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Gemini 3.7 Flash vs GPT-6 Sol

Full profiles: Gemini 3.7 Flash (Google) and GPT-6 Sol (OpenAI): every benchmark, price and rank.

Updated · Data from 10 sources

As of 9 Nov 2026, Gemini 3.7 Flash and GPT-6 Sol are neck and neck on quality (62.2 vs 62.9 on the BenchLeader Index, inside the ±4.9 margin), and Gemini 3.7 Flash is 2.7× cheaper at $1.50 vs $4.00 per 1M tokens blended. Choose Gemini 3.7 Flash for multimodal (67 vs 61), knowledge (67 vs 62), and human preference (68 vs 64) and fast first answers (2.4 s vs 72.1 s); choose GPT-6 Sol for agents & tools (60 vs 48), maths (69 vs 63), and coding (67 vs 63), where it also streams faster.

Key facts (as of 9 Nov 2026)

  • Gemini 3.7 Flash scores 62.2 on the BenchLeader Index and GPT-6 Sol scores 62.9 (BenchLeader, 9 Nov 2026).
  • Gemini 3.7 Flash costs $1.50 per 1M tokens blended (list price, 9 Nov 2026).
  • GPT-6 Sol costs $4.00 per 1M tokens blended (list price, 9 Nov 2026).
  • GPT-6 Sol streams faster than Gemini 3.7 Flash (Artificial Analysis, 7-day median, 9 Nov 2026).
  • Of the 59 benchmarks both models have, GPT-6 Sol leads 36 (BenchLeader, 9 Nov 2026).
  • On Arena WebDev, Gemini 3.7 Flash is rated 1588 and GPT-6 Sol 1674 (LMArena, as published by 9 Nov 2026).
Gemini 3.7 Flash benchmarks high Google GPT-6 Sol benchmarks max OpenAIAdd 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 casePickWhyConfidence
CodingGPT-6 Sol67 vs 63 category score; Arena WebDev 1674 vs 1588Medium
Agents & tool useGPT-6 Sol60 vs 48 category score; Terminal-Bench 50.3% vs 12.4%High
MathsGPT-6 Sol69 vs 63 category score; FrontierMath Tiers 1–3 89.8% vs 71.6%Medium
ReasoningGemini 3.7 Flash68 vs 66 category score; GPQA Diamond 94.8% vs 94.3%Medium
KnowledgeGemini 3.7 Flash67 vs 62 category score; SimpleQA Verified 69.2% vs 60.7%Medium
Long documentsGPT-6 Sol67 vs 66 category score; AA-LCR v1.1 83.7% vs 81.7%Medium
Images and other mediaGemini 3.7 Flash67 vs 61 category score; Arena Vision 1313 vs 1232Medium
Chat quality (human preference)Gemini 3.7 Flash68 vs 64 on Arena votesMedium
Lowest costGemini 3.7 Flash$1.50 vs $4.00 per 1M blended; agentic coding session $0.060 vs $0.160–
Fastest first answerGemini 3.7 Flash2.4 s (Gemini 3.7 Flash (high)) vs 72.1 s (GPT-6 Sol (max)) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Gemini 3.7 Flash (high) and GPT-6 Sol (max) are neck and neck on quality (62.2 vs 62.9, within the ±4.9 margin).
  • Gemini 3.7 Flash (high) is stronger in human preference, knowledge, multimodal, reasoning.
  • GPT-6 Sol (max) is stronger in agents & tools, coding, long context, maths.
  • Gemini 3.7 Flash (high) is 2.7× cheaper ($1.50 vs $4.00 per 1M blended).
  • GPT-6 Sol (max) streams 1.3× faster (121 vs 92 tokens per second).

At a glance

SpecGemini 3.7 FlashGPT-6 Sol
DeveloperGoogleOpenAI
Released13 Aug 202622 Sep 2026
Context window (tokens)1,048,5761,050,000
Compared atGemini 3.7 Flash (high)GPT-6 Sol (max)
Open weightsNoNo
Price in / out / cached input per 1M$0.750 / $3.75 / $0.075$2.00 / $10.00 / $0.200

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.

CategoryGemini 3.7 Flash (high)GPT-6 Sol (max)Leader
Reasoning67.966.2Gemini 3.7 Flash
Coding62.766.5GPT-6 Sol
Agents & tools48.059.6GPT-6 Sol
Maths62.968.5GPT-6 Sol
Knowledge66.561.5Gemini 3.7 Flash
Human preference68.264.2Gemini 3.7 Flash
Multimodal67.260.7Gemini 3.7 Flash
Long context65.666.6GPT-6 Sol

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.

2550 avg75ReasoningCodingAgents & toolsMathsKnowledgeLong contextMultimodalHumanpreferenceGemini 3.7 Flash, Reasoning: 67.9Gemini 3.7 Flash, Coding: 62.7Gemini 3.7 Flash, Agents & tools: 48.0Gemini 3.7 Flash, Maths: 62.9Gemini 3.7 Flash, Knowledge: 66.5Gemini 3.7 Flash, Long context: 65.6Gemini 3.7 Flash, Multimodal: 67.2Gemini 3.7 Flash, Human preference: 68.2GPT-6 Sol, Reasoning: 66.2GPT-6 Sol, Coding: 66.5GPT-6 Sol, Agents & tools: 59.6GPT-6 Sol, Maths: 68.5GPT-6 Sol, Knowledge: 61.5GPT-6 Sol, Long context: 66.6GPT-6 Sol, Multimodal: 60.7GPT-6 Sol, Human preference: 64.2

Not drawn, measured for fewer than two of these models: Instruction following.

ModelIndex

Where sources disagree

Across the 59 benchmarks both have, Gemini 3.7 Flash leads 22, GPT-6 Sol leads 36 and 1 is a tie. Every overall index that rates both puts Gemini 3.7 Flash ahead.

Overall indexGemini 3.7 Flash (high)GPT-6 Sol (max)Leader
BenchLeader Index62.262.9neck and neck
Arena Text14891457Gemini 3.7 Flash

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.

MeasureGemini 3.7 Flash (high)GPT-6 Sol (max)
Blended price per 1M tokens$1.50$4.00
Input / output per 1M$0.750 / $3.75$2.00 / $10.00
Cached input per 1M$0.075$0.200
Price per task: chat reply$0.0014$0.0038
Price per task: summarize a 30-page report$0.011$0.030
Price per task: code edit$0.010$0.027
Price per task: agentic coding session$0.060$0.160
Price per task: structured extraction$0.0023$0.0060
Agentic coding session, input mostly cached$0.030$0.079
Cost per benchmark task (AA Index)–$2.47
Output tokens per task (AA Index)–54k
Of which reasoning–35k
Time per task (AA Index)–7 min
Output speed92 tok/s121 tok/s
Time to first answer2.4 s72.1 s
Time to a complete answer–130.2 s

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.7 Flash (high) scores 62.2 and takes 2 s to its first answer token; Gemini 3.7 Flash (medium) scores 60.2 in 2 s, Gemini 3.7 Flash (low) scores 57.4 in 2 s. GPT-6 Sol (max) scores 62.9 and takes 72 s to its first answer token; GPT-6 Sol (xhigh) scores 58.6 in 24 s, GPT-6 Sol (high) scores 58.2 in 9 s. 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

117 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.

