DeepSeek V4.1 Flash 1017 vs Muse Spark
Full profiles: DeepSeek V4.1 Flash 1017 (DeepSeek) and Muse Spark (Meta): every benchmark, price and rank.
Updated · Data from 8 sources
As of 25 Oct 2026, DeepSeek V4.1 Flash 1017 (max) and Muse Spark are neck and neck on quality (64.0 vs 64.3, inside the ±5.0 margin of error) and close on price, so pick on the category that matters to you. Pick DeepSeek V4.1 Flash 1017 for reasoning (71 vs 65); pick Muse Spark for knowledge (63 vs 57).
DeepSeek V4.1 Flash 1017 benchmarks max DeepSeek
Muse Spark benchmarks 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 65 category score; Vibe Code Bench v1.1 87.7% vs 19.7% | Medium |
| Agents & tool use | Muse Spark | 66 vs 64 category score | Medium |
| Maths | DeepSeek V4.1 Flash 1017 | 62 vs 59 category score; OTIS Mock AIME 99.4% vs 88.9% | Medium |
| Reasoning | DeepSeek V4.1 Flash 1017 | 71 vs 65 category score; GPQA Diamond 93.2% vs 89.8% | Medium |
| Knowledge | Muse Spark | 63 vs 57 category score; AA-Omniscience 7.2 vs 4.7 | Medium |
| Long documents | DeepSeek V4.1 Flash 1017 | 66 vs 64 category score; AA-LCR 82.7% vs 78.0% | Medium |
| Images and other media | Either | 64 vs 65 category score; MMMU-Pro 80.6% vs 80.5% | Either |
| Chat quality (human preference) | – | Only Muse Spark has an Arena rating (68 category score) | Not comparable |
| 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 Spark are neck and neck on quality (64.0 vs 64.3, within the ±5.0 margin).
- DeepSeek V4.1 Flash 1017 (max) is stronger in coding, composite, long context, maths, reasoning.
- Muse Spark is stronger in agents & tools, knowledge, multimodal, human preference, instruction following.
At a glance
| Spec | DeepSeek V4.1 Flash 1017 | Muse Spark |
|---|---|---|
| Developer | DeepSeek | Meta |
| Released | 17 Oct 2026 | 8 Apr 2026 |
| Context window (tokens) | 1,048,576 | 262,144 |
| Compared at | DeepSeek V4.1 Flash 1017 (max) | Muse Spark |
| Open weights | Yes | No |
| Price in / out / cached input per 1M | $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 | DeepSeek V4.1 Flash 1017 (max) | Muse Spark | Leader |
|---|---|---|---|
| Reasoning | 70.6 | 65.3 | DeepSeek V4.1 Flash 1017 |
| Coding | 69.9 | 65.0 | DeepSeek V4.1 Flash 1017 |
| Agents & tools | 63.5 | 66.1 | Muse Spark |
| Maths | 61.8 | 59.1 | DeepSeek V4.1 Flash 1017 |
| Knowledge | 57.1 | 63.3 | Muse Spark |
| Instruction following | – | 77.3 | not comparable |
| Human preference | – | 68.3 | not comparable |
| Multimodal | 63.7 | 64.5 | level |
| Long context | 66.4 | 64.0 | DeepSeek V4.1 Flash 1017 |
| Composite | 80.0 | 64.5 | DeepSeek V4.1 Flash 1017 |
Where sources disagree
Across the 10 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 8, Muse Spark leads 2. Every overall index that rates both puts DeepSeek V4.1 Flash 1017 ahead.
| Overall index | DeepSeek V4.1 Flash 1017 (max) | Muse Spark | Leader |
|---|---|---|---|
| BenchLeader Index | 64.0 | 64.3 | neck and neck |
| AA Intelligence Index v4.3.2 | 45.1 | 31.3 | 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 | DeepSeek V4.1 Flash 1017 (max) | Muse Spark |
|---|---|---|
| Blended price per 1M tokens | $0.525 | – |
| Input / output per 1M | $0.300 / $1.20 | – / – |
| Cached input per 1M | $0.0060 | – |
| Price per task: chat reply | $0.0005 | – |
| Price per task: summarize a 30-page report | $0.0043 | – |
| Price per task: code edit | $0.0036 | – |
| Price per task: agentic coding session | $0.023 | – |
| Price per task: structured extraction | $0.0008 | – |
| Cost to run a full benchmark suite | $0.262 | – |
| Output speed | 195 tok/s | – |
| Time to first answer | 11.4 s | – |
| Time to a complete answer | 13.9 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. Muse Spark scores 64.3. 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
98 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 Spark |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 64.0 | 64.3 |
| Agents & tools score | BenchLeader | 63.5 | 66.1 |
| Coding score | BenchLeader | 69.9 | 65.0 |
| Composite score | BenchLeader | 80.0 | 64.5 |
| Knowledge score | BenchLeader | 57.1 | 63.3 |
| Long context score | BenchLeader | 66.4 | 64.0 |
| Maths score | BenchLeader | 61.8 | 59.1 |
| Multimodal score | BenchLeader | 63.7 | 64.5 |
| Reasoning score | BenchLeader | 70.6 | 65.3 |
| Human preference score | BenchLeader | – | 68.3 |
| Instruction following score | BenchLeader | – | 77.3 |
| Blended price $/M | BenchLeader | $0.525 | – |
| Output speed | BenchLeader | 195 tok/s | – |
| Time to first answer | BenchLeader | 11.4 s | – |
| Context window | BenchLeader | 1,048,576 tokens | 262,144 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 93.2% | 89.8% |
| Humanity's Last Exam | Scale AI / CAIS | – | 40.6% |
| Arena Hard Prompts | Arena (LMArena) | – | 1506 |
| LiveBench 2.0 Reasoning | LiveBench | 89.1%† | – |
| GPQA Diamond (AA) | Artificial Analysis | – | 88.4% |
| Humanity's Last Exam (AA) | Artificial Analysis | 43.3% | 40.7% |
| GPQA Diamond (Vals) | Vals AI | – | 89.7% |
| ARC-AGI-1 | ARC Prize | 93.5% | – |
| ARC-AGI-2 | ARC Prize | 78.1% | – |
| CritPt | Artificial Analysis | 24.0% | 11.3% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 46.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 49.0% | – |
| Coding | |||
| SciCode | SciCode | – | 51.5% |
| Arena Coding | Arena (LMArena) | – | 1529 |
| Arena WebDev | Arena (LMArena) | 1665 | – |
| LiveBench 2.0 Coding | LiveBench | 96.0%† | – |
| SciCode (AA) | Artificial Analysis | 55.9% | – |
| SWE-bench (Vals) | Vals AI | – | 74.4% |
| SWE-Bench Pro | Scale AI SEAL | – | 55.0% |
| Code Migration | Vals AI | 44.2% | – |
| Code Migration v1.1 | Vals AI | 67.5% | – |
| Vibe Code Bench v1.1 | Vals AI | 87.7% | 19.7% |
| SWE-Bench Pro (private) | Scale AI SEAL | – | 55.0% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | – | 24.2% |
| SWE Atlas: Test Writing | Scale AI SEAL | – | 31.1% |
Show all 98 benchmarks
| Metric | Publisher | DeepSeek V4.1 Flash 1017 (max) | Muse Spark |
|---|---|---|---|
| Coding | |||
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 33.8% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | – | 62.2% |
| FrontierCode 1.1 (AA) | Artificial Analysis | 43.7% | – |
| Agents & tools | |||
| LiveBench Long Agentic | LiveBench | 50.9%† | – |
| LiveBench Browser | LiveBench | 76.0%† | – |
| Terminal-Bench Hard | Artificial Analysis | – | 45.5% |
| τ²-Bench Telecom (AA) | Artificial Analysis | – | 91.5% |
| MCP Atlas | Scale AI SEAL | – | 82.2% |
| GDPval-AA v2.1 | Artificial Analysis | 62.3% | – |
| Finance Agent v2 | Vals AI | 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 | 9.2% | – |
| Legal Research Bench | Vals AI | 45.2% | – |
| Tax Agent Bench | Vals AI | 44.4% | – |
| Terminal-Bench 2.0 (Vals) | Vals AI | – | 59.5% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 31.8% | – |
