Claude Fable 5.2 vs DeepSeek V4.1 Flash 1017
Full profiles: Claude Fable 5.2 (Anthropic) and DeepSeek V4.1 Flash 1017 (DeepSeek): every benchmark, price and rank.
Updated · Data from 9 sources
As of 9 Nov 2026, Claude Fable 5.2 is ahead of DeepSeek V4.1 Flash on quality (69.4 vs 58.9 on the BenchLeader Index), but DeepSeek V4.1 Flash is 30× cheaper at $0.525 vs $16.00 per 1M tokens blended. Claude Fable 5.2 leads in every category we measure both in. DeepSeek V4.1 Flash streams ~2× faster.
Key facts (as of 9 Nov 2026)
- Claude Fable 5.2 scores 69.4 on the BenchLeader Index and DeepSeek V4.1 Flash scores 58.9 (BenchLeader, 9 Nov 2026).
- Claude Fable 5.2 costs $16.00 per 1M tokens blended (list price, 9 Nov 2026).
- DeepSeek V4.1 Flash costs $0.525 per 1M tokens blended (list price, 9 Nov 2026).
- DeepSeek V4.1 Flash streams ~2× faster than Claude Fable 5.2 (Artificial Analysis, 7-day median, 9 Nov 2026).
- Of the 20 benchmarks both models have, Claude Fable 5.2 leads 20 (BenchLeader, 9 Nov 2026).
Claude Fable 5.2 benchmarks max Anthropic
DeepSeek V4.1 Flash 1017 benchmarks max DeepSeekAdd a third modelWhich 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 | Claude Fable 5.2 | 80 vs 63 category score; FrontierCode 2.0 (AA) 48.8% vs 28.5% | High |
| Reasoning | Claude Fable 5.2 | 78 vs 56 category score; HLE-Diamond (AA) 80.2% vs 25.3% | High |
| Knowledge | Claude Fable 5.2 | 82 vs 48 category score; AA-Omniscience v1.1 66.8 vs 0.9 | High |
| Long documents | Either | 66 vs 66 category score; AA-LCR v1.1 83.3% vs 82.7% | Either |
| Lowest cost | DeepSeek V4.1 Flash 1017 | $0.525 vs $16.00 per 1M blended; agentic coding session $0.023 vs $0.640 | – |
| Fastest first answer | Claude Fable 5.2 | 3.0 s (Claude Fable 5.2 (max)) vs 51.3 s (DeepSeek V4.1 Flash 1017 (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 Fable 5.2 (max) leads on quality: 69.4 vs 58.9.
- Claude Fable 5.2 (max) is stronger in coding, knowledge, long context, reasoning.
- DeepSeek V4.1 Flash 1017 (max) is stronger in agents & tools, maths, multimodal.
- DeepSeek V4.1 Flash 1017 (max) is 30× cheaper ($0.525 vs $16.00 per 1M blended).
- DeepSeek V4.1 Flash 1017 (max) streams 2.0× faster (146 vs 72 tokens per second).
At a glance
| Spec | Claude Fable 5.2 | DeepSeek V4.1 Flash 1017 |
|---|---|---|
| Developer | Anthropic | DeepSeek |
| Released | 9 Nov 2026 | 17 Oct 2026 |
| Context window (tokens) | 1,000,000 | 1,048,576 |
| Compared at | Claude Fable 5.2 (max) | DeepSeek V4.1 Flash 1017 (max) |
| Open weights | No | Yes |
| Price in / out / cached input per 1M | $8.00 / $40.00 / $0.200 | $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 Fable 5.2 (max) | DeepSeek V4.1 Flash 1017 (max) | Leader |
|---|---|---|---|
| Reasoning | 78.4 | 56.0 | Claude Fable 5.2 |
| Coding | 80.2 | 63.4 | Claude Fable 5.2 |
| Agents & tools | – | 62.9 | not comparable |
| Maths | – | 61.5 | not comparable |
| Knowledge | 81.7 | 48.1 | Claude Fable 5.2 |
| Multimodal | – | 63.1 | not comparable |
| Long context | 66.4 | 66.1 | level |
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.
Not drawn, measured for fewer than two of these models: Agents & tools, Maths, Instruction following, Multimodal, Human preference.
Where sources disagree
Across the 20 benchmarks both have, Claude Fable 5.2 leads 20, DeepSeek V4.1 Flash 1017 leads 0. Every overall index that rates both puts Claude Fable 5.2 ahead.
| Overall index | Claude Fable 5.2 (max) | DeepSeek V4.1 Flash 1017 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 69.4 | 58.9 | Claude Fable 5.2 |
| AA Intelligence Index v5.0 | 64.6 | 32.6 | Claude Fable 5.2 |
| Vals Index | 71.3† | 61.3 | Claude Fable 5.2 |
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.
| Measure | Claude Fable 5.2 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|
| Blended price per 1M tokens | $16.00 | $0.525 |
| Input / output per 1M | $8.00 / $40.00 | $0.300 / $1.20 |
| Cached input per 1M | $0.200 | $0.0060 |
| Price per task: chat reply | $0.015 | $0.0005 |
| Price per task: summarize a 30-page report | $0.120 | $0.0043 |
| Price per task: code edit | $0.108 | $0.0036 |
| Price per task: agentic coding session | $0.640 | $0.023 |
| Price per task: structured extraction | $0.024 | $0.0008 |
| Agentic coding session, input mostly cached | $0.289 | $0.0096 |
| Cost per benchmark task (AA Index) | $26.54 | $0.602 |
| Output tokens per task (AA Index) | 274k | 139k |
| Of which reasoning | 193k | 91k |
| Time per task (AA Index) | – | 16 min |
| Output speed | 72 tok/s | 146 tok/s |
| Time to first answer | 3.0 s | 51.3 s |
| Time to a complete answer | – | 103.0 s |
Per token is not per task: an average task of Artificial Analysis' Intelligence Index cost $26.54 on Claude Fable 5.2 (max) and $0.602 on DeepSeek V4.1 Flash 1017 (max), and Claude Fable 5.2 (max) wrote 2.0× as many output tokens for the same work, which a per-token price hides.
Each model is compared at its best-ranked reasoning-effort setting. Claude Fable 5.2 (max) scores 69.4 and takes 3 s to its first answer token; Claude Fable 5.2 (high) scores 68.9 in 3 s, Claude Fable 5.2 (xhigh) scores 68.7 in 3 s. DeepSeek V4.1 Flash 1017 (max) scores 58.9 and takes 51 s to its first answer token; DeepSeek V4.1 Flash 1017 (high) scores 51.2 in 24 s, DeepSeek V4.1 Flash 1017 (no reasoning) scores 45.0 in 1 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
88 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 Fable 5.2 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 69.4 | 58.9 |
| Coding score | BenchLeader | 80.2 | 63.4 |
| Knowledge score | BenchLeader | 81.7 | 48.1 |
| Long context score | BenchLeader | 66.4 | 66.1 |
| Reasoning score | BenchLeader | 78.4 | 56.0 |
| Agents & tools score | BenchLeader | – | 62.9 |
| Maths score | BenchLeader | – | 61.5 |
| Multimodal score | BenchLeader | – | 63.1 |
| Blended price $/M | BenchLeader | $16.00 | $0.525 |
| Output speed | BenchLeader | 72 tok/s | 146 tok/s |
| Time to first answer | BenchLeader | 3.0 s | 51.3 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | – | 93.2% |
| LiveBench 2.0 Reasoning | LiveBench | 88.8%† | 89.1%† |
| Humanity's Last Exam (AA) | Artificial Analysis | 74.3% | 43.3% |
| HLE-Diamond (AA) | Artificial Analysis | 80.2% | 25.3% |
| ARC-AGI-1 | ARC Prize | 97.5% | 93.5% |
| ARC-AGI-2 | ARC Prize | 92.5% | 78.1% |
| ARC-AGI-3 | ARC Prize | 94.9% | 5.8% |
| CritPt | Artificial Analysis | 35.4% | 24.0% |
| CritPt v2 hard subset (AA) | Artificial Analysis | 76.5% | 25.0% |
| MysteryMechanism | Vals AI | 51.8%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | – | 46.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | – | 49.0% |
| Coding | |||
| SciCode | SciCode | – | 55.9% |
| Arena WebDev | Arena (LMArena) | – | 1664 |
| LiveBench 2.0 Coding | LiveBench | 79.2%† | 80.4%† |
| SciCode (AA) | Artificial Analysis | 67.7% | 55.9% |
| Code Migration | Vals AI | – | 44.2% |
| Code Migration v1.1 | Vals AI | 83.3%† | 67.5% |
| ProgramBench | Vals AI | 19.0%† | – |
| SWE-bench Multimodal | Vals AI | 62.3%† | – |
| Vibe Code Bench v1.1 | Vals AI | 93.8%† | 87.7% |
| CursorBench | Cursor | – | 47.7% |
| ALE-Bench | Epoch AI Benchmarking Hub | – | 1622 |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 59.6% | 33.8% |
| Startrise Frontend | Startrise | – | 74.2%† |
Show all 88 benchmarks
| Metric | Publisher | Claude Fable 5.2 (max) | DeepSeek V4.1 Flash 1017 (max) |
|---|---|---|---|
| Coding | |||
| GameBench 2 Overall | DuelLab GameBench 2 | – | 61.3† |
| GameBench 2 by reasoning setting | DuelLab GameBench 2 | – | 69.8 |
| Design Arena Website | Design Arena | – | 1295† |
| FrontierCode 1.1 (AA) | Artificial Analysis | 56.2% | 43.7% |
| FrontierCode 2.0 (AA) | Artificial Analysis | 48.8% | 28.5% |
| Agents & tools | |||
| APEX-Agents | Mercor | – | 69.8% |
| Arena Agent | Arena (LMArena) | – | 2.1 |
| LiveBench Long Agentic | LiveBench | 82.9%† | 38.8%† |
| LiveBench Browser | LiveBench | 86.9%† | 67.2%† |
| GDPval-AA v2.1, normalised score | Artificial Analysis | – | 62.3% |
| GDPval-AA v2.1 | Artificial Analysis | 1831 | 1746 |
| Finance Agent v2 | Vals AI | – | 57.0% |
| Finance Agent v2.1 | Vals AI | 69.5%† | 62.9% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 5.0%† | 14.2% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | – | 9.2% |
| Legal Research Bench | Vals AI | 46.1%† | 45.2% |
| Tax Agent Bench | Vals AI | 32.1%† | 44.4% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 65.2%† | 31.8% |
| Terminal-Bench Science | Vals AI | 55.7%† | – |
| AutomationBench | Artificial Analysis | 76.4% | 66.6% |
| GDP.pdf (AA) | Artificial Analysis | 24.2% | 17.2% |
| Harvey LAB-AA v1.1 | Harvey | 7.2% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1785 | 1570 |
| GDPx | GDPx by SemiAnalysis | – | 5.4% |
| Design Arena Agentic | Design Arena | – | 1304† |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 73.3% | 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 | – | 71.2% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | – | 46.3% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | – | 99.4% |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | – | 42.5% |
| LiveBench 2.0 Data Analysis | LiveBench | 81.5%† | 79.5%† |
| LiveBench Research | LiveBench | 94.5%† | 78.6%† |
| AA-Omniscience v1.1 | Artificial Analysis | 66.8 | 0.9 |
| PRBench Finance | Scale AI SEAL | – | 47.1%† |
| PRBench Legal | Scale AI SEAL | – | 47.3%† |
| BioMysteryBench | Vals AI | 83.7%† | – |
| Excel Modeling Benchmark | Vals AI | – | 61.8% |
| Excel Modeling Benchmark v1.1 | Vals AI | 77.4%† | 69.2% |
| DrugDiscoveryBench | Scale AI SEAL | – | 60.6%† |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 79.1% | 39.6% |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 40.7% | 35.9% |
| HealthBench Professional (AA) | OpenAI | 67.7% | – |
| Instruction following | |||
| MultiChallenge | Scale AI SEAL | – | 74.9%† |
| Multimodal | |||
| LiveBench Design | LiveBench | 85.1%† | 79.8%† |
| MMMU-Pro | Artificial Analysis | – | 80.6% |
| AA-3D | Artificial Analysis | 1271 | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 83.3% | 82.7% |
| MLCR | Artificial Analysis | – | 26.7% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | – | 159.3† |
| LiveBench 2.0 | LiveBench | 84.9%† | 70.3%† |
| AA Intelligence Index v5.0 | Artificial Analysis | 64.6 | 32.6 |
| AA Intelligence Index v4.3.2 | Artificial Analysis | – | 45.1 |
| AA Progress Index v1 | Artificial Analysis | – | 323.7 |
| Vals Index | Vals AI | 71.3† | 61.3 |
| Vals Finance Index | Vals AI | 63.6%† | 60.9% |
| Vals Science Index | Vals AI | 63.7%† | – |
| Vals Router Index | Vals AI | – | 61.3%† |
| AA Cyber Index | Artificial Analysis | – | 56.8 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | – | 27.2%† |
| Metadata | |||
| AA Openness Index | Artificial Analysis | – | 44.4 |
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
- DeepSeek V4.1 Flash 1017 (max): 1 score revision.