MetricPublisherGemini 3.7 Flash (high)GPT-6 Sol (max)
BenchLeader IndexBenchLeader62.262.9
Agents & tools scoreBenchLeader48.059.6
Coding scoreBenchLeader62.766.5
Human preference scoreBenchLeader68.264.2
Knowledge scoreBenchLeader66.561.5
Long context scoreBenchLeader65.666.6
Maths scoreBenchLeader62.968.5
Multimodal scoreBenchLeader67.260.7
Reasoning scoreBenchLeader67.966.2
Blended price $/MBenchLeader$1.50$4.00
Output speedBenchLeader92 tok/s121 tok/s
Time to first answerBenchLeader2.4 s72.1 s
Context windowBenchLeader1,048,576 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub94.8%94.3%
Arena Hard PromptsArena (LMArena)15101483
LiveBench 1.0 ReasoningLiveBench87.8%88.7%
GPQA Diamond (AA)Artificial Analysis94.5%–
Humanity's Last Exam (AA)Artificial Analysis47.9%47.9%
HLE-Diamond (AA)Artificial Analysis–45.2%
GPQA Diamond (Vals)Vals AI93.9%–
ARC-AGI-1ARC Prize95.5%95.5%
ARC-AGI-2ARC Prize84.6%89.6%
ARC-AGI-3ARC Prize–23.0%
CritPtArtificial Analysis14.3%30.9%
CritPt v2 hard subset (AA)Artificial Analysis–66.5%
MysteryMechanismVals AI–30.2%
Chess PuzzlesEpoch AI Benchmarking Hub66.0%56.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub37.0%56.0%
LMCAEpoch AI Benchmarking Hub50.4%59.1%
DTBenchEpoch AI Benchmarking Hub96.8%97.3%
ForecastBenchForecastBench66.2%–
Coding
SciCodeSciCode57.2%57.6%
FrontierCodeCognition43.6%†49.3%
Arena CodingArena (LMArena)15201520
Arena WebDevArena (LMArena)15881674
LiveBench 1.0 CodingLiveBench78.9%81.8%
LiveCodeBenchVals AI88.7%–
IOIVals AI67.8%82.6%
Show all 117 benchmarks
MetricPublisherGemini 3.7 Flash (high)GPT-6 Sol (max)
Coding
SWE-bench (Vals)Vals AI80.8%–
Code MigrationVals AI34.8%57.2%
ProgramBenchVals AI0.0%2.0%
Vibe Code Bench v1.1Vals AI70.4%87.8%
MirrorCodeEpoch AI Benchmarking Hub41.1%–
DeepSWE v1.1Epoch AI Benchmarking Hub65.3%–
ALE-BenchEpoch AI Benchmarking Hub904.32462
FrontierSWEEpoch AI Benchmarking Hub20.3%–
Terminal-Bench 4.0 (AA)Artificial Analysis13.6%43.9%
Terminal-Bench 2.1 (AA)Artificial Analysis85.8%–
GameBench 2 OverallDuelLab GameBench 2–72.9†
GameBench 2 by reasoning settingDuelLab GameBench 2–79.3†
Design Arena WebsiteDesign Arena1300†1285†
FrontierCode 2.0 (AA)Artificial Analysis–35.6%
Agents & tools
Terminal-BenchTerminal-Bench12.4%50.3%
Remote Labor IndexScale AI / CAIS5.0%†–
APEX-AgentsMercor67.8%†54.3%
Arena AgentArena (LMArena)-1.97
LiveBench Agentic CodingLiveBench58.3%52.9%
Terminal-Bench 2.1 (Vals)Vals AI77.5%83.2%
τ³-Banking (AA)Artificial Analysis32.8%–
ITBench SRE (AA)Artificial Analysis–49.4%
Analyst Agent (AA)Artificial Analysis60.0%–
CyberBenchVals AI43.8%78.0%
Finance Agent v2Vals AI59.0%49.0%
Harvey's Legal Agent Benchmark v1Vals AI8.8%1.7%
Legal Research BenchVals AI34.6%28.9%
SkillsBenchVals AI65.9%–
SREBenchVals AI4.6%30.5%
Tax Agent BenchVals AI22.8%15.0%
Terminal-Bench 4.0 (Vals)Vals AI12.1%44.4%
Terminal-Bench ScienceVals AI7.1%30.0%
Arena SearchArena (LMArena)–1229
Vending-Bench 2Andon Labs–14427.9†
AutomationBenchArtificial Analysis62.0%61.6%
GDP.pdf (AA)Artificial Analysis23.6%25.2%
Harvey LAB-AA v1.1Harvey–3.6%
EnterpriseOps-GymArtificial Analysis50.4%†–
AA-Briefcase v1.1Artificial Analysis–1476
Design Arena AgenticDesign Arena1218†1212†
Terminal-Bench-Science 0.1 (AA)Artificial Analysis–30.0%
CWE-Bench (AA)Artificial Analysis–64.2%
DeepSec-Bench (AA)Artificial Analysis–46.3%
CyberGym end-to-end (AA)Artificial Analysis–0.0%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub71.6%89.8%
FrontierMath Tier 4Epoch AI Benchmarking Hub36.6%90.0%
OTIS Mock AIMEEpoch AI Benchmarking Hub97.2%100.0%
ProofBenchVals AI58.0%†83.0%†
LiveBench MathematicsLiveBench93.5%96.4%
Arena MathsArena (LMArena)15021440
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub69.2%60.7%
LiveBench 1.0 Data AnalysisLiveBench68.0%81.2%
AA-Omniscience v1.1Artificial Analysis–21.4
MMLU-ProVals AI90.1%–
LegalBenchVals AI87.3%–
TaxEvalVals AI74.7%–
PRBench LegalScale AI SEAL–38.6%†
BioMysteryBenchVals AI–74.8%
Excel Modeling BenchmarkVals AI71.3%71.5%
MedCodeVals AI53.4%47.1%
MedScribeVals AI83.9%82.0%
Public Benefits Bench v1.1Vals AI–56.6%
EBR-benchEpoch AI Benchmarking Hub–53.3%
GDP.pdfEpoch AI Benchmarking Hub23.8%26.4%
AA-Omniscience v1.1: accuracyArtificial Analysis–51.1%
AA-Omniscience v1.1: non-hallucinationArtificial Analysis–39.1%
HealthBench Professional (AA)OpenAI–62.3%
Instruction following
LiveBench LanguageLiveBench85.5%85.3%
LiveBench Instruction FollowingLiveBench79.9%68.6%
Arena Instruction FollowingArena (LMArena)14861448
Human preference
Arena TextArena (LMArena)14891457
Arena Creative WritingArena (LMArena)14871430
Arena Multi-turnArena (LMArena)14901466
Arena Longer QueriesArena (LMArena)15011466
Multimodal
Arena VisionArena (LMArena)13131232
MMMU-ProArtificial Analysis85.5%83.0%
MMMU-Pro (Vals)Vals AI89.0%–
MortgageTaxVals AI66.7%–
Blueprint-Bench 2Epoch AI Benchmarking Hub–36.9%†
AA-3DArtificial Analysis–1131
Long context
AA-LCR v1.1Artificial Analysis81.7%83.7%
Arena DocumentArena (LMArena)1468–
MLCRArtificial Analysis12.2%33.9%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub158.4†164.1†
LiveBench 1.0LiveBench78.8%79.3%
AA Intelligence Index v5.0Artificial Analysis–44.2
AA Intelligence Index v4.3.2Artificial Analysis39.147.6
AA Progress Index v1Artificial Analysis317.4334
Vals RSI IndexVals AI18.3%28.1%
Vals Science IndexVals AI–45.0%
AA Cyber IndexArtificial Analysis–36.8
Safety & honesty
FORTRESSScale AI SEAL–13.5%†

