DeepSeek V4.1 Flash 1017 vs Muse Wonder
Full profiles: DeepSeek V4.1 Flash 1017 (DeepSeek) and Muse Wonder (Meta): every benchmark, price and rank.
Updated · Data from 8 sources
As of 25 Oct 2026, DeepSeek V4.1 Flash 1017 (max) and Muse Wonder (max) are neck and neck on quality (64.0 vs 67.5 on the BenchLeader Index, inside the ±5.8 margin of error), and DeepSeek V4.1 Flash 1017 (max) costs 15× less, which makes it the better buy for most workloads. Pick DeepSeek V4.1 Flash 1017 for agents & tools (64 vs 56); pick Muse Wonder for knowledge (73 vs 57).
DeepSeek V4.1 Flash 1017 benchmarks max DeepSeek
Muse Wonder benchmarks max MetaOpen 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 66 category score; Arena WebDev 1665 vs 1651 | Medium |
| Agents & tool use | DeepSeek V4.1 Flash 1017 | 64 vs 56 category score; Finance Agent v2 57.0% vs 56.6% | High |
| Maths | Muse Wonder | 68 vs 62 category score; FrontierMath Tiers 1–3 82.1% vs 71.2% | Medium |
| Reasoning | Muse Wonder | 81 vs 71 category score; CritPt 28.3% vs 24.0% | High |
| Knowledge | Muse Wonder | 73 vs 57 category score; AA-Omniscience 25.5 vs 4.7 | High |
| Long documents | DeepSeek V4.1 Flash 1017 | 66 vs 65 category score; AA-LCR 82.7% vs 80.7% | Medium |
| Chat quality (human preference) | – | Only Muse Wonder has an Arena rating (71 category score) | Not comparable |
| Lowest cost | DeepSeek V4.1 Flash 1017 | $0.525 vs $8.00 per 1M blended; agentic coding session $0.023 vs $0.320 | – |
| Fastest first answer | DeepSeek V4.1 Flash 1017 | 11.4 s (DeepSeek V4.1 Flash 1017 (max)) vs 40.3 s (Muse Wonder (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
- DeepSeek V4.1 Flash 1017 (max) and Muse Wonder (max) are neck and neck on quality (64.0 vs 67.5, within the ±5.8 margin).
- DeepSeek V4.1 Flash 1017 (max) is stronger in agents & tools, coding, long context, multimodal.
- Muse Wonder (max) is stronger in composite, knowledge, maths, reasoning, human preference.
- DeepSeek V4.1 Flash 1017 (max) is 15× cheaper ($0.525 vs $8.00 per 1M blended).
- DeepSeek V4.1 Flash 1017 (max) streams 1.3× faster (195 vs 145 tokens per second).
At a glance
| Spec | DeepSeek V4.1 Flash 1017 | Muse Wonder |
|---|---|---|
| Developer | DeepSeek | Meta |
| Released | 17 Oct 2026 | 12 Oct 2026 |
| Context window (tokens) | 1,048,576 | 1,048,576 |
| Compared at | DeepSeek V4.1 Flash 1017 (max) | Muse Wonder (max) |
| Open weights | Yes | No |
| Price in / out / cached input per 1M | $0.300 / $1.20 / $0.0060 | $4.00 / $20.00 / $0.200 |
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 | DeepSeek V4.1 Flash 1017 (max) | Muse Wonder (max) | Leader |
|---|---|---|---|
| Reasoning | 70.6 | 81.3 | Muse Wonder |
| Coding | 69.9 | 66.1 | DeepSeek V4.1 Flash 1017 |
| Agents & tools | 63.5 | 55.8 | DeepSeek V4.1 Flash 1017 |
| Maths | 61.8 | 67.8 | Muse Wonder |
| Knowledge | 57.1 | 73.0 | Muse Wonder |
| Human preference | – | 70.7 | not comparable |
| Multimodal | 63.7 | – | not comparable |
| Long context | 66.4 | 65.4 | DeepSeek V4.1 Flash 1017 |
| Composite | 80.0 | 88.1 | Muse Wonder |
Where sources disagree
Across the 33 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 7, Muse Wonder leads 25 and 1 is a tie. Every overall index that rates both puts Muse Wonder ahead.
| Overall index | DeepSeek V4.1 Flash 1017 (max) | Muse Wonder (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 64.0 | 67.5 | neck and neck |
| AA Intelligence Index v4.3.2 | 45.1 | 52.4 | Muse Wonder |
| Vals Index | 61.3 | 64.9 | Muse Wonder |
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 | DeepSeek V4.1 Flash 1017 (max) | Muse Wonder (max) |
|---|---|---|
| Blended price per 1M tokens | $0.525 | $8.00 |
| Input / output per 1M | $0.300 / $1.20 | $4.00 / $20.00 |
| Cached input per 1M | $0.0060 | $0.200 |
| Price per task: chat reply | $0.0005 | $0.0076 |
| Price per task: summarize a 30-page report | $0.0043 | $0.060 |
| Price per task: code edit | $0.0036 | $0.054 |
| Price per task: agentic coding session | $0.023 | $0.320 |
| Price per task: structured extraction | $0.0008 | $0.012 |
| Cost to run a full benchmark suite | $0.262 | $4.54 |
| Output speed | 195 tok/s | 145 tok/s |
| Time to first answer | 11.4 s | 40.3 s |
| Time to a complete answer | 13.9 s | 43.8 s |
Per token is not per task: on Artificial Analysis' full suite DeepSeek V4.1 Flash 1017 (max) cost $0.262 and Muse Wonder (max) $4.54, because Muse Wonder (max) used about 1.1× as many tokens for the same work.
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. Muse Wonder (max) scores 67.5 and takes 40 s to its first answer token; Muse Wonder scores 64.3 in 3 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
96 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 | DeepSeek V4.1 Flash 1017 (max) | Muse Wonder (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 64.0 | 67.5 |
| Agents & tools score | BenchLeader | 63.5 | 55.8 |
| Coding score | BenchLeader | 69.9 | 66.1 |
| Composite score | BenchLeader | 80.0 | 88.1 |
| Knowledge score | BenchLeader | 57.1 | 73.0 |
| Long context score | BenchLeader | 66.4 | 65.4 |
| Maths score | BenchLeader | 61.8 | 67.8 |
| Multimodal score | BenchLeader | 63.7 | – |
| Reasoning score | BenchLeader | 70.6 | 81.3 |
| Human preference score | BenchLeader | – | 70.7 |
| Blended price $/M | BenchLeader | $0.525 | $8.00 |
| Output speed | BenchLeader | 195 tok/s | 145 tok/s |
| Time to first answer | BenchLeader | 11.4 s | 40.3 s |
| Context window | BenchLeader | 1,048,576 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 93.2% | – |
| Arena Hard Prompts | Arena (LMArena) | – | 1522 |
| LiveBench 2.0 Reasoning | LiveBench | 89.1%† | 90.6%† |
| LiveBench 1.0 Reasoning | LiveBench | – | 90.6% |
| Humanity's Last Exam (AA) | Artificial Analysis | 43.3% | 50.1% |
| ARC-AGI-1 | ARC Prize | 93.5% | – |
| ARC-AGI-2 | ARC Prize | 78.1% | – |
| CritPt | Artificial Analysis | 24.0% | 28.3% |
| MysteryMechanism | Vals AI | – | 27.5% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 46.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 49.0% | 51.0% |
| LMCA | Epoch AI Benchmarking Hub | – | 56.8%† |
| DTBench | Epoch AI Benchmarking Hub | – | 95.2%† |
| Coding | |||
| SciCode | SciCode | – | 60.3% |
| Arena Coding | Arena (LMArena) | – | 1545 |
| Arena WebDev | Arena (LMArena) | 1665 | 1651 |
| LiveBench 2.0 Coding | LiveBench | 96.0%† | 86.2%† |
| LiveBench 1.0 Coding | LiveBench | – | 80.7% |
| SciCode (AA) | Artificial Analysis | 55.9% | 60.3% |
