Is Gemini 3 Pro better than Qwen3.7?

Gemini 3 Pro and Qwen3.7 (max) are neck and neck on quality (60.2 vs 60.3, within the ±5.4 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2 Nov 2026, so check the category scores for your use.

Is Gemini 3 Pro or Qwen3.7 better for coding?

Qwen3.7 scores higher in coding (59 vs 58 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1440 for Gemini 3 Pro against 1515 for Qwen3.7.

Is Gemini 3 Pro or Qwen3.7 better for agents and tool use?

Gemini 3 Pro scores higher in agentic tasks (62 vs 49 on the category index, where 50 is average).

When was Qwen3.7 released?

Qwen3.7 was released on 19 May 2026.

Gemini 3 Pro vs Qwen3.7

Full profiles: Gemini 3 Pro (Google) and Qwen3.7 (Alibaba): every benchmark, price and rank.

Updated 1 Nov 2026 · Data from 17 sources

As of 2 Nov 2026, Gemini 3 Pro and Qwen3.7 are neck and neck on quality (60.2 vs 60.3 on the BenchLeader Index, inside the ±5.4 margin). Choose Gemini 3 Pro for agents & tools (62 vs 49) and human preference (68 vs 56); choose Qwen3.7 for instruction following (78 vs 60), knowledge (61 vs 56), and maths (58 vs 54).

Key facts (as of 2 Nov 2026)

Gemini 3 Pro scores 60.2 on the BenchLeader Index and Qwen3.7 scores 60.3 (BenchLeader, 2 Nov 2026).
Qwen3.7 costs $3.75 per 1M tokens blended (list price, 2 Nov 2026).
Of the 17 benchmarks both models have, Qwen3.7 leads 9 (BenchLeader, 2 Nov 2026).
On Arena WebDev, Gemini 3 Pro is rated 1440 and Qwen3.7 1515 (LMArena, as published by 2 Nov 2026).

Gemini 3 Pro benchmarks Google

Qwen3.7 benchmarks max Alibaba Add a third model

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use case	Pick	Why	Confidence
Coding	Qwen3.7	59 vs 58 category score; Arena WebDev 1515 vs 1440	Medium
Agents & tool use	Gemini 3 Pro	62 vs 49 category score	High
Maths	Qwen3.7	58 vs 54 category score; Arena Maths 1482 vs 1477	Medium
Reasoning	Either	66 vs 66 category score; GPQA Diamond 92.6% vs 90.9%	Either
Knowledge	Qwen3.7	61 vs 56 category score; MMLU-Pro 89.3% vs 90.1%	Medium
Following instructions	Qwen3.7	78 vs 60 category score; Arena Instruction Following 1465 vs 1472	High
Chat quality (human preference)	Gemini 3 Pro	68 vs 56 on Arena votes	High
High volume on a budget	Neither flagship	A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs	–

Key differences

Gemini 3 Pro and Qwen3.7 (max) are neck and neck on quality (60.2 vs 60.3, within the ±5.4 margin).
Gemini 3 Pro is stronger in agents & tools, human preference, multimodal.
Qwen3.7 (max) is stronger in coding, instruction following, knowledge, maths, reasoning, long context.

At a glance

Spec	Gemini 3 Pro	Qwen3.7
Developer	Google	Alibaba
Released	18 Nov 2025	19 May 2026
Context window (tokens)	–	1,000,000
Compared at	Gemini 3 Pro	Qwen3.7 (max)
Open weights	No	No
Price in / out / cached input per 1M	–	$2.50 / $7.50 / $0.330

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

Category	Gemini 3 Pro	Qwen3.7 (max)	Leader
Reasoning	65.6	66.3	level
Coding	57.8	59.1	Qwen3.7
Agents & tools	61.6	49.0	Gemini 3 Pro
Maths	54.2	58.1	Qwen3.7
Knowledge	55.9	61.2	Qwen3.7
Instruction following	59.9	78.0	Qwen3.7
Human preference	67.7	55.6	Gemini 3 Pro
Multimodal	65.6	–	not comparable
Long context	–	64.3	not comparable

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

Not drawn, measured for fewer than two of these models: Long context, Multimodal.

ModelIndex

Where sources disagree

Across the 17 benchmarks both have, Gemini 3 Pro leads 8, Qwen3.7 leads 9. Every overall index that rates both puts Gemini 3 Pro ahead.

Overall index	Gemini 3 Pro	Qwen3.7 (max)	Leader
BenchLeader Index	60.2	60.3	neck and neck
Arena Text	1485	1474	Gemini 3 Pro

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

Measure	Gemini 3 Pro	Qwen3.7 (max)
Blended price per 1M tokens	–	$3.75
Input / output per 1M	– / –	$2.50 / $7.50
Cached input per 1M	–	$0.330
Price per task: chat reply	–	$0.0033
Price per task: summarize a 30-page report	–	$0.035
Price per task: code edit	–	$0.026
Price per task: agentic coding session	–	$0.180
Price per task: structured extraction	–	$0.0065
Agentic coding session, input mostly cached	–	$0.082
Output speed	–	203 tok/s
Time to first answer	–	14.1 s
Time to a complete answer	–	16.6 s

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3 Pro scores 60.2; Gemini 3 Pro (high) scores 60.1. Qwen3.7 (max) scores 60.3 and takes 14 s to its first answer token. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

138 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

Metric	Publisher	Gemini 3 Pro	Qwen3.7 (max)
BenchLeader Index	BenchLeader	60.2	60.3
Agents & tools score	BenchLeader	61.6	49.0
Coding score	BenchLeader	57.8	59.1
Human preference score	BenchLeader	67.7	55.6
Instruction following score	BenchLeader	59.9	78.0
Knowledge score	BenchLeader	55.9	61.2
Maths score	BenchLeader	54.2	58.1
Multimodal score	BenchLeader	65.6	–
Reasoning score	BenchLeader	65.6	66.3
Long context score	BenchLeader	–	64.3
Blended price $/M	BenchLeader	–	$3.75
Output speed	BenchLeader	–	203 tok/s
Time to first answer	BenchLeader	–	14.1 s
Context window	BenchLeader	–	1,000,000 tokens
Reasoning
GPQA Diamond	Epoch AI Benchmarking Hub	92.6%	90.9%
Humanity's Last Exam	Scale AI / CAIS	37.5%	–
SimpleBench	SimpleBench	76.4%	70.4%
Arena Hard Prompts	Arena (LMArena)	1502	1495
LiveBench 1.0 Reasoning	LiveBench	–	83.3%
GPQA Diamond (AA)	Artificial Analysis	90.8%†	92.3%
Humanity's Last Exam (AA)	Artificial Analysis	39.7%†	40.5%
GPQA Diamond (Vals)	Vals AI	91.7%†	90.2%
Kagi LLM Benchmark	Kagi LLM Benchmark	80.1%	–
GPQA Diamond (HELM)	HELM Capabilities	80.3%	–
ARC-AGI-1	ARC Prize	75.0%	–
ARC-AGI-2	ARC Prize	54.0%	–
CritPt	Artificial Analysis	9.1%†	13.4%
SciPredict	Scale AI SEAL	25.3%	–
Chess Puzzles	Epoch AI Benchmarking Hub	–	26.0%
Mystery Game Puzzles	Epoch AI Benchmarking Hub	–	32.0%
CL-bench	Epoch AI Benchmarking Hub	15.8%	–
LMCA	Epoch AI Benchmarking Hub	–	44.0%
DTBench	Epoch AI Benchmarking Hub	–	92.3%
ForecastBench	ForecastBench	65.2%	–
Coding
SWE-bench Verified (Epoch)	Epoch AI Benchmarking Hub	72.9%	77.3%
SciCode	SciCode	–	49.5%
WeirdML	WeirdML	69.9%	–
GSO-Bench	GSO-Bench	18.6%	–
Arena Coding	Arena (LMArena)	1517	1523