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

  • GPT-6 Sol (max): BenchLeader Index 63.5 → 62.9.
  • Gemini 3.7 Flash (high): 1 score revision.
  • GPT-6 Sol (max): 2 score revisions.
  • Gemini 3.7 Flash (high): 1 new result (Arena Document).
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): 6 new results (AA Intelligence Index v5.0, AA-Omniscience v1.1, CritPt v2 hard subset (AA)…).
  • GPT-6 Sol (max): 1 score revision.
  • Gemini 3.7 Flash (high): 1 new result (MirrorCode).
  • GPT-6 Sol (max): 1 score revision.

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

Gemini 3.7 Flash vs GPT-6 Sol: questions

Is Gemini 3.7 Flash better than GPT-6 Sol?
Gemini 3.7 Flash (high) and GPT-6 Sol (max) are neck and neck on quality (62.2 vs 62.9, within the ±4.9 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.
Gemini 3.7 Flash vs GPT-6 Sol: which is cheaper, and will that change?
Gemini 3.7 Flash is cheaper today: $1.50 against $4.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is Gemini 3.7 Flash or GPT-6 Sol better for coding?
GPT-6 Sol scores higher in coding (67 vs 63 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1588 for Gemini 3.7 Flash against 1674 for GPT-6 Sol.
Which is faster, Gemini 3.7 Flash or GPT-6 Sol?
GPT-6 Sol streams faster (121 vs 92 output tokens per second, Artificial Analysis 7-day median).
Is Gemini 3.7 Flash or GPT-6 Sol better for agents and tool use?
GPT-6 Sol scores higher in agentic tasks (60 vs 48 on the category index, where 50 is average). On Terminal-Bench, the top shared agents & tools benchmark, it is 12.4% for Gemini 3.7 Flash against 50.3% for GPT-6 Sol.
More questions (4)
Which is better for long documents?
GPT-6 Sol scores higher on long-context benchmarks (67 vs 66). Both take about 1.1M tokens: Gemini 3.7 Flash 1,048,576, GPT-6 Sol 1,050,000.
Which has lower latency?
Gemini 3.7 Flash answers first: 2.4 s against 72.1 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
Do independent benchmarks agree on Gemini 3.7 Flash vs GPT-6 Sol?
Across the 59 benchmarks both have, Gemini 3.7 Flash leads 22, GPT-6 Sol leads 36 and 1 is a tie. Every overall index that rates both puts Gemini 3.7 Flash ahead.
When was GPT-6 Sol released?
GPT-6 Sol was released on 22 Sep 2026.