- DeepSeek V4.1 Flash 1017 (max): 3 score revisions.
- DeepSeek V4.1 Flash 1017 (max): 1 new result (ARC-AGI-3); 2 score revisions.
- DeepSeek V4.1 Flash 1017 (max): 1 score revision.
- DeepSeek V4.1 Flash 1017 (max): 1 score revision.
- DeepSeek V4.1 Flash 1017 (max): 1 new result (Arena Agent); 1 score revision.
- DeepSeek V4.1 Flash 1017 (max): 4 new results (SciCode, APEX-Agents, CursorBench…); 1 score revision.
- DeepSeek V4.1 Flash 1017 (max): BenchLeader Index 61.8 → 59.0.
- DeepSeek V4.1 Flash 1017 (max): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 4 score revisions; cost per task moved from $0.26/M to $0.60/M (130% up).
- DeepSeek V4.1 Flash 1017 (max): BenchLeader Index 61.3 → 61.8.
Related comparisons
- Claude Fable 5.2 vs Claude Opus 5.5
- Claude Fable 5.2 vs Gemini 4 Carbon
- Claude Fable 5.2 vs GPT-6 Astra
- DeepSeek V4.1 Flash 1017 vs Claude Opus 5.5
- DeepSeek V4.1 Flash 1017 vs Gemini 4 Carbon
- DeepSeek V4.1 Flash 1017 vs GPT-6 Astra
- Claude Fable 5.2 vs DeepSeek V4 Pro
- Claude Fable 5.2 vs Claude Fable 5.1
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Claude Fable 5.2 vs DeepSeek V4.1 Flash 1017: questions
- Is Claude Fable 5.2 better than DeepSeek V4.1 Flash 1017?
- Claude Fable 5.2 (max) leads on quality: 69.4 vs 58.9. The BenchLeader Index combines every independent quality benchmark; Claude Fable 5.2 (max) is ahead overall as of 9 Nov 2026, but check the category scores for your use.
- Claude Fable 5.2 vs DeepSeek V4.1 Flash 1017: which is cheaper, and will that change?
- DeepSeek V4.1 Flash 1017 is cheaper today: $0.525 against $16.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Claude Fable 5.2 or DeepSeek V4.1 Flash 1017 better for coding?
- Claude Fable 5.2 scores higher in coding (80 vs 63 on the category index, where 50 is average). On FrontierCode 2.0 (AA), the top shared coding benchmark, it is 48.8% for Claude Fable 5.2 against 28.5% for DeepSeek V4.1 Flash 1017.
- Which is faster, Claude Fable 5.2 or DeepSeek V4.1 Flash 1017?
- DeepSeek V4.1 Flash 1017 streams ~2× faster (146 vs 72 output tokens per second, Artificial Analysis 7-day median).
- Is DeepSeek V4.1 Flash the same as DeepSeek V4.1 Flash 1017?
- DeepSeek V4.1 Flash 1017 is the checkpoint compared here (BenchLeader Index 58.9); people searching for DeepSeek V4.1 Flash land on this page because it replaced that earlier build.
More questions (4)
- Which is better for long documents?
- They are level on long-context benchmarks (66 vs 66). Both take about 1M tokens: Claude Fable 5.2 1,000,000, DeepSeek V4.1 Flash 1017 1,048,576.
- Which has lower latency?
- Claude Fable 5.2 answers first: 3.0 s against 51.3 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 Claude Fable 5.2 vs DeepSeek V4.1 Flash 1017?
- Across the 20 benchmarks both have, Claude Fable 5.2 leads 20, DeepSeek V4.1 Flash 1017 leads 0. Every overall index that rates both puts Claude Fable 5.2 ahead.
- When was Claude Fable 5.2 released?
- Claude Fable 5.2 was released on 9 Nov 2026.