Show all 138 benchmarks

Metric	Publisher	Gemini 3 Pro	Qwen3.7 (max)
Coding
Arena WebDev	Arena (LMArena)	1440	1515
LiveBench 1.0 Coding	LiveBench	–	74.2%
LiveCodeBench	Vals AI	86.4%	87.1%
SWE-bench (Vals)	Vals AI	76.4%†	68.8%
SWE-Bench Pro	Scale AI SEAL	43.3%	–
SWE-bench Verified (bash only)	SWE-bench	74.2%	–
SWE-bench Verified (any scaffold)	SWE-bench	77.4%	–
Code Migration	Vals AI	–	13.1%
Vibe Code Bench v1.1	Vals AI	14.3%†	47.7%
SWE-Bench Pro (private)	Scale AI SEAL	43.3%	–
ALE-Bench	Epoch AI Benchmarking Hub	1176.8	1189.4
AlgoTune	AlgoTune	1.8	–
Terminal-Bench 4.0 (AA)	Artificial Analysis	–	1.5%
Terminal-Bench 2.1 (AA)	Artificial Analysis	–	74.5%
Startrise Frontend	Startrise	–	63.6%
LiveCodeBench (AA)	Artificial Analysis	91.8%†	–
Agents & tools
Terminal-Bench	Terminal-Bench	69.4%	–
GDPval	OpenAI	40.3%	–
Remote Labor Index	Scale AI / CAIS	1.3%	–
Arena Agent	Arena (LMArena)	–	-6.6
LiveBench Agentic Coding	LiveBench	–	43.6%
Terminal-Bench Hard	Artificial Analysis	41.7%†	50.8%
τ²-Bench Telecom (AA)	Artificial Analysis	87.1%†	94.7%
Terminal-Bench 2.1 (Vals)	Vals AI	–	61.0%
MCP Atlas	Scale AI SEAL	70.3%	–
BFCL Overall	Berkeley Function Calling Leaderboard	72.5%	–
τ²-bench	τ²-bench	82.5%†	–
τ³-bench Banking	τ²-bench	18.0%†	–
τ³-Banking (AA)	Artificial Analysis	–	11.8%
ITBench SRE (AA)	Artificial Analysis	–	42.5%
Analyst Agent (AA)	Artificial Analysis	–	18.8%
Finance Agent v2	Vals AI	–	47.8%
Harvey's Legal Agent Benchmark v1	Vals AI	–	1.7%
Legal Research Bench	Vals AI	–	25.5%
Poker Agent	Vals AI	1078.9%	–
Tax Agent Bench	Vals AI	–	15.8%
Terminal-Bench 2.0 (Vals)	Vals AI	55.1%†	59.2%
BALROG	BALROG	58.1%	–
DeepResearch Bench	DeepResearch Bench	46.3%†	–
METR Time Horizons	METR	71.0%	–
GBAEval	Epoch AI Benchmarking Hub	–	0.4%
Vending-Bench 2	Andon Labs	5478.2	–
AutomationBench	Artificial Analysis	–	23.0%
GDP.pdf (AA)	Artificial Analysis	–	8.6%
EnterpriseOps-Gym	Artificial Analysis	–	45.0%
AA-Briefcase v1.1	Artificial Analysis	–	917
Maths
FrontierMath Tiers 1–3	Epoch AI Benchmarking Hub	–	64.6%
FrontierMath Tier 4	Epoch AI Benchmarking Hub	–	34.1%
OTIS Mock AIME	Epoch AI Benchmarking Hub	91.4%	95.6%
ProofBench	Vals AI	20.0%	26.0%
LiveBench Mathematics	LiveBench	–	85.3%
AIME (Vals)	Vals AI	96.7%†	–
MGSM	Vals AI	93.9%†	–
AIME 2026	MathArena	91.7%	–
HMMT February 2026	MathArena	86.4%	–
MathArena Apex	MathArena	23.4%	–
Omni-MATH (HELM)	HELM Capabilities	55.6%	–
MATH 500	Vals AI	96.4%†	–
Arena Maths	Arena (LMArena)	1477	1482
Knowledge
SimpleQA Verified	Epoch AI Benchmarking Hub	–	55.8%
LiveBench 1.0 Data Analysis	LiveBench	–	71.8%
MMLU-Pro	Vals AI	90.1%	89.3%
LegalBench	Vals AI	87.0%†	84.9%
CorpFin	Vals AI	63.7%†	63.7%
TaxEval	Vals AI	72.6%†	75.3%
MedQA	Vals AI	96.0%†	–
PRBench Finance	Scale AI SEAL	39.2%	–
PRBench Legal	Scale AI SEAL	40.6%	–
MultiNRC	Scale AI SEAL	59.0%	–
