DeepSeek V3.2 vs Mistral Large 4
Updated October 21, 2026. 43 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
DeepSeek V3.2 and Mistral Large 4 are level for coding, 54.4 against 55.3 on the Vibe Coding Index, so price and context decide.
Pick DeepSeek V3.2 when output tokens cost 10.0x less, or when what matters is LMArena Text: hard prompts in English or LMArena Text: medicine and healthcare, where it leads. Pick Mistral Large 4 when the context window is larger, 1.05M against 164K tokens, or when what matters is LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
- Shared results
- 43
- DeepSeek V3.2 only
- 32
- Mistral Large 4 only
- 38
- Like-for-like categories
- 7 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
No call
Level: 54.4 against 55.3, inside 2 points.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 21.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only DeepSeek V3.2 has a GPQA Diamond result, 80.3%.
Directional only
Math
AIME
No call
Only DeepSeek V3.2 has a AIME result, 84.6%.
Directional only
Knowledge
MMLU Pro
No call
Only DeepSeek V3.2 has a MMLU Pro result, 84.9%.
Directional only
Web design
Design Arena: websites
Mistral Large 4
Mistral Large 4 leads, 1258 against 1175.
Same board, both measured
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3.2
DeepSeek V3.2 $0.0005, Mistral Large 4 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only DeepSeek V3.2 has the number, $0.99.
Directional only
At a glance
- Coding index
- DeepSeek V3.2 54.4 from 2 benchmarks, Mistral Large 4 55.3 from 2 benchmarks.
- Widest category
- Coding, 26.7 points apart on average over 6 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): DeepSeek V3.2 5.1% against Mistral Large 4 78.4%, 73.3 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.2 $0.42 against Mistral Large 4 $4.18 per million output tokens, 10.0x apart.
- Context window
- DeepSeek V3.2 takes 164K tokens, Mistral Large 4 1.05M.
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 V3.2 | Bars | Mistral Large 4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 1 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 2 | 2 | ||
| Web design | 0 | 8 | ||
| General | 5 | 12 | ||
| All shared boards | 8 | 35 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index06
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| SWE-bench Verified | 70.0% | Not measured | Only DeepSeek V3.2 measured |
| SWE-bench Multilingual | 59.0% | