DeepSeek V4.1 Flash 1017 vs Mistral Large 4
Updated October 21, 2026. 30 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick DeepSeek V4.1 Flash 1017 for coding: it scores 83.3 on the Vibe Coding Index against 55.3 for Mistral Large 4.
Pick Mistral Large 4 when the benchmark that matters is Harvey's Legal Agent Benchmark (Vals AI), where it leads.
- Shared results
- 30
- DeepSeek V4.1 Flash 1017 only
- 2
- Mistral Large 4 only
- 51
- Like-for-like categories
- 6 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 scores 83.3 against 55.3.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads, 39.5 against 38.4.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads, 1312 against 1258.
Same board, both measured
General
Vals Index
No call
Only DeepSeek V4.1 Flash 1017 has a Vals Index result, 61.3%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 $0.0004, Mistral Large 4 $0.0034 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4.1 Flash 1017 83.3 from 2 benchmarks, Mistral Large 4 55.3 from 2 benchmarks.
- Widest category
- Agentic work, 24.6 points apart on average over 8 shared benchmarks.
- Widest single gap
- LiveBench browser: DeepSeek V4.1 Flash 1017 76.0% against Mistral Large 4 8.0%, 68.0 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash 1017 $0.60 against Mistral Large 4 $4.18 per million output tokens, 7.0x apart.
- Context window
- Both take 1.05M tokens.
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 1017 | Bars | Mistral Large 4 | Ties |
|---|---|---|---|---|
| Coding | 9 | 0 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 7 | 1 | ||
| Reasoning | 2 | 0 | ||
| Web design | 8 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 29 | 1 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index90
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench coding | 96.0% | 60.0% | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev | 1664 | 1543 | DeepSeek V4.1 Flash 1017 |
| Terminal-Bench 4 (Vals AI) | 31.8% | 27.8% | DeepSeek V4.1 Flash 1017 |
| Vibe Code Bench (Vals AI) | 87.7% | 78.4% | DeepSeek V4.1 Flash 1017 |
| Code migration (Vals AI) | 44.2% | 30.6% | DeepSeek V4.1 Flash 1017 |
| IOI (Vals AI) | Not measured | 45.3% | Only Mistral Large 4 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 33.1% | Only Mistral Large 4 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 14.3% | Only Mistral Large 4 measured |
| SciCode | 55.9% | 54.2% | DeepSeek V4.1 Flash 1017 |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| ALE-Bench | 1622.0 | 1213.2 | DeepSeek V4.1 Flash 1017 |
| LMArena Text: coding | Not measured | 1478 | Only Mistral Large 4 measured |
| LMArena Text: software and IT | Not measured | 1467 | Only Mistral Large 4 measured |
| LMArena WebDev: React | 1667 | 1559 | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev: HTML | 1687 | 1487 | DeepSeek V4.1 Flash 1017 |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.5 | 38.4 | DeepSeek V4.1 Flash 1017 |
| Epoch Capabilities Index | Not measured | 150.0 | Only Mistral Large 4 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | 1238 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench research | 79.5% | 28.1% | DeepSeek V4.1 Flash 1017 |
| LiveBench browser | 76.0% | 8.0% | DeepSeek V4.1 Flash 1017 |
| LiveBench long agentic | 50.9% | 11.8% | DeepSeek V4.1 Flash 1017 |
| Finance Agent (Vals AI) | 57.0% | 54.7% | DeepSeek V4.1 Flash 1017 |
| Tax Agent Bench (Vals AI) | 44.4% | 30.4% | DeepSeek V4.1 Flash 1017 |
| Legal Research Bench (Vals AI) | 45.2% | 31.7% | DeepSeek V4.1 Flash 1017 |
| Harvey's Legal Agent Benchmark (Vals AI) | 14.2% | 17.5% | Mistral Large 4 |
| Excel Modeling Benchmark (Vals AI) | 61.8% | 56.2% | DeepSeek V4.1 Flash 1017 |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Mistral Large 4 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench reasoning | 89.1% | 83.9% | DeepSeek V4.1 Flash 1017 |
| MysteryMechanism (Vals AI) | Not measured | 12.2% | Only Mistral Large 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.3% | 35.0% | DeepSeek V4.1 Flash 1017 |
| GPQA Diamond (Epoch AI run) | Not measured | 88.1% | Only Mistral Large 4 measured |
| Chess puzzles | Not measured | 33.0% | Only Mistral Large 4 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | Not measured | 1444 | Only Mistral Large 4 measured |
| LMArena Text: expert | Not measured | 1444 | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | Not measured | 1442 | Only Mistral Large 4 measured |
| LMArena Vision: diagrams | Not measured | 1288 | Only Mistral Large 4 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 98.3% | Only Mistral Large 4 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 58.6% | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | Not measured | 26.8% | Only Mistral Large 4 measured |
| ProofBench | Not measured | 10.0% | Only Mistral Large 4 measured |
| LMArena Text: math | Not measured | 1469 | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | Not measured | 1462 | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 40.7% | Only Mistral Large 4 measured |
| SimpleQA Verified | Not measured | 20.0% | Only Mistral Large 4 measured |
| LMArena Text: science | Not measured | 1448 | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1433 | Only Mistral Large 4 measured |
| LMArena Text: legal and government | Not measured | 1425 | Only Mistral Large 4 measured |
| LMArena Text: business and finance | Not measured | 1439 | Only Mistral Large 4 measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1312 | 1258 | DeepSeek V4.1 Flash 1017 |
| Design Arena: UI components | 1305 | 1275 | DeepSeek V4.1 Flash 1017 |
| Design Arena: game dev | 1365 | 1226 | DeepSeek V4.1 Flash 1017 |
| Design Arena: data viz | 1330 | 1274 | DeepSeek V4.1 Flash 1017 |
| Design Arena: 3D | 1368 | 1253 | DeepSeek V4.1 Flash 1017 |
| Design Arena: all code categories | 1335 | 1259 | DeepSeek V4.1 Flash 1017 |
| Design Arena: SVG | Not measured | 1232 | Only Mistral Large 4 measured |
| Design Arena: ASCII art | 1244 | 1203 | DeepSeek V4.1 Flash 1017 |
| LiveBench design | 83.4% | 65.6% | DeepSeek V4.1 Flash 1017 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | Leader |
|---|---|---|---|
| Vals Index | 61.3% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench data analysis | 79.5% | 76.5% | DeepSeek V4.1 Flash 1017 |
| MedScribe (Vals AI) | Not measured | 80.4% | Only Mistral Large 4 measured |
| Long context reasoning (AA-LCR) | 82.7% | 81.3% | DeepSeek V4.1 Flash 1017 |
| DTBench | Not measured | 88.2% | Only Mistral Large 4 measured |
| LMCA | Not measured | 35.8% | Only Mistral Large 4 measured |
| Surface Evolver Bench | Not measured | 28.1% | Only Mistral Large 4 measured |
| Furniture assembly | Not measured | 20.8% | Only Mistral Large 4 measured |
| LMArena Text | Not measured | 1431 | Only Mistral Large 4 measured |
| LMArena Text: instruction following | Not measured | 1422 | Only Mistral Large 4 measured |
| LMArena Text: creative writing | Not measured | 1363 | Only Mistral Large 4 measured |
| LMArena Vision | Not measured | 1272 | Only Mistral Large 4 measured |
| LMArena Text: English | Not measured | 1433 | Only Mistral Large 4 measured |
| LMArena Text: non-English | Not measured | 1422 | Only Mistral Large 4 measured |
| LMArena Text: Chinese | Not measured | 1492 | Only Mistral Large 4 measured |
| LMArena Text: Japanese | Not measured | 1415 | Only Mistral Large 4 measured |
| LMArena Text: French | Not measured | 1492 | Only Mistral Large 4 measured |
| LMArena Text: Spanish | Not measured | 1455 | Only Mistral Large 4 measured |
| LMArena Text: Russian | Not measured | 1417 | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | Not measured | 1435 | Only Mistral Large 4 measured |
| LMArena Text: longer queries | Not measured | 1428 | Only Mistral Large 4 measured |
| LMArena Text: writing and language | Not measured | 1386 | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | Not measured | 1378 | Only Mistral Large 4 measured |
| LMArena Vision: English | Not measured | 1283 | Only Mistral Large 4 measured |
| LMArena Vision: reading text | Not measured | 1284 | Only Mistral Large 4 measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Mistral Large 4 | 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 1017 costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash 1017 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash 1017 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 1017 | Mistral Large 4 |
|---|---|---|
| Maker | DeepSeek | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | October 17, 2026 | October 6, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.15 | $1.36 |
| Output $/Mtok | $0.60 | $4.18 |
| Coding index | 83.3 | 55.3 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash 1017 better than Mistral Large 4 for coding?
Pick DeepSeek V4.1 Flash 1017 for coding: it scores 83.3 on the Vibe Coding Index against 55.3 for Mistral Large 4. Pick Mistral Large 4 when the benchmark that matters is Harvey's Legal Agent Benchmark (Vals AI), where it leads.
Which is cheaper, DeepSeek V4.1 Flash 1017 or Mistral Large 4?
DeepSeek V4.1 Flash 1017 costs $0.15 per million input tokens and $0.60 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4.1 Flash 1017 or Mistral Large 4?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4.1 Flash 1017 vs Mistral Large 4 comparison based on?
30 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4.1 Flash 1017's coding index rests on 2 independent benchmarks and Mistral Large 4's on 2. Where only one model has a result, the page says so instead of naming a winner.