DeepSeek V4.1 Flash vs Mistral Large 2407
DeepSeek V4.1 Flash leads Mistral Large 2407 on the Artificial Analysis Intelligence Index, 24.7 to 7.6, and DeepSeek V4.1 Flash costs 7.7x less per output token ($0.78 vs $6.00 per million). Updated October 21, 2026; 6 benchmarks have a result for both.
vs boards won of 6 shared
DeepSeek V4.1 Flash or Mistral Large 2407: which to pick
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; Mistral Large 2407 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
Model ADeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved taskModel BMistral Large 2407Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 6
- DeepSeek V4.1 Flash only
- 95
- Mistral Large 2407 only
- 11
- Like-for-like categories
- 4 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only DeepSeek V4.1 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 24.7 against 7.6.
Same board, both measured
Web design
Design Arena: websites
No call
Only DeepSeek V4.1 Flash has a Design Arena: websites result, 1309.
Directional only
Long documents
Listed context window
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash $0.0006, Mistral Large 2407 $0.0050 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4.1 Flash 62.5 from 5 benchmarks, Mistral Large 2407 not benchmarked.
- Widest category
- Math, 89.9 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: DeepSeek V4.1 Flash 98.3% against Mistral Large 2407 8.5%, 89.9 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.78 against Mistral Large 2407 $6.00 per million output tokens, 7.7x apart.
- Context window
- DeepSeek V4.1 Flash takes 1.05M tokens, Mistral Large 2407 131K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | DeepSeek V4.1 Flash | Bars | Mistral Large 2407 | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Math | 1 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 6 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index21 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | 84.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Code migration (Vals AI) | 45.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IOI (Vals AI) | 40.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| SWE-bench Multimodal (Vals AI) | 46.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | 16.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| SkillsBench (Vals AI) | 69.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 26.7% | Only Mistral Large 2407 measured |
| SciCode | 51.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: coding | 1502 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: software and IT | 1496 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: React | 1628 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: HTML | 1612 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev: from an image | 1606 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 7.6 | DeepSeek V4.1 Flash |
| Epoch Capabilities Index | 155.9 | Not measured | Only DeepSeek V4.1 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| LiveBench research | 86.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench browser | 84.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench long agentic | 40.1% | Not measured | Only DeepSeek V4.1 Flash measured |
| SREBench (Vals AI) | 0.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | 53.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Tax Agent Bench (Vals AI) | 26.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| Legal Research Bench (Vals AI) | 41.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 57.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| BioMysteryBench (Vals AI) | 67.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vals Science Index | 29.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| τ²-Bench Telecom | Not measured | 33.0% | Only Mistral Large 2407 measured |
| APEX-Agents | 39.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| LiveBench reasoning | 86.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| MysteryMechanism (Vals AI) | 21.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 47.2% | Only Mistral Large 2407 measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 2.9% | DeepSeek V4.1 Flash |
| GPQA Diamond (Epoch AI run) | 89.8% | 49.0% | DeepSeek V4.1 Flash |
| ARC-AGI | 94.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI-2 | 72.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| SimpleBench | Not measured | 22.5% | Only Mistral Large 2407 measured |
| Chess puzzles | 48.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Mystery game puzzles | 43.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts | 1483 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: expert | 1501 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts in English | 1488 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: diagrams | 1297 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: homework | 1307 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 0.0 | Only Mistral Large 2407 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 0.0% | Only Mistral Large 2407 measured |
| OTIS Mock AIME | 98.3% | 8.5% | DeepSeek V4.1 Flash |
| FrontierMath, tiers 1 to 3 | 67.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProofBench | 54.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| MATH level 5 | Not measured | 44.8% | Only Mistral Large 2407 measured |
| LMArena Text: math | 1478 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: mathematical work | 1485 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedCode (Vals AI) | 41.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 68.3% | Only Mistral Large 2407 measured |
| SimpleQA Verified | 42.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| MMLU | Not measured | 80.0% | Only Mistral Large 2407 measured |
| LMArena Text: science | 1469 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: medicine and healthcare | 1484 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: legal and government | 1443 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: business and finance | 1461 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| Design Arena: websites | 1309 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: UI components | 1315 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: game dev | 1330 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: data viz | 1290 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: 3D | 1356 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: all code categories | 1320 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: SVG | 1244 | Not measured | Only DeepSeek V4.1 Flash measured |
| Design Arena: ASCII art | 1265 | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench design | 79.2% | Not measured | Only DeepSeek V4.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Public Benefits Bench (Vals AI) | 64.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| SAGE (Vals AI) | 47.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedScribe (Vals AI) | 85.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| IFBench | Not measured | 31.6% | Only Mistral Large 2407 measured |
| Long context reasoning (AA-LCR) | 84.0% | 2.0% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | 61.2% | DeepSeek V4.1 Flash |
| LMCA | 47.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Creative writing (Lech Mazur) | Not measured | 69.0% | Only Mistral Large 2407 measured |
| Surface Evolver Bench | 46.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Furniture assembly | 34.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text | 1464 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: instruction following | 1473 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: creative writing | 1437 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision | 1278 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: English | 1473 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: non-English | 1449 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Chinese | 1501 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: German | 1470 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Japanese | 1432 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Korean | 1436 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: French | 1465 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Spanish | 1459 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Russian | 1467 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: Polish | 1457 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: multi-turn | 1461 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: longer queries | 1473 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: writing and language | 1450 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: entertainment and media | 1445 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: English | 1288 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: Chinese | 1327 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: reading text | 1282 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: humor | 1260 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Vision: creative writing | 1275 | Not measured | Only DeepSeek V4.1 Flash measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Mistral Large 2407 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
DeepSeek V4.1 Flash$0.0006Fits in one request
Mistral Large 2407$0.0050Fits in one request
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash$0.013Fits in one request
Mistral Large 2407$0.118Fits in one request
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash$0.050Fits in one request
Mistral Large 2407$0.460Exceeds the context window
DeepSeek V4.1 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | DeepSeek V4.1 Flash | Mistral Large 2407 |
|---|---|---|
| Maker | DeepSeek | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | November 19, 2024 |
| Context window | 1.05M | 131K |
| Input $/Mtok | $0.21 | $2.00 |
| Output $/Mtok | $0.78 | $6.00 |
| Coding index | 62.5 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than Mistral Large 2407 for coding?
Only DeepSeek V4.1 Flash has a coding score, 62.5 on the Vibe Coding Index; Mistral Large 2407 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, DeepSeek V4.1 Flash or Mistral Large 2407?
DeepSeek V4.1 Flash costs $0.21 per million input tokens and $0.78 per million output tokens; Mistral Large 2407 costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4.1 Flash or Mistral Large 2407?
DeepSeek V4.1 Flash, with 1.05M tokens against 131K.
How many benchmarks is the DeepSeek V4.1 Flash vs Mistral Large 2407 comparison based on?
6 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4.1 Flash's coding index rests on 5 independent benchmarks and Mistral Large 2407's on 0. Where only one model has a result, the page says so instead of naming a winner.