BenchLeader

DeepSeek V4.1 Flash 1017 vs Gemini 3.7 Flash

Full profiles: DeepSeek V4.1 Flash 1017 (DeepSeek) and Gemini 3.7 Flash (Google): every benchmark, price and rank.

Updated · Data from 9 sources

As of 25 Oct 2026, DeepSeek V4.1 Flash 1017 (max) and Gemini 3.7 Flash (high) are neck and neck on quality (64.0 vs 63.5 on the BenchLeader Index, inside the ±5.2 margin of error), and DeepSeek V4.1 Flash 1017 (max) costs 2.9× less, which makes it the better buy for most workloads. Pick DeepSeek V4.1 Flash 1017 for agents & tools (64 vs 48); pick Gemini 3.7 Flash for knowledge (68 vs 57).

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
CodingDeepSeek V4.1 Flash 101770 vs 63 category score; Arena WebDev 1665 vs 1590Medium
Agents & tool useDeepSeek V4.1 Flash 101764 vs 48 category score; Harvey's Legal Agent Benchmark v1 9.2% vs 8.8%High
MathsGemini 3.7 Flash63 vs 62 category score; FrontierMath Tiers 1–3 71.6% vs 71.2%Medium
ReasoningDeepSeek V4.1 Flash 101771 vs 67 category score; CritPt 24.0% vs 14.3%Medium
KnowledgeGemini 3.7 Flash68 vs 57 category score; SimpleQA Verified 69.2% vs 42.5%High
Long documentsEither66 vs 66 category score; AA-LCR 82.7% vs 81.7%Either
Images and other mediaGemini 3.7 Flash68 vs 64 category score; MMMU-Pro 85.5% vs 80.6%Medium
Chat quality (human preference)–Only Gemini 3.7 Flash has an Arena rating (68 category score)Not comparable
Lowest costDeepSeek V4.1 Flash 1017$0.525 vs $1.50 per 1M blended; agentic coding session $0.023 vs $0.060–
Fastest first answerGemini 3.7 Flash2.5 s (Gemini 3.7 Flash (high)) vs 11.4 s (DeepSeek V4.1 Flash 1017 (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

  • DeepSeek V4.1 Flash 1017 (max) and Gemini 3.7 Flash (high) are neck and neck on quality (64.0 vs 63.5, within the ±5.2 margin).
  • DeepSeek V4.1 Flash 1017 (max) is stronger in agents & tools, coding, composite, long context, reasoning.
  • Gemini 3.7 Flash (high) is stronger in knowledge, maths, multimodal, human preference.
  • DeepSeek V4.1 Flash 1017 (max) is 2.9× cheaper ($0.525 vs $1.50 per 1M blended).
  • DeepSeek V4.1 Flash 1017 (max) streams 2.2× faster (195 vs 88 tokens per second).

At a glance

SpecDeepSeek V4.1 Flash 1017Gemini 3.7 Flash
DeveloperDeepSeekGoogle
Released17 Oct 202613 Aug 2026
Context window (tokens)1,048,5761,048,576
Compared atDeepSeek V4.1 Flash 1017 (max)Gemini 3.7 Flash (high)
Open weightsYesNo
Price in / out / cached input per 1M$0.300 / $1.20 / $0.0060$0.750 / $3.75 / $0.075

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.

CategoryDeepSeek V4.1 Flash 1017 (max)Gemini 3.7 Flash (high)Leader
Reasoning70.667.3DeepSeek V4.1 Flash 1017
Coding69.962.9DeepSeek V4.1 Flash 1017
Agents & tools63.547.6DeepSeek V4.1 Flash 1017
Maths61.863.3Gemini 3.7 Flash
Knowledge57.168.0Gemini 3.7 Flash
Human preference–68.4not comparable
Multimodal63.767.6Gemini 3.7 Flash
Long context66.465.9level
Composite80.073.2DeepSeek V4.1 Flash 1017

Where sources disagree

Across the 30 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 15, Gemini 3.7 Flash leads 15. Every overall index that rates both puts DeepSeek V4.1 Flash 1017 ahead.

