026. BenchLeader has results for it at 3 reasoning-effort settings.

Data as of 24 Oct 2026. Compare these configurations.

Cite as: BenchLeader, “Qwen3.7: benchmarks, pricing, speed and rank”, data as of 24 Oct 2026, https://www.benchleader.com/models/qwen3-7.