| IOI | Vals AI | – | 66.9% |
| Code Migration | Vals AI | 44.2% | 62.5% |
| Code Migration v1.1 | Vals AI | 67.5% | 72.4% |
| SWE-bench Multimodal | Vals AI | – | 45.6% |
| Vibe Code Bench 1-100 | Vals AI | – | 26.6% |
| Vibe Code Bench v1.1 | Vals AI | 87.7% | 83.1% |
Show all 96 benchmarks
| Metric | Publisher | DeepSeek V4.1 Flash 1017 (max) | Muse Wonder (max) |
|---|---|---|---|
| Coding | |||
| CursorBench | Cursor | – | 50.4% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 33.8% | 52.0% |
| FrontierCode 1.1 (AA) | Artificial Analysis | 43.7% | 46.5% |
| Agents & tools | |||
| Arena Agent | Arena (LMArena) | – | 3.3 |
| LiveBench Long Agentic | LiveBench | 50.9%† | 53.2%† |
| LiveBench Browser | LiveBench | 76.0%† | 72.0%† |
| LiveBench Agentic Coding | LiveBench | – | 62.7% |
| HiL-Bench | Scale AI SEAL | – | 79.7%† |
| GDPval-AA v2.1 | Artificial Analysis | 62.3% | 63.5% |
| CUA-bench | Vals AI | – | 7.2% |
| CyberBench | Vals AI | – | 80.4% |
| Finance Agent v2 | Vals AI | 57.0% | 56.6% |
| Finance Agent v2.1 | Vals AI | 62.9% | 65.5% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 14.2% | 23.8% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 9.2% | 17.1% |
| Legal Research Bench | Vals AI | 45.2% | 50.5% |
| Tax Agent Bench | Vals AI | 44.4% | 36.3% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 31.8% | 49.5% |
| Terminal-Bench Science | Vals AI | – | 22.9% |
| Vending-Bench 2 | Andon Labs | – | 9432.2† |
| AutomationBench | Artificial Analysis | 66.6% | 68.1% |
| GDP.pdf (AA) | Artificial Analysis | 17.2% | 30.6% |
| Harvey LAB-AA v1.1 | Harvey | – | 10.0% |
| AA-Briefcase v1.1 | Artificial Analysis | 1570 | 1659 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 12.9% | 25.7% |
| 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% | 82.1% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 46.3% | 70.7% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 99.4% | 99.4% |
| ProofBench | Vals AI | – | 84.0%† |
| LiveBench Mathematics | LiveBench | – | 96.5% |
| Arena Maths | Arena (LMArena) | – | 1496 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 42.5% | – |
| LiveBench 2.0 Data Analysis | LiveBench | 79.5%† | 81.6%† |
| LiveBench Research | LiveBench | 79.5%† | 88.0%† |
| LiveBench 1.0 Data Analysis | LiveBench | – | 81.6% |
| AA-Omniscience | Artificial Analysis | 4.7 | 25.5 |
| PRBench Finance | Scale AI SEAL | – | 58.7%† |
| PRBench Legal | Scale AI SEAL | – | 58.4%† |
| BioMysteryBench | Vals AI | – | 67.0% |
| Excel Modeling Benchmark | Vals AI | 61.8% | 67.1% |
| Excel Modeling Benchmark v1.1 | Vals AI | 69.2% | 72.5% |
| Public Benefits Bench v1.1 | Vals AI | – | 70.2% |
| EBR-bench | Epoch AI Benchmarking Hub | – | 31.4% |
| GDP.pdf | Epoch AI Benchmarking Hub | – | 30.8% |
| AA-Omniscience: accuracy | Artificial Analysis | 42.9% | 41.1% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 33.3% | 73.5% |
| Instruction following | |||
| LiveBench Language | LiveBench | – | 82.9% |
| LiveBench Instruction Following | LiveBench | – | 73.0% |
| Arena Instruction Following | Arena (LMArena) | – | 1498 |
| Human preference | |||
| Arena Text | Arena (LMArena) | – | 1509 |
| EQ-Bench 4 | EQ-Bench | – | 1324† |
| Arena Creative Writing | Arena (LMArena) | – | 1492 |
| Arena Multi-turn | Arena (LMArena) | – | 1519 |
| Arena Longer Queries | Arena (LMArena) | – | 1502 |
| Multimodal | |||
| LiveBench Design | LiveBench | 83.4%† | 75.1%† |
| MMMU-Pro | Artificial Analysis | 80.6% | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 82.7% | 80.7% |
| MLCR | Artificial Analysis | 26.7% | 22.2% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | – | 161.8† |
| LiveBench 2.0 | LiveBench | 79.2%† | 78.1%† |
| LiveBench 1.0 | LiveBench | – | 81.2% |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 45.1 | 52.4 |
| Vals Index | Vals AI | 61.3 | 64.9 |
| Vals Finance Index | Vals AI | 60.9% | 61.2% |
| Vals Science Index | Vals AI | – | 39.1% |
| Vals Router Index | Vals AI | 61.3%† | 64.9%† |
| 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
- DeepSeek V4.1 Flash 1017 (max): 10 new results (MLCR, AA Cyber Index, CWE-Bench (AA)…).
- Muse Wonder (max): 8 new results (MLCR, Code Migration v1.1, Excel Modeling Benchmark v1.1…).
- Muse Wonder (max): 2 new results (FrontierCode 1.1 (AA), Terminal-Bench-Science 0.1 (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…).
- Muse Wonder (max): 1 new result (Arena Maths); 2 score revisions.
- DeepSeek V4.1 Flash 1017 (max): 1 new result (FrontierCode 1.1 (AA)); 2 score revisions.
- Muse Wonder (max): 3 score revisions.
- Muse Wonder (max): BenchLeader Index 67.1 → 67.6.
- Muse Wonder (max): 1 new result (CursorBench).
Related comparisons
- 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
- Muse Wonder vs Claude Opus 5.5
- Muse Wonder vs Gemini 4 Argon
- Muse Wonder vs Muse Wonder Full
- Muse Wonder vs Claude Fable 5.1
- DeepSeek V4.1 Flash 1017 vs Muse Spark 1.3
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
DeepSeek V4.1 Flash 1017 vs Muse Wonder: questions
- Is DeepSeek V4.1 Flash 1017 better than Muse Wonder?
- DeepSeek V4.1 Flash 1017 (max) and Muse Wonder (max) are neck and neck on quality (64.0 vs 67.5, within the ±5.8 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 Muse Wonder, and will that change?
- DeepSeek V4.1 Flash 1017 is cheaper today: $0.525 against $8.00 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 Muse Wonder for coding?
- DeepSeek V4.1 Flash 1017 scores higher in coding (70 vs 66 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 1651 for Muse Wonder.
- Is DeepSeek V4.1 Flash 1017 better than Muse Wonder for agents and tool use?
- DeepSeek V4.1 Flash 1017 scores higher in agentic tasks (64 vs 56 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 65). Both accept 1,048,576 tokens of context.
- Which has lower latency?
- DeepSeek V4.1 Flash 1017 (max) answers first: 11.4 s against 40.3 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.
- Which is faster, DeepSeek V4.1 Flash 1017 or Muse Wonder?
- DeepSeek V4.1 Flash 1017 streams faster: 195 against 145 output tokens per second.
- Do independent benchmarks agree on DeepSeek V4.1 Flash 1017 vs Muse Wonder?
- Across the 33 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 7, Muse Wonder leads 25 and 1 is a tie. Every overall index that rates both puts Muse Wonder ahead.
- When was DeepSeek V4.1 Flash 1017 released?
- DeepSeek V4.1 Flash 1017 was released on 17 Oct 2026.