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DeepSeek V4.1 Flash 1017 vs GPT-5.5 Pro

Full profiles: DeepSeek V4.1 Flash 1017 (DeepSeek) and GPT-5.5 Pro (OpenAI): every benchmark, price and rank.

Updated · Data from 7 sources

As of 25 Oct 2026, DeepSeek V4.1 Flash 1017 (max) and GPT-5.5 Pro (xhigh) are neck and neck on quality (64.0 vs 65.3 on the BenchLeader Index, inside the ±9.1 margin of error), and DeepSeek V4.1 Flash 1017 (max) costs 129× less, which makes it the better buy for most workloads. GPT-5.5 Pro leads in every category we measure both in.

DeepSeek V4.1 Flash 1017 benchmarks max DeepSeek GPT-5.5 Pro benchmarks xhigh OpenAIOpen in the comparison tool

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
MathsGPT-5.5 Pro71 vs 62 category score; FrontierMath Tiers 1–3 87.7% vs 71.2%High
ReasoningGPT-5.5 Pro78 vs 71 category score; ARC-AGI-2 84.2% vs 78.1%Medium
Lowest costDeepSeek V4.1 Flash 1017$0.525 vs $67.50 per 1M blended; agentic coding session $0.023 vs $2.52–
Fastest first answerEither11.4 s (DeepSeek V4.1 Flash 1017 (max)) vs 11.4 s (GPT-5.5 Pro (xhigh)) 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 GPT-5.5 Pro (xhigh) are neck and neck on quality (64.0 vs 65.3, within the ±9.1 margin).
  • DeepSeek V4.1 Flash 1017 (max) is stronger in agents & tools, coding, composite, knowledge, long context, multimodal.
  • GPT-5.5 Pro (xhigh) is stronger in maths, reasoning.
  • DeepSeek V4.1 Flash 1017 (max) is 129× cheaper ($0.525 vs $67.50 per 1M blended).
  • DeepSeek V4.1 Flash 1017 (max) streams 7.2× faster (195 vs 27 tokens per second).

At a glance

SpecDeepSeek V4.1 Flash 1017GPT-5.5 Pro
DeveloperDeepSeekOpenAI
Released17 Oct 202623 Apr 2026
Context window (tokens)1,048,5761,050,000
Compared atDeepSeek V4.1 Flash 1017 (max)GPT-5.5 Pro (xhigh)
Open weightsYesNo
Price in / out / cached input per 1M$0.300 / $1.20 / $0.0060$30.00 / $180.00 / –

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)GPT-5.5 Pro (xhigh)Leader
Reasoning70.677.6GPT-5.5 Pro
Coding69.9–not comparable
Agents & tools63.5–not comparable
Maths61.871.3GPT-5.5 Pro
Knowledge57.1–not comparable
Multimodal63.7–not comparable
Long context66.4–not comparable
Composite80.0–not comparable

Where sources disagree

Across the 6 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 0, GPT-5.5 Pro leads 6.

Overall indexDeepSeek V4.1 Flash 1017 (max)GPT-5.5 Pro (xhigh)Leader
BenchLeader Index64.065.3neck and neck

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)GPT-5.5 Pro (xhigh)
Blended price per 1M tokens$0.525$67.50
Input / output per 1M$0.300 / $1.20$30.00 / $180.00
Cached input per 1M$0.0060–
Price per task: chat reply$0.0005$0.066
Price per task: summarize a 30-page report$0.0043$0.468
Price per task: code edit$0.0036$0.450
Price per task: agentic coding session$0.023$2.52
Price per task: structured extraction$0.0008$0.096
Cost to run a full benchmark suite$0.262–
Output speed195 tok/s27 tok/s
Time to first answer11.4 s11.4 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. GPT-5.5 Pro (xhigh) scores 65.3 and takes 11 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

59 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)GPT-5.5 Pro (xhigh)
BenchLeader IndexBenchLeader64.065.3
Agents & tools scoreBenchLeader63.5–
Coding scoreBenchLeader69.9–
Composite scoreBenchLeader80.0–
Knowledge scoreBenchLeader57.1–
Long context scoreBenchLeader66.4–
Maths scoreBenchLeader61.871.3
Multimodal scoreBenchLeader63.7–
Reasoning scoreBenchLeader70.677.6
Blended price $/MBenchLeader$0.525$67.50
Output speedBenchLeader195 tok/s27 tok/s
Time to first answerBenchLeader11.4 s11.4 s
Context windowBenchLeader1,048,576 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub93.2%–
SimpleBenchSimpleBench–76.9%†
LiveBench 2.0 ReasoningLiveBench89.1%†–
Humanity's Last Exam (AA)Artificial Analysis43.3%–
ARC-AGI-1ARC Prize93.5%95.0%
ARC-AGI-2ARC Prize78.1%84.2%
CritPtArtificial Analysis24.0%30.6%
Chess PuzzlesEpoch AI Benchmarking Hub46.0%62.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub49.0%–
LMCAEpoch AI Benchmarking Hub–53.9%
DTBenchEpoch AI Benchmarking Hub–96.0%
Coding
Arena WebDevArena (LMArena)1665–
LiveBench 2.0 CodingLiveBench96.0%†–
SciCode (AA)Artificial Analysis55.9%–
Code MigrationVals AI44.2%–
Code Migration v1.1Vals AI67.5%–
Vibe Code Bench v1.1Vals AI87.7%–
Terminal-Bench 4.0 (AA)Artificial Analysis33.8%–
FrontierCode 1.1 (AA)Artificial Analysis43.7%–
Agents & tools
LiveBench Long AgenticLiveBench50.9%†–
LiveBench BrowserLiveBench76.0%†–
GDPval-AA v2.1Artificial Analysis62.3%–
Finance Agent v2Vals AI57.0%–
Finance Agent v2.1Vals AI62.9%–
Harvey's Legal Agent Benchmark v1.1Vals AI14.2%–
Show all 59 benchmarks
MetricPublisherDeepSeek V4.1 Flash 1017 (max)GPT-5.5 Pro (xhigh)
Agents & tools
Harvey's Legal Agent Benchmark v1Vals AI9.2%–
Legal Research BenchVals AI45.2%–
Tax Agent BenchVals AI44.4%–
Terminal-Bench 4.0 (Vals)Vals AI31.8%–
AutomationBenchArtificial Analysis66.6%–
GDP.pdf (AA)Artificial Analysis17.2%–
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%–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub71.2%87.7%
FrontierMath Tier 4Epoch AI Benchmarking Hub46.3%78.0%
OTIS Mock AIMEEpoch AI Benchmarking Hub99.4%–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub42.5%–
LiveBench 2.0 Data AnalysisLiveBench79.5%†–
LiveBench ResearchLiveBench79.5%†–
AA-OmniscienceArtificial Analysis4.7–
Excel Modeling BenchmarkVals AI61.8%–
Excel Modeling Benchmark v1.1Vals AI69.2%–
AA-Omniscience: accuracyArtificial Analysis42.9%–
AA-Omniscience: non-hallucinationArtificial Analysis33.3%–
Multimodal
LiveBench DesignLiveBench83.4%†–
MMMU-ProArtificial Analysis80.6%–
Long context
AA-LCRArtificial Analysis82.7%–
MLCRArtificial Analysis26.7%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub–162.9†
LiveBench 2.0LiveBench79.2%†–
AA Intelligence Index v4.3.2Artificial Analysis45.1–
Vals IndexVals AI61.3–
Vals Finance IndexVals AI60.9%–
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)…).
  • 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…).
  • DeepSeek V4.1 Flash 1017 (max): 1 new result (FrontierCode 1.1 (AA)); 2 score revisions.
  • GPT-5.5 Pro (xhigh): 1 new result (Chess Puzzles).
  • GPT-5.5 Pro (xhigh): BenchLeader Index 66.5 → 65.6.
  • GPT-5.5 Pro (xhigh): BenchLeader Index 67.1 → 66.5.

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

DeepSeek V4.1 Flash 1017 vs GPT-5.5 Pro: questions

Is DeepSeek V4.1 Flash 1017 better than GPT-5.5 Pro?
DeepSeek V4.1 Flash 1017 (max) and GPT-5.5 Pro (xhigh) are neck and neck on quality (64.0 vs 65.3, within the ±9.1 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 GPT-5.5 Pro, and will that change?
DeepSeek V4.1 Flash 1017 is cheaper today: $0.525 against $67.50 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Which is better for long documents?
Both take about 1.1M tokens: DeepSeek V4.1 Flash 1017 1,048,576, GPT-5.5 Pro 1,050,000.
Which has lower latency?
DeepSeek V4.1 Flash 1017 (max) answers first: 11.4 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 GPT-5.5 Pro?
DeepSeek V4.1 Flash 1017 streams faster: 195 against 27 output tokens per second.
Do independent benchmarks agree on DeepSeek V4.1 Flash 1017 vs GPT-5.5 Pro?
Across the 6 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 0, GPT-5.5 Pro leads 6.
When was DeepSeek V4.1 Flash 1017 released?
DeepSeek V4.1 Flash 1017 was released on 17 Oct 2026.