DeepSeek-V4.1-Flash vs Muse Spark Open
Wins 2 of 7 areas
Agents · Long documents
Wins 3 of 7 areas
Facts · Images and charts · Math
Muse Spark Open wins more areas, narrowly.DeepSeek-V4.1-Flash is cheaper and better at agents.
Scores updated · 16 tests both models report · How we compare
Where each one wins
Tests won in each of the seven areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- MathCompetition and research-level math02Muse Spark Open2 of 2 tests
- FactsGetting facts right instead of making them up12Muse Spark Open2 of 3 tests
- Images and chartsUnderstanding pictures, charts and video01Muse Spark Open1 of 1 test
- AgentsCarrying out multi-step tasks on its own20DeepSeek-V4.1-Flash2 of 2 tests
- Long documentsFinding answers in very long texts10DeepSeek-V4.1-Flash1 of 1 test
- CodingWriting and fixing software11Even1 each
- ReasoningHard problems that need careful thinking11Even1 each · 1 tie
Images and charts and long documents rest on a single test each.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
DeepSeek-V4.1-Flash costs 73% less for the same work.
The biggest differences
The three tests each model wins by the widest margin. Scores are out of 100.
Where Muse Spark Open pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+72.4points ahead
- Short factual questions, answered correctlySimpleQA Verified+13.7points ahead
- Code for real scientific research problemsSciCode+6.5points ahead
Where DeepSeek-V4.1-Flash pulls ahead
- Complex command-line tasks across many fieldsTerminal-Bench 4.0+18.7points ahead
- Command-line tasks in a real terminalTerminal-Bench 2.1+14.2points ahead
- Real work tasks from 44 professionsGDPVal+9.9points ahead
Every test, side by side
All 16 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingEven
- Terminal-Bench 2.1DeepSeek-V4.1-Flash by 14.290.676.4+14.2
- SciCodeMuse Spark Open by 6.551.958.4+6.5
AgentsDeepSeek-V4.1-Flash
- Terminal-Bench 4.0DeepSeek-V4.1-Flash by 18.726.88.1+18.7
- GDPValDeepSeek-V4.1-Flash by 9.95545.1+9.9
ReasoningEven
- Humanity's Last ExamMuse Spark Open by 4.739.243.9+4.7
- GPQA DiamondDeepSeek-V4.1-Flash by 1.990.989+1.9
- CritPttie14.314.9tie
FactsMuse Spark Open
- AA-Omniscience · Non-hallucinationMuse Spark Open by 72.43.575.9+72.4
- SimpleQA VerifiedMuse Spark Open by 13.742.956.6+13.7
- AA-Omniscience · AccuracyDeepSeek-V4.1-Flash by 7.146.439.3+7.1
Images and chartsMuse Spark Open
- MMMU-ProMuse Spark Open by 3.97780.9+3.9
MathMuse Spark Open
- FrontierMath Tier 4Muse Spark Open by 4.926.831.7+4.9
- FrontierMath Tiers 1-3 (v2)Muse Spark Open by 2.467.469.8+2.4
Long documentsDeepSeek-V4.1-Flash
- AA-LCRDeepSeek-V4.1-Flash by 5.78478.3+5.7
Other results2 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- AA-OmniscienceMuse Spark Open by 30-5.324.6+30
- AA Intelligencetie39.538.9tie
Questions people ask
Which is better, DeepSeek-V4.1-Flash or Muse Spark Open?
Muse Spark Open wins three of the seven areas where both have results: facts, images and charts and math. DeepSeek-V4.1-Flash wins agents and long documents, and costs 73% less. They are level on coding and reasoning.
Which is better for coding?
Neither. They win 1 coding test each of the 2 both models report.
Which is cheaper?
DeepSeek-V4.1-Flash costs $0.30 per million input tokens and $1.20 per million output tokens; Muse Spark Open costs $1.25 and $4.25. That makes DeepSeek-V4.1-Flash about 73% cheaper for the same work.
How do you compare the two?
We use the 16 benchmark tests both models have published scores on. The verdict counts the 14 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 2 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.