Overall indexDeepSeek V4.1 Flash 1017 (max)Gemini 3.7 Flash (high)Leader
BenchLeader Index64.063.5neck and neck
AA Intelligence Index v4.3.245.139.1DeepSeek V4.1 Flash 1017

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; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.

MeasureDeepSeek V4.1 Flash 1017 (max)Gemini 3.7 Flash (high)
Blended price per 1M tokens$0.525$1.50
Input / output per 1M$0.300 / $1.20$0.750 / $3.75
Cached input per 1M$0.0060$0.075
Price per task: chat reply$0.0005$0.0014
Price per task: summarize a 30-page report$0.0043$0.011
Price per task: code edit$0.0036$0.010
Price per task: agentic coding session$0.023$0.060
Price per task: structured extraction$0.0008$0.0023
Cost to run a full benchmark suite$0.262–
Output speed195 tok/s88 tok/s
Time to first answer11.4 s2.5 s
Time to a complete answer13.9 s–

Each model is compared at its best-ranked reasoning-effort setting. DeepSeek V4.1 Flash 1017 (max) scores 64.0 and takes 11 s to its first answer token. Gemini 3.7 Flash (high) scores 63.5 and takes 2 s to its first answer token; Gemini 3.7 Flash (medium) scores 63.1 in 2 s, Gemini 3.7 Flash (low) scores 60.3 in 2 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

112 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.

MetricPublisherDeepSeek V4.1 Flash 1017 (max)Gemini 3.7 Flash (high)
BenchLeader IndexBenchLeader64.063.5
Agents & tools scoreBenchLeader63.547.6
Coding scoreBenchLeader69.962.9
Composite scoreBenchLeader80.073.2
Knowledge scoreBenchLeader57.168.0
Long context scoreBenchLeader66.465.9
Maths scoreBenchLeader61.863.3
Multimodal scoreBenchLeader63.767.6
Reasoning scoreBenchLeader70.667.3
Human preference scoreBenchLeader–68.4
Blended price $/MBenchLeader$0.525$1.50
Output speedBenchLeader195 tok/s88 tok/s
Time to first answerBenchLeader11.4 s2.5 s
Context windowBenchLeader1,048,576 tokens1,048,576 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub93.2%94.8%
Arena Hard PromptsArena (LMArena)–1509
LiveBench 2.0 ReasoningLiveBench89.1%†87.8%†
LiveBench 1.0 ReasoningLiveBench–87.8%
GPQA Diamond (AA)Artificial Analysis–94.5%
Humanity's Last Exam (AA)Artificial Analysis43.3%47.9%
GPQA Diamond (Vals)Vals AI–93.9%
ARC-AGI-1ARC Prize93.5%95.5%
ARC-AGI-2ARC Prize78.1%84.6%
CritPtArtificial Analysis24.0%14.3%
Chess PuzzlesEpoch AI Benchmarking Hub46.0%66.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub49.0%37.0%
LMCAEpoch AI Benchmarking Hub–50.4%
DTBenchEpoch AI Benchmarking Hub–96.8%
ForecastBenchForecastBench–66.2%
Coding
SciCodeSciCode–57.2%
FrontierCodeCognition–43.6%†
Arena CodingArena (LMArena)–1520
Arena WebDevArena (LMArena)16651590
LiveBench 2.0 CodingLiveBench96.0%†80.5%†
LiveBench 1.0 CodingLiveBench–78.9%
SciCode (AA)Artificial Analysis55.9%57.2%
LiveCodeBenchVals AI–88.7%
IOIVals AI–67.8%
SWE-bench (Vals)Vals AI–80.8%
Show all 112 benchmarks
MetricPublisherDeepSeek V4.1 Flash 1017 (max)Gemini 3.7 Flash (high)
Coding
Code MigrationVals AI44.2%34.8%
Code Migration v1.1Vals AI67.5%–
ProgramBenchVals AI–0.0%
Vibe Code Bench v1.1Vals AI87.7%70.4%
DeepSWE v1.1Epoch AI Benchmarking Hub–65.3%
ALE-BenchEpoch AI Benchmarking Hub–904.3
FrontierSWEEpoch AI Benchmarking Hub–20.3%
Terminal-Bench 4.0 (AA)Artificial Analysis33.8%13.6%
Terminal-Bench 2.1 (AA)Artificial Analysis–85.8%
FrontierCode 1.1 (AA)Artificial Analysis43.7%–
Agents & tools
Terminal-BenchTerminal-Bench–11.2%
Remote Labor IndexScale AI / CAIS–5.0%†
APEX-AgentsMercor–67.8%†
Arena AgentArena (LMArena)–-1.3
LiveBench Long AgenticLiveBench50.9%†28.3%†
LiveBench BrowserLiveBench76.0%†56.0%†
LiveBench Agentic CodingLiveBench–58.3%
Terminal-Bench 2.1 (Vals)Vals AI–77.5%
GDPval-AA v2.1Artificial Analysis62.3%–
τ³-Banking (AA)Artificial Analysis–32.8%
Analyst Agent (AA)Artificial Analysis–60.0%
CyberBenchVals AI–43.8%
Finance Agent v2Vals AI57.0%59.0%
Finance Agent v2.1Vals AI62.9%–
Harvey's Legal Agent Benchmark v1.1Vals AI14.2%–
Harvey's Legal Agent Benchmark v1Vals AI9.2%8.8%
Legal Research BenchVals AI45.2%34.6%
SkillsBenchVals AI–65.9%
SREBenchVals AI–4.6%
Tax Agent BenchVals AI44.4%22.8%
Terminal-Bench 4.0 (Vals)Vals AI31.8%12.1%
Terminal-Bench ScienceVals AI–7.1%
AutomationBenchArtificial Analysis66.6%62.0%
GDP.pdf (AA)Artificial Analysis17.2%23.6%
EnterpriseOps-GymArtificial Analysis–50.4%†
AA-Briefcase v1.1Artificial Analysis1570–
Terminal-Bench-Science 0.1 (AA)Artificial Analysis12.9%–
CWE-Bench (AA)Artificial Analysis69.2%–
DeepSec-Bench (AA)Artificial Analysis24.9%–
CyberGym end-to-end (AA)Artificial Analysis76.3%–
FACTS SearchGoogle–80.9%†
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub71.2%71.6%
FrontierMath Tier 4Epoch AI Benchmarking Hub46.3%36.6%
OTIS Mock AIMEEpoch AI Benchmarking Hub99.4%97.2%
ProofBenchVals AI–58.0%†
LiveBench MathematicsLiveBench–93.5%
Arena MathsArena (LMArena)–1505
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub42.5%69.2%
LiveBench 2.0 Data AnalysisLiveBench79.5%†68.0%†
LiveBench ResearchLiveBench79.5%†76.5%†
LiveBench 1.0 Data AnalysisLiveBench–68.0%
AA-OmniscienceArtificial Analysis4.726.5
MMLU-ProVals AI–90.1%
LegalBenchVals AI–87.3%
TaxEvalVals AI–74.7%
Excel Modeling BenchmarkVals AI61.8%71.3%
Excel Modeling Benchmark v1.1Vals AI69.2%–
MedCodeVals AI–53.4%
MedScribeVals AI–83.9%
GDP.pdfEpoch AI Benchmarking Hub–23.8%
AA-Omniscience: accuracyArtificial Analysis42.9%55.3%
AA-Omniscience: non-hallucinationArtificial Analysis33.3%35.5%
Instruction following
LiveBench LanguageLiveBench–85.5%
LiveBench Instruction FollowingLiveBench–79.9%
Arena Instruction FollowingArena (LMArena)–1487
Human preference
Arena TextArena (LMArena)–1490
Arena Creative WritingArena (LMArena)–1492
Arena Multi-turnArena (LMArena)–1489
Arena Longer QueriesArena (LMArena)–1501
Multimodal
Arena VisionArena (LMArena)–1314
LiveBench DesignLiveBench83.4%†73.2%†
MMMU-ProArtificial Analysis80.6%85.5%
MMMU-Pro (Vals)Vals AI–89.0%
MortgageTaxVals AI–66.7%
SAGEVals AI–49.2%
Long context
AA-LCRArtificial Analysis82.7%81.7%
MLCRArtificial Analysis26.7%12.2%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub–158.0†
LiveBench 2.0LiveBench79.2%†67.2%†
LiveBench 1.0LiveBench–78.8%
AA Intelligence Index v4.3.2Artificial Analysis45.139.1
Vals IndexVals AI61.3–
Vals Finance IndexVals AI60.9%–
Vals RSI IndexVals AI–18.3%
Vals Router IndexVals AI61.3%†–
AA Cyber IndexArtificial Analysis56.8–
Metadata
AA Openness IndexArtificial Analysis44.4–

Data as of 2026-10-25. Best configuration of each model; every score links to its source on the model pages.

What changed

  • DeepSeek V4.1 Flash 1017 (max): 10 new results (MLCR, AA Cyber Index, CWE-Bench (AA)…).
  • Gemini 3.7 Flash (high): 2 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index).
  • Gemini 3.7 Flash (high): input price moved from $0.38/M to $0.75/M (97% up); output price moved from $1.88/M to $3.75/M (99% up).
  • DeepSeek V4.1 Flash 1017 (max): BenchLeader Index 63.1 → 63.9.
  • DeepSeek V4.1 Flash 1017 (max): 11 new results (GPQA Diamond, FrontierMath Tiers 1–3, FrontierMath Tier 4…).
  • Gemini 3.7 Flash (high): 1 score revision; input price moved from $0.75/M to $0.38/M (49% down); output price moved from $3.75/M to $1.88/M (50% down).
  • DeepSeek V4.1 Flash 1017 (max): 1 new result (FrontierCode 1.1 (AA)); 2 score revisions.
  • Gemini 3.7 Flash (high): 1 new result (ForecastBench).
  • Gemini 3.7 Flash (high): BenchLeader Index 62.9 → 63.5.
  • Gemini 3.7 Flash (high): BenchLeader Index 60.8 → 62.9.

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

DeepSeek V4.1 Flash 1017 vs Gemini 3.7 Flash: questions

Is DeepSeek V4.1 Flash 1017 better than Gemini 3.7 Flash?
DeepSeek V4.1 Flash 1017 (max) and Gemini 3.7 Flash (high) are neck and neck on quality (64.0 vs 63.5, within the ±5.2 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-25, so check the category scores for your use.
Which is cheaper, DeepSeek V4.1 Flash 1017 or Gemini 3.7 Flash, and will that change?
DeepSeek V4.1 Flash 1017 is cheaper today: $0.525 against $1.50 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is DeepSeek V4.1 Flash 1017 better than Gemini 3.7 Flash for coding?
DeepSeek V4.1 Flash 1017 scores higher in coding (70 vs 63 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1665 for DeepSeek V4.1 Flash 1017 against 1590 for Gemini 3.7 Flash.
Is DeepSeek V4.1 Flash 1017 better than Gemini 3.7 Flash for agents and tool use?
DeepSeek V4.1 Flash 1017 scores higher in agentic tasks (64 vs 48 on the category index, where 50 is average).
Which is better for long documents?
They are level on long-context benchmarks (66 vs 66). Both accept 1,048,576 tokens of context.
Which has lower latency?
Gemini 3.7 Flash (high) answers first: 2.5 s against 11.4 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.
Which is faster, DeepSeek V4.1 Flash 1017 or Gemini 3.7 Flash?
DeepSeek V4.1 Flash 1017 streams faster: 195 against 88 output tokens per second.
Do independent benchmarks agree on DeepSeek V4.1 Flash 1017 vs Gemini 3.7 Flash?
Across the 30 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 15, Gemini 3.7 Flash leads 15. Every overall index that rates both puts DeepSeek V4.1 Flash 1017 ahead.
When was DeepSeek V4.1 Flash 1017 released?
DeepSeek V4.1 Flash 1017 was released on 17 Oct 2026.