MMLU-Pro (HELM)	HELM Capabilities	90.3%	–
CaseLaw v2	Vals AI	53.1%†	–
Excel Modeling Benchmark	Vals AI	–	57.0%
MedCode	Vals AI	52.2%†	38.8%
MedScribe	Vals AI	72.0%†	79.4%
DrugDiscoveryBench	Scale AI SEAL	–	29.3%†
EBR-bench	Epoch AI Benchmarking Hub	–	9.5%
Global-MMLU-Lite (AA)	Artificial Analysis	92.2%†	–
Instruction following
LiveBench Language	LiveBench	–	79.7%
LiveBench Instruction Following	LiveBench	–	74.0%
IFBench	Artificial Analysis	70.4%†	80.5%
MultiChallenge	Scale AI SEAL	65.7%	–
TutorBench	Scale AI SEAL	53.7%	–
IFEval (HELM)	HELM Capabilities	87.6%	–
WildBench (HELM)	HELM Capabilities	85.9%	–
Arena Instruction Following	Arena (LMArena)	1472	1465
Human preference
Arena Text	Arena (LMArena)	1485	1474
EQ-Bench 4	EQ-Bench	–	1100
Arena Creative Writing	Arena (LMArena)	1485	1437
Arena Multi-turn	Arena (LMArena)	1496	1482
Arena Longer Queries	Arena (LMArena)	1490	1490
Multimodal
Arena Vision	Arena (LMArena)	1305	–
MMMU-Pro	Artificial Analysis	80.2%†	–
VISTA	Scale AI SEAL	51.5%	–
MMMU-Pro (official)	MMMU	81.0%	–
MMMU-Pro (Vals)	Vals AI	87.5%†	–
MortgageTax	Vals AI	69.1%†	–
AudioMC	Scale AI SEAL	54.6%†	–
AudioMC (text output)	Scale AI SEAL	54.6%†	–
VTB	Scale AI SEAL	26.9%	–
GeoBench	GeoBench	84.0%	–
VPCT	Epoch AI Benchmarking Hub	91.0%	–
Long context
AA-LCR v1.1	Artificial Analysis	76.0%†	79.0%
Arena Document	Arena (LMArena)	1451	–
MLCR	Artificial Analysis	–	14.4%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	153.2	154.2
LiveBench 1.0	LiveBench	–	73.1%
AA Intelligence Index v4.3.2	Artificial Analysis	28.0†	29.5
AA Progress Index v1	Artificial Analysis	290.7†	293.8
HELM Capabilities mean	HELM Capabilities	79.9%	–
Safety & honesty
FORTRESS	Scale AI SEAL	41.7%	–
MASK	Scale AI SEAL	42.6%	–
PropensityBench	Scale AI SEAL	52.9%	–
Metadata
AA Openness Index	Artificial Analysis	5.6†	–

Data as of 2026-11-02. Best configuration of each model; every score links to its source on the model pages.

What changed

1 Nov 2026 Qwen3.7 (max): cached input price moved from $0.50/M to $0.33/M (34% down).
31 Oct 2026 Qwen3.7 (max): cached input price moved from $0.33/M to $0.50/M (52% up).
30 Oct 2026 Qwen3.7 (max): cached input price moved from $0.50/M to $0.33/M (34% down).
28 Oct 2026 Qwen3.7 (max): BenchLeader Index 60.8 → 60.3.
28 Oct 2026 Qwen3.7 (max): 1 new result (AA Progress Index v1).
27 Oct 2026 Qwen3.7 (max): cached input price moved from $0.33/M to $0.50/M (52% up).
26 Oct 2026 Qwen3.7 (max): cost per task moved from $1.15/M to $0.93/M (19% down).
25 Oct 2026 Qwen3.7 (max): 1 new result (AA-Briefcase v1.1); 1 score revision; cached input price moved from $0.50/M to $0.33/M (34% down).
24 Oct 2026 Qwen3.7 (max): cached input price moved from $0.33/M to $0.50/M (52% up).
23 Oct 2026 Gemini 3 Pro: 1 score revision.

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs