Claude Sonnet 5.5 vs DeepSeek V4.1 Flash 1017
Full profiles: Claude Sonnet 5.5 (Anthropic) and DeepSeek V4.1 Flash 1017 (DeepSeek): every benchmark, price and rank.
Updated · Data from 9 sources
As of 25 Oct 2026, Claude Sonnet 5.5 (max) and DeepSeek V4.1 Flash 1017 (max) are neck and neck on quality (69.4 vs 64.0 on the BenchLeader Index, inside the ±6.3 margin of error), and DeepSeek V4.1 Flash 1017 (max) costs 7.6× less, which makes it the better buy for most workloads. Claude Sonnet 5.5 leads in every category we measure both in.
Claude Sonnet 5.5 benchmarks max Anthropic
DeepSeek V4.1 Flash 1017 benchmarks max DeepSeekOpen in the comparison toolWhich 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 | Either | 69 vs 70 category score; SciCode (AA) 61.0% vs 55.9% | Either |
| Agents & tool use | Claude Sonnet 5.5 | 70 vs 64 category score; GDPval-AA v2.1 66.9% vs 62.3% | Medium |
| Maths | Claude Sonnet 5.5 | 72 vs 62 category score; FrontierMath Tiers 1–3 88.8% vs 71.2% | High |
| Reasoning | Claude Sonnet 5.5 | 77 vs 71 category score; GPQA Diamond 95.6% vs 93.2% | Medium |
| Knowledge | Claude Sonnet 5.5 | 65 vs 57 category score; SimpleQA Verified 46.5% vs 42.5% | High |
| Long documents | Either | 66 vs 66 category score; AA-LCR 82.7% vs 82.7% | Either |
| Lowest cost | DeepSeek V4.1 Flash 1017 | $0.525 vs $4.00 per 1M blended; agentic coding session $0.023 vs $0.160 | – |
| Fastest first answer | DeepSeek V4.1 Flash 1017 | 11.4 s (DeepSeek V4.1 Flash 1017 (max)) vs 343.1 s (Claude Sonnet 5.5 (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Claude Sonnet 5.5 (max) and DeepSeek V4.1 Flash 1017 (max) are neck and neck on quality (69.4 vs 64.0, within the ±6.3 margin).
- Claude Sonnet 5.5 (max) is stronger in agents & tools, composite, knowledge, maths, reasoning.
- DeepSeek V4.1 Flash 1017 (max) is stronger in coding, multimodal.
- DeepSeek V4.1 Flash 1017 (max) is 7.6× cheaper ($0.525 vs $4.00 per 1M blended).
- DeepSeek V4.1 Flash 1017 (max) streams 1.5× faster (195 vs 133 tokens per second).
At a glance
| Spec | Claude Sonnet 5.5 | DeepSeek V4.1 Flash 1017 |
|---|---|---|
| Developer | Anthropic | DeepSeek |
| Released | 28 Sept 2026 | 17 Oct 2026 |
| Context window (tokens) | 1,000,000 | 1,048,576 |
| Compared at | Claude Sonnet 5.5 (max) | DeepSeek V4.1 Flash 1017 (max) |
| Open weights | No | Yes |
| Price in / out / cached input per 1M | $2.00 / $10.00 / $0.100 | $0.300 / $1.20 / $0.0060 |
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 | Claude Sonnet 5.5 (max) | DeepSeek V4.1 Flash 1017 (max) | Leader |
|---|---|---|---|
| Reasoning | 77.4 | 70.6 | Claude Sonnet 5.5 |
| Coding | 69.3 | 69.9 | level |
| Agents & tools | 70.1 | 63.5 | Claude Sonnet 5.5 |
| Maths | 72.4 | 61.8 | Claude Sonnet 5.5 |
| Knowledge | 65.0 | 57.1 | Claude Sonnet 5.5 |
| Multimodal | – | 63.7 | not comparable |
| Long context | 66.4 | 66.4 | level |
| Composite | 92.2 | 80.0 | Claude Sonnet 5.5 |
Where sources disagree
Across the 23 benchmarks both have, Claude Sonnet 5.5 leads 22, DeepSeek V4.1 Flash 1017 leads 0 and 1 is a tie. Every overall index that rates both puts Claude Sonnet 5.5 ahead.
| Overall index | Claude Sonnet 5.5 (max) | DeepSeek V4.1 Flash 1017 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 69.4 | 64.0 | neck and neck |
| AA Intelligence Index v4.3.2 | 56 | 45.1 | Claude Sonnet 5.5 |
| Vals Index | 70.8† | 61.3 | Claude Sonnet 5.5 |
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.
| Measure | Claude Sonnet 5.5 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|
| Blended price per 1M tokens | $4.00 | $0.525 |
| Input / output per 1M | $2.00 / $10.00 | $0.300 / $1.20 |
| Cached input per 1M | $0.100 | $0.0060 |
| Price per task: chat reply | $0.0038 | $0.0005 |
| Price per task: summarize a 30-page report | $0.030 | $0.0043 |
| Price per task: code edit | $0.027 | $0.0036 |
| Price per task: agentic coding session | $0.160 | $0.023 |
| Price per task: structured extraction | $0.0060 | $0.0008 |
| Cost to run a full benchmark suite | $5.46 | $0.262 |
| Output speed | 133 tok/s | 195 tok/s |
| Time to first answer | 343.1 s | 11.4 s |
| Time to a complete answer | 346.9 s | 13.9 s |
Per token is not per task: on Artificial Analysis' full suite Claude Sonnet 5.5 (max) cost $5.46 and DeepSeek V4.1 Flash 1017 (max) $0.262, because Claude Sonnet 5.5 (max) used about 2.7× as many tokens for the same work, which a per-token price hides.
Each model is compared at its best-ranked reasoning-effort setting. Claude Sonnet 5.5 (max) scores 69.4 and takes 343 s to its first answer token; Claude Sonnet 5.5 (xhigh) scores 67.9 in 26 s, Claude Sonnet 5.5 (high) scores 65.6 in 10 s. DeepSeek V4.1 Flash 1017 (max) scores 64.0 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
108 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 | Claude Sonnet 5.5 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 69.4 | 64.0 |
| Agents & tools score | BenchLeader | 70.1 | 63.5 |
| Coding score | BenchLeader | 69.3 | 69.9 |
| Composite score | BenchLeader | 92.2 | 80.0 |
| Knowledge score | BenchLeader | 65.0 | 57.1 |
| Long context score | BenchLeader | 66.4 | 66.4 |
| Maths score | BenchLeader | 72.4 | 61.8 |
| Reasoning score | BenchLeader | 77.4 | 70.6 |
| Multimodal score | BenchLeader | – | 63.7 |
| Blended price $/M | BenchLeader | $4.00 | $0.525 |
| Output speed | BenchLeader | 133 tok/s | 195 tok/s |
| Time to first answer | BenchLeader | 343.1 s | 11.4 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 95.6% | 93.2% |
| Humanity's Last Exam | Scale AI / CAIS | 46.1%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1505† | – |
| LiveBench 2.0 Reasoning | LiveBench | 91.6%† | 89.1%† |
| LiveBench 1.0 Reasoning | LiveBench | 91.6% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 55.0% | 43.3% |
| ARC-AGI-1 | ARC Prize | 96.5% | 93.5% |
| ARC-AGI-2 | ARC Prize | 83.9%† | 78.1% |
| ARC-AGI-3 | ARC Prize | 72.4%† | – |
| CritPt | Artificial Analysis | 31.4% | 24.0% |
| MysteryMechanism | Vals AI | 49.1%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 59.0% | 46.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 65.0% | 49.0% |
| LMCA | Epoch AI Benchmarking Hub | 68.3% | – |
| DTBench | Epoch AI Benchmarking Hub | 97.3% | – |
| Coding | |||
| SciCode | SciCode | 61.0% | – |
| FrontierCode | Cognition | 52.1%† | – |
| Arena Coding | Arena (LMArena) | 1528† | – |
| Arena WebDev | Arena (LMArena) | 1769† | 1665 |
| LiveBench 2.0 Coding | LiveBench | 94.7%† | 96.0%† |
| LiveBench 1.0 Coding | LiveBench | 91.4% | – |
| SciCode (AA) | Artificial Analysis | 61.0% | 55.9% |
| IOI | Vals AI | 83.1%† | – |
| Code Migration | Vals AI | 69.8%† | 44.2% |
| Code Migration v1.1 | Vals AI | 86.9%† | 67.5% |
Show all 108 benchmarks
| Metric | Publisher | Claude Sonnet 5.5 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|---|
| Coding | |||
| ProgramBench | Vals AI | 6.5%† | – |
| SWE-bench Multimodal | Vals AI | 58.3%† | – |
| Vibe Code Bench v1.1 | Vals AI | 92.4%† | 87.7% |
| CursorBench | Cursor | 55.5% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 1819.1† | – |
| FrontierSWE | Epoch AI Benchmarking Hub | 61.9% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 63.6% | 33.8% |
| Startrise Frontend | Startrise | 75.9%† | – |
| FrontierCode 1.1 (AA) | Artificial Analysis | 45.8% | 43.7% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 61.8% | – |
| APEX-Agents | Mercor | 75.5% | – |
| Arena Agent | Arena (LMArena) | 14 | – |
| LiveBench Long Agentic | LiveBench | 78.8%† | 50.9%† |
| LiveBench Browser | LiveBench | 84.0%† | 76.0%† |
| LiveBench Agentic Coding | LiveBench | 56.3% | – |
| Terminal-Bench 2.1 (Vals) | Vals AI | 83.2%† | – |
| GDPval-AA v2.1 | Artificial Analysis | 66.9% | 62.3% |
| Analyst Agent (AA) | Artificial Analysis | 57.5% | – |
| CyberBench | Vals AI | 59.6%† | – |
| Finance Agent v2 | Vals AI | 58.1%† | 57.0% |
| Finance Agent v2.1 | Vals AI | 67.3%† | 62.9% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 10.4%† | 14.2% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 2.9%† | 9.2% |
| Legal Research Bench | Vals AI | 48.1%† | 45.2% |
| SREBench | Vals AI | 30.1%† | – |
| Tax Agent Bench | Vals AI | 42.0%† | 44.4% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 64.1%† | 31.8% |
| Terminal-Bench Science | Vals AI | 47.1%† | – |
| Vending-Bench 2 | Andon Labs | 11165.3† | – |
| AutomationBench | Artificial Analysis | 71.8% | 66.6% |
| GDP.pdf (AA) | Artificial Analysis | 25.8% | 17.2% |
| Harvey LAB-AA v1.1 | Harvey | 2.8% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1816 | 1570 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 53.3% | 12.9% |
| CWE-Bench (AA) | Artificial Analysis | – | 69.2% |
| DeepSec-Bench (AA) | Artificial Analysis | – | 24.9% |
| CyberGym end-to-end (AA) | Artificial Analysis | – | 76.3% |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 88.8% | 71.2% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 80.5% | 46.3% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | 99.4% |
| ProofBench | Vals AI | 100.0% | – |
| LiveBench Mathematics | LiveBench | 96.1% | – |
| Arena Maths | Arena (LMArena) | 1501† | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 46.5% | 42.5% |
| LiveBench 2.0 Data Analysis | LiveBench | 59.5%† | 79.5%† |
| LiveBench Research | LiveBench | 83.6%† | 79.5%† |
| LiveBench 1.0 Data Analysis | LiveBench | 59.5% | – |
| AA-Omniscience | Artificial Analysis | 32.3 | 4.7 |
| BioMysteryBench | Vals AI | 81.1%† | – |
| ClaimBench | Vals AI | 100.0%† | – |
| Excel Modeling Benchmark | Vals AI | 75.7%† | 61.8% |
| Excel Modeling Benchmark v1.1 | Vals AI | 75.9%† | 69.2% |
| MedCode | Vals AI | 52.9%† | – |
| MedScribe | Vals AI | 91.1%† | – |
| Public Benefits Bench v1.1 | Vals AI | 67.2%† | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 31.4% | – |
| AA-Omniscience: accuracy | Artificial Analysis | 54.0% | 42.9% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 53.0% | 33.3% |
| Instruction following | |||
| LiveBench Language | LiveBench | 78.0% | – |
| LiveBench Instruction Following | LiveBench | 56.8% | – |
| Arena Instruction Following | Arena (LMArena) | 1485† | – |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1478† | – |
| Arena Creative Writing | Arena (LMArena) | 1466† | – |
| Arena Multi-turn | Arena (LMArena) | 1474† | – |
| Arena Longer Queries | Arena (LMArena) | 1500† | – |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1287† | – |
| LiveBench Design | LiveBench | 85.0%† | 83.4%† |
| MMMU-Pro | Artificial Analysis | – | 80.6% |
| SAGE | Vals AI | 51.8%† | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 39.3%† | – |
| AA-3D | Artificial Analysis | 1199 | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 82.7% | 82.7% |
| MLCR | Artificial Analysis | 41.7% | 26.7% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 166.2† | – |
| LiveBench 2.0 | LiveBench | 82.5%† | 79.2%† |
| LiveBench 1.0 | LiveBench | 75.7% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 56 | 45.1 |
| Vals Index | Vals AI | 70.8† | 61.3 |
| Vals Finance Index | Vals AI | 64.5%† | 60.9% |
| Vals Science Index | Vals AI | 59.1%† | – |
| Vals Router Index | Vals AI | 69.0%† | 61.3%† |
| AA Cyber Index | Artificial Analysis | – | 56.8 |
| Metadata | |||
| AA Openness Index | Artificial Analysis | – | 44.4 |
Data as of 2026-10-25. Best configuration of each model; every score links to its source on the model pages.
What changed
- Claude Sonnet 5.5 (max): 1 score revision.
- 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.
- Claude Sonnet 5.5 (max): 1 new result (ARC-AGI-1); 1 score revision.
- 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.
- Claude Sonnet 5.5 (max): BenchLeader Index 67.6 → 69.5.
- Claude Sonnet 5.5 (max): 2 new results (LMCA, DTBench).
- Claude Sonnet 5.5 (max): 1 score revision.
- Claude Sonnet 5.5 (max): 1 score revision.
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- DeepSeek V4.1 Flash 1017 vs Gemini 4 Argon
- DeepSeek V4.1 Flash 1017 vs Muse Wonder Full
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- Claude Sonnet 5.5 vs DeepSeek V4 Pro
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Claude Sonnet 5.5 vs DeepSeek V4.1 Flash 1017: questions
- Is Claude Sonnet 5.5 better than DeepSeek V4.1 Flash 1017?
- Claude Sonnet 5.5 (max) and DeepSeek V4.1 Flash 1017 (max) are neck and neck on quality (69.4 vs 64.0, within the ±6.3 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, Claude Sonnet 5.5 or DeepSeek V4.1 Flash 1017, and will that change?
- DeepSeek V4.1 Flash 1017 is cheaper today: $0.525 against $4.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Claude Sonnet 5.5 better than DeepSeek V4.1 Flash 1017 for coding?
- They are level in coding (69 vs 70 on the category index).
- Is Claude Sonnet 5.5 better than DeepSeek V4.1 Flash 1017 for agents and tool use?
- Claude Sonnet 5.5 scores higher in agentic tasks (70 vs 64 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 take about 1M tokens: Claude Sonnet 5.5 1,000,000, DeepSeek V4.1 Flash 1017 1,048,576.
- Which has lower latency?
- DeepSeek V4.1 Flash 1017 (max) answers first: 11.4 s against 343.1 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.
- Which is faster, Claude Sonnet 5.5 or DeepSeek V4.1 Flash 1017?
- DeepSeek V4.1 Flash 1017 streams faster: 195 against 133 output tokens per second.
- Do independent benchmarks agree on Claude Sonnet 5.5 vs DeepSeek V4.1 Flash 1017?
- Across the 23 benchmarks both have, Claude Sonnet 5.5 leads 22, DeepSeek V4.1 Flash 1017 leads 0 and 1 is a tie. Every overall index that rates both puts Claude Sonnet 5.5 ahead.
- When was DeepSeek V4.1 Flash 1017 released?
- DeepSeek V4.1 Flash 1017 was released on 17 Oct 2026.