| AutomationBench | Artificial Analysis | 66.6% | – |
| GDP.pdf (AA) | Artificial Analysis | 17.2% | – |
| 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% | – |
| 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% | 88.9% |
| ProofBench | Vals AI | – | 17.0% |
| AIME (Vals) | Vals AI | – | 96.9% |
| Arena Maths | Arena (LMArena) | – | 1467 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 42.5% | – |
| LiveBench 2.0 Data Analysis | LiveBench | 79.5%† | – |
| LiveBench Research | LiveBench | 79.5%† | – |
| AA-Omniscience | Artificial Analysis | 4.7 | 7.2 |
| MMLU-Pro | Vals AI | – | 87.3% |
| LegalBench | Vals AI | – | 84.2% |
| CorpFin | Vals AI | – | 65.1% |
| TaxEval | Vals AI | – | 77.7% |
| PRBench Finance | Scale AI SEAL | – | 52.4% |
| PRBench Legal | Scale AI SEAL | – | 52.3% |
| MultiNRC | Scale AI SEAL | – | 59.0% |
| CaseLaw v2 | Vals AI | – | 63.1% |
| Excel Modeling Benchmark | Vals AI | 61.8% | – |
| Excel Modeling Benchmark v1.1 | Vals AI | 69.2% | – |
| MedCode | Vals AI | – | 51.3% |
| MedScribe | Vals AI | – | 85.9% |
| AA-Omniscience: accuracy | Artificial Analysis | 42.9% | 49.6% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 33.3% | 15.8% |
| Instruction following | |||
| IFBench | Artificial Analysis | – | 75.9% |
| MultiChallenge | Scale AI SEAL | – | 75.5% |
| TutorBench | Scale AI SEAL | – | 68.5% |
| Arena Instruction Following | Arena (LMArena) | – | 1465 |
| Human preference | |||
| Arena Text | Arena (LMArena) | – | 1489 |
| Arena Creative Writing | Arena (LMArena) | – | 1464 |
| Arena Multi-turn | Arena (LMArena) | – | 1494 |
| Arena Longer Queries | Arena (LMArena) | – | 1476 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | – | 1306 |
| LiveBench Design | LiveBench | 83.4%† | – |
| MMMU-Pro | Artificial Analysis | 80.6% | 80.5% |
| MMMU-Pro (official) | MMMU | – | 80.4%† |
| MMMU-Pro (Vals) | Vals AI | – | 87.4% |
| Long context | |||
| AA-LCR | Artificial Analysis | 82.7% | 78.0% |
| Arena Document | Arena (LMArena) | – | 1467 |
| MLCR | Artificial Analysis | 26.7% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | – | 152.0 |
| LiveBench 2.0 | LiveBench | 79.2%† | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 45.1 | 31.3 |
| Vals Index | Vals AI | 61.3 | – |
| Vals Finance Index | Vals AI | 60.9% | – |
| Vals Router Index | Vals AI | 61.3%† | – |
| AA Cyber Index | Artificial Analysis | 56.8 | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | – | 20.2% |
| 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)…).
- 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.
- Muse Spark: 1 new result (PRBench Legal).
- Muse Spark: 1 new result (SWE Atlas: Codebase QnA).
- Muse Spark: 2 new results (PRBench Legal, MultiNRC).
- Muse Spark: 1 new result (PRBench Finance).
- Muse Spark: 1 new result (PRBench Finance).
- Muse Spark: 1 new result (TutorBench); 1 score revision.
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 Spark vs Claude Opus 5.5
- Muse Spark vs Gemini 4 Argon
- Muse Spark vs Muse Wonder Full
- Muse Spark vs Claude Fable 5.1
- DeepSeek V4.1 Flash 1017 vs GPT-6 Astra
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
DeepSeek V4.1 Flash 1017 vs Muse Spark: questions
- Is DeepSeek V4.1 Flash 1017 better than Muse Spark?
- DeepSeek V4.1 Flash 1017 (max) and Muse Spark are neck and neck on quality (64.0 vs 64.3, within the ±5.0 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.
- Is DeepSeek V4.1 Flash 1017 better than Muse Spark for coding?
- DeepSeek V4.1 Flash 1017 scores higher in coding (70 vs 65 on the category index, where 50 is average).
- Is DeepSeek V4.1 Flash 1017 better than Muse Spark for agents and tool use?
- Muse Spark scores higher in agentic tasks (66 vs 64 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). DeepSeek V4.1 Flash 1017 accepts more context: 1,048,576 against 262,144 tokens for Muse Spark.
- Do independent benchmarks agree on DeepSeek V4.1 Flash 1017 vs Muse Spark?
- Across the 10 benchmarks both have, DeepSeek V4.1 Flash 1017 leads 8, Muse Spark leads 2. 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.