Claude Opus 4.8 vs DeepSeek V4.1 Flash 1017
Full profiles: Claude Opus 4.8 (Anthropic) and DeepSeek V4.1 Flash 1017 (DeepSeek): every benchmark, price and rank.
Updated · Data from 12 sources
As of 24 Oct 2026, Claude Opus 4.8 (max) and DeepSeek V4.1 Flash 1017 (max) are neck and neck on quality (63.3 vs 64.0 on the BenchLeader Index, inside the ±6.2 margin of error), and DeepSeek V4.1 Flash 1017 (max) costs 19× less, which makes it the better buy for most workloads. Pick Claude Opus 4.8 for knowledge (67 vs 57); pick DeepSeek V4.1 Flash 1017 for coding (70 vs 59).
Claude Opus 4.8 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 | DeepSeek V4.1 Flash 1017 | 70 vs 59 category score; SciCode (AA) 55.9% vs 54.4% | High |
| Agents & tool use | DeepSeek V4.1 Flash 1017 | 63 vs 57 category score; AutomationBench 66.6% vs 45.6% | Medium |
| Maths | Claude Opus 4.8 | 68 vs 62 category score; FrontierMath Tiers 1–3 80.0% vs 71.2% | Medium |
| Reasoning | DeepSeek V4.1 Flash 1017 | 71 vs 69 category score; GPQA Diamond 93.2% vs 91.0% | Medium |
| Knowledge | Claude Opus 4.8 | 67 vs 57 category score; SimpleQA Verified 53.0% vs 42.5% | High |
| Long documents | DeepSeek V4.1 Flash 1017 | 66 vs 64 category score; AA-LCR 82.7% vs 77.7% | Medium |
| Lowest cost | DeepSeek V4.1 Flash 1017 | $0.525 vs $10.00 per 1M blended; agentic coding session $0.023 vs $0.400 | – |
| Fastest first answer | DeepSeek V4.1 Flash 1017 | 11.2 s (DeepSeek V4.1 Flash 1017 (max)) vs 27.5 s (Claude Opus 4.8 (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 Opus 4.8 (max) and DeepSeek V4.1 Flash 1017 (max) are neck and neck on quality (63.3 vs 64.0, within the ±6.2 margin).
- Claude Opus 4.8 (max) is stronger in instruction following, knowledge, maths.
- DeepSeek V4.1 Flash 1017 (max) is stronger in agents & tools, coding, composite, long context, reasoning, multimodal.
- DeepSeek V4.1 Flash 1017 (max) is 19× cheaper ($0.525 vs $10.00 per 1M blended).
- DeepSeek V4.1 Flash 1017 (max) streams 3.1× faster (198 vs 63 tokens per second).
At a glance
| Spec | Claude Opus 4.8 | DeepSeek V4.1 Flash 1017 |
|---|---|---|
| Developer | Anthropic | DeepSeek |
| Released | 28 May 2026 | 17 Oct 2026 |
| Context window (tokens) | 1,000,000 | 1,048,576 |
| Compared at | Claude Opus 4.8 (max) | DeepSeek V4.1 Flash 1017 (max) |
| Open weights | No | Yes |
| Price in / out / cached input per 1M | $5.00 / $25.00 / $0.500 | $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 Opus 4.8 (max) | DeepSeek V4.1 Flash 1017 (max) | Leader |
|---|---|---|---|
| Reasoning | 68.8 | 70.6 | DeepSeek V4.1 Flash 1017 |
| Coding | 58.9 | 70.1 | DeepSeek V4.1 Flash 1017 |
| Agents & tools | 56.5 | 63.0 | DeepSeek V4.1 Flash 1017 |
| Maths | 68.1 | 61.8 | Claude Opus 4.8 |
| Knowledge | 66.9 | 57.1 | Claude Opus 4.8 |
| Instruction following | 62.1 | – | not comparable |
| Multimodal | – | 63.7 | not comparable |
| Long context | 63.8 | 66.4 | DeepSeek V4.1 Flash 1017 |
| Composite | 76.2 | 80.0 | DeepSeek V4.1 Flash 1017 |
Where sources disagree
Across the 19 benchmarks both have, Claude Opus 4.8 leads 9, DeepSeek V4.1 Flash 1017 leads 10. Every overall index that rates both puts DeepSeek V4.1 Flash 1017 ahead.
| Overall index | Claude Opus 4.8 (max) | DeepSeek V4.1 Flash 1017 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 63.3 | 64.0 | neck and neck |
| AA Intelligence Index v4.3.2 | 41.8 | 45.1 | DeepSeek 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.
| Measure | Claude Opus 4.8 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|
| Blended price per 1M tokens | $10.00 | $0.525 |
| Input / output per 1M | $5.00 / $25.00 | $0.300 / $1.20 |
| Cached input per 1M | $0.500 | $0.0060 |
| Price per task: chat reply | $0.0095 | $0.0005 |
| Price per task: summarize a 30-page report | $0.075 | $0.0043 |
| Price per task: code edit | $0.068 | $0.0036 |
| Price per task: agentic coding session | $0.400 | $0.023 |
| Price per task: structured extraction | $0.015 | $0.0008 |
| Cost to run a full benchmark suite | $4.08 | $0.262 |
| Output speed | 63 tok/s | 198 tok/s |
| Time to first answer | 27.5 s | 11.2 s |
| Time to a complete answer | 35.4 s | 13.7 s |
Per token is not per task: on Artificial Analysis' full suite Claude Opus 4.8 (max) cost $4.08 and DeepSeek V4.1 Flash 1017 (max) $0.262, because DeepSeek V4.1 Flash 1017 (max) used about 1.2× as many tokens for the same work.
Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 4.8 (max) scores 63.3 and takes 28 s to its first answer token; Claude Opus 4.8 (high) scores 60.7 in 1 s, Claude Opus 4.8 scores 60.1 in 1 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
144 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 Opus 4.8 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 63.3 | 64.0 |
| Agents & tools score | BenchLeader | 56.5 | 63.0 |
| Coding score | BenchLeader | 58.9 | 70.1 |
| Composite score | BenchLeader | 76.2 | 80.0 |
| Instruction following score | BenchLeader | 62.1 | – |
| Knowledge score | BenchLeader | 66.9 | 57.1 |
| Long context score | BenchLeader | 63.8 | 66.4 |
| Maths score | BenchLeader | 68.1 | 61.8 |
| Reasoning score | BenchLeader | 68.8 | 70.6 |
| Multimodal score | BenchLeader | – | 63.7 |
| Blended price $/M | BenchLeader | $10.00 | $0.525 |
| Output speed | BenchLeader | 63 tok/s | 198 tok/s |
| Time to first answer | BenchLeader | 27.5 s | 11.2 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 91.0% | 93.2% |
| SimpleBench | SimpleBench | 64.8%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1505† | – |
| LiveBench 2.0 Reasoning | LiveBench | 89.2%† | 89.1%† |
| LiveBench 1.0 Reasoning | LiveBench | 89.2% | – |
| GPQA Diamond (AA) | Artificial Analysis | 92.0% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 48.7% | 43.3% |
| GPQA Diamond (Vals) | Vals AI | 92.4%† | – |
| EnigmaEval | Scale AI SEAL | 23.5%† | – |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 88.8%† | – |
| ARC-AGI-1 | ARC Prize | 92.5% | 93.5% |
| ARC-AGI-2 | ARC Prize | 72.1%† | 78.1% |
| ARC-AGI-3 | ARC Prize | 1.5%† | – |
| CritPt | Artificial Analysis | 20.9% | 24.0% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 52.0% | 46.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 36.0% | 49.0% |
| LMCA | Epoch AI Benchmarking Hub | 57.5% | – |
| DTBench | Epoch AI Benchmarking Hub | 94.9% | – |
| ForecastBench | ForecastBench | 66.3% | – |
| BTF-3 | Epoch AI Benchmarking Hub | 14.0%† | – |
| Coding | |||
| SciCode | SciCode | 53.5% | – |
| WeirdML | WeirdML | 70.5%† | – |
| FrontierCode | Cognition | 46.5%† | – |
| GSO-Bench | GSO-Bench | 47.1%† | – |
| Arena Coding | Arena (LMArena) | 1529† | – |
Show all 144 benchmarks
| Metric | Publisher | Claude Opus 4.8 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|---|
| Coding | |||
| Arena WebDev | Arena (LMArena) | 1536† | 1664 |
| LiveBench 2.0 Coding | LiveBench | 77.3%† | 96.0%† |
| LiveBench 1.0 Coding | LiveBench | 81.8% | – |
| SciCode (AA) | Artificial Analysis | 54.4% | 55.9% |
| LiveCodeBench | Vals AI | 87.8%† | – |
| SWE-bench (Vals) | Vals AI | 88.6%† | – |
| Code Migration | Vals AI | 47.3%† | 44.2% |
| Code Migration v1.1 | Vals AI | – | 67.5% |
| ProgramBench | Vals AI | 1.0%† | – |
| Vibe Code Bench v1.1 | Vals AI | 82.7%† | 87.7% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 57.3%† | – |
| SWE Atlas: Refactoring | Scale AI SEAL | 46.7%† | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 49.6%† | – |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 87.5%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 59.0% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 1563.8† | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 21.7% | 33.8% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 84.6% | – |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 43.7% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 23.6% | – |
| OSWorld-Verified 2.0 | OSWorld | 20.6% | – |
| Remote Labor Index | Scale AI / CAIS | 8.3%† | – |
| APEX-Agents | Mercor | 48.9% | – |
| LiveBench Long Agentic | LiveBench | 48.3%† | 50.9%† |
| LiveBench Browser | LiveBench | 96.0%† | 76.0%† |
| LiveBench Agentic Coding | LiveBench | 50.5% | – |
| Terminal-Bench Hard | Artificial Analysis | 58.3% | – |
| τ²-Bench Telecom (AA) | Artificial Analysis | 94.4% | – |
| Terminal-Bench 2.1 (Vals) | Vals AI | 71.9%† | – |
| MCP Atlas | Scale AI SEAL | 82.2% | – |
| HiL-Bench | Scale AI SEAL | 35.3%† | – |
| τ³-bench Banking | τ²-bench | 39.7% | – |
| GDPval-AA v2.1 | Artificial Analysis | – | 62.3% |
| τ³-Banking (AA) | Artificial Analysis | 34.2% | – |
| Analyst Agent (AA) | Artificial Analysis | 45.0% | – |
| Finance Agent v2 | Vals AI | 53.9%† | 57.0% |
| Finance Agent v2.1 | Vals AI | – | 62.9% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | – | 14.2% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 9.6%† | 9.2% |
| Legal Research Bench | Vals AI | 43.8%† | 45.2% |
| SkillsBench | Vals AI | 59.2%† | – |
| Tax Agent Bench | Vals AI | 30.0%† | 44.4% |
| Terminal-Bench 2.0 (Vals) | Vals AI | 70.0%† | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 23.2%† | 31.8% |
| Terminal-Bench Science | Vals AI | 4.3%† | – |
| Time Horizon Index: KSP | Vals AI | 11.8%† | – |
| Arena Search | Arena (LMArena) | 1195† | – |
| DeepResearch Bench | DeepResearch Bench | 50.2%† | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 32.9% | – |
| GBAEval | Epoch AI Benchmarking Hub | 70.9%† | – |
| Vending-Bench 2 | Andon Labs | 2992.3 | – |
| AutomationBench | Artificial Analysis | 45.6% | 66.6% |
| GDP.pdf (AA) | Artificial Analysis | 22.8% | 17.2% |
| EnterpriseOps-Gym | Artificial Analysis | 44.0% | – |
| AA-Briefcase v1.1 | Artificial Analysis | – | 1570 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | – | 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% |
| FACTS Search | 79.6%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 80.0% | 71.2% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 56.1% | 46.3% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 98.3% | 99.4% |
| ProofBench | Vals AI | 69.0% | – |
| LiveBench Mathematics | LiveBench | 94.3% | – |
| AIME 2026 | MathArena | 100.0% | – |
| HMMT February 2026 | MathArena | 95.5% | – |
| MathArena Apex | MathArena | 81.3% | – |
| Arena Maths | Arena (LMArena) | 1477† | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 53.0% | 42.5% |
| LiveBench 2.0 Data Analysis | LiveBench | 66.0%† | 79.5%† |
| LiveBench Research | LiveBench | 81.8%† | 79.5%† |
| LiveBench 1.0 Data Analysis | LiveBench | 66.0% | – |
| AA-Omniscience | Artificial Analysis | 28.8 | 4.7 |
| MMLU-Pro | Vals AI | 89.6%† | – |
| LegalBench | Vals AI | 83.6%† | – |
| CorpFin | Vals AI | 66.7%† | – |
| TaxEval | Vals AI | 75.6%† | – |
| Excel Modeling Benchmark | Vals AI | 69.4%† | 61.8% |
| Excel Modeling Benchmark v1.1 | Vals AI | – | 69.2% |
| MedCode | Vals AI | 53.2%† | – |
| MedScribe | Vals AI | 85.8%† | – |
| Public Benefits Bench v1.1 | Vals AI | 68.1%† | – |
| DrugDiscoveryBench | Scale AI SEAL | 46.8% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 28.6% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 24.0% | – |
| AA-Omniscience: accuracy | Artificial Analysis | 48.8% | 42.9% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 60.8% | 33.3% |
| Instruction following | |||
| LiveBench Language | LiveBench | 79.7% | – |
| LiveBench Instruction Following | LiveBench | 72.0% | – |
| IFBench | Artificial Analysis | 62.2% | – |
| Arena Instruction Following | Arena (LMArena) | 1478† | – |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1474† | – |
| EQ-Bench 4 | EQ-Bench | 1281† | – |
| Arena Creative Writing | Arena (LMArena) | 1463† | – |
| Arena Multi-turn | Arena (LMArena) | 1495† | – |
| Arena Longer Queries | Arena (LMArena) | 1499† | – |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1289† | – |
| LiveBench Design | LiveBench | 78.8%† | 83.4%† |
| MMMU-Pro | Artificial Analysis | – | 80.6% |
| MMMU-Pro (Vals) | Vals AI | 86.6%† | – |
| MortgageTax | Vals AI | 69.9%† | – |
| SAGE | Vals AI | 54.8%† | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 14.5%† | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 77.7% | 82.7% |
| Arena Document | Arena (LMArena) | 1475† | – |
| MLCR | Artificial Analysis | 19.4% | 26.7% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 159.0† | – |
| LiveBench 2.0 | LiveBench | 76.8%† | 79.2%† |
| LiveBench 1.0 | LiveBench | 76.2% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 41.8 | 45.1 |
| Vals Index | Vals AI | – | 61.3 |
| Vals Finance Index | Vals AI | – | 60.9% |
| Vals RSI Index | Vals AI | 24.0% | – |
| Vals Multimodal Index | Vals AI | 70.9%† | – |
| Vals Router Index | Vals AI | – | 61.3%† |
| AA Cyber Index | Artificial Analysis | – | 56.8 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 18.2% | – |
| Metadata | |||
| AA Openness Index | Artificial Analysis | – | 44.4 |
Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.
What changed
- Claude Opus 4.8 (max): 1 new result (Vals RSI Index).
- 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 Opus 4.8 (max): 1 score revision.
- DeepSeek V4.1 Flash 1017 (max): 11 new results (GPQA Diamond, FrontierMath Tiers 1–3, FrontierMath Tier 4…).
- Claude Opus 4.8 (max): 1 new result (ForecastBench).
- DeepSeek V4.1 Flash 1017 (max): 1 new result (FrontierCode 1.1 (AA)); 2 score revisions.
- Claude Opus 4.8 (max): BenchLeader Index 62.5 → 63.4.
- Claude Opus 4.8 (max): 5 new results (AutomationBench, GDP.pdf (AA), MLCR…).
- Claude Opus 4.8 (max): 1 score revision.
Related comparisons
- Claude Opus 4.8 vs Claude Opus 5.5
- Claude Opus 4.8 vs Gemini 4 Argon
- Claude Opus 4.8 vs Muse Wonder Full
- DeepSeek V4.1 Flash 1017 vs Claude Opus 5.5
- DeepSeek V4.1 Flash 1017 vs Gemini 4 Argon
- DeepSeek V4.1 Flash 1017 vs Muse Wonder Full
- DeepSeek V4.1 Flash 1017 vs Claude Fable 5.1
- Claude Opus 4.7 vs DeepSeek V4.1 Flash 1017
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Claude Opus 4.8 vs DeepSeek V4.1 Flash 1017: questions
- Is Claude Opus 4.8 better than DeepSeek V4.1 Flash 1017?
- Claude Opus 4.8 (max) and DeepSeek V4.1 Flash 1017 (max) are neck and neck on quality (63.3 vs 64.0, within the ±6.2 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-24, so check the category scores for your use.
- Which is cheaper, Claude Opus 4.8 or DeepSeek V4.1 Flash 1017, and will that change?
- DeepSeek V4.1 Flash 1017 is cheaper today: $0.525 against $10.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Claude Opus 4.8 better than DeepSeek V4.1 Flash 1017 for coding?
- DeepSeek V4.1 Flash 1017 scores higher in coding (70 vs 59 on the category index, where 50 is average).
- Is Claude Opus 4.8 better than DeepSeek V4.1 Flash 1017 for agents and tool use?
- DeepSeek V4.1 Flash 1017 scores higher in agentic tasks (63 vs 57 on the category index, where 50 is average).
- Which is better for long documents?
- DeepSeek V4.1 Flash 1017 scores higher on long-context benchmarks (66 vs 64). Both take about 1M tokens: Claude Opus 4.8 1,000,000, DeepSeek V4.1 Flash 1017 1,048,576.
- Which has lower latency?
- DeepSeek V4.1 Flash 1017 (max) answers first: 11.2 s against 27.5 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 Opus 4.8 or DeepSeek V4.1 Flash 1017?
- DeepSeek V4.1 Flash 1017 streams faster: 198 against 63 output tokens per second.
- Do independent benchmarks agree on Claude Opus 4.8 vs DeepSeek V4.1 Flash 1017?
- Across the 19 benchmarks both have, Claude Opus 4.8 leads 9, DeepSeek V4.1 Flash 1017 leads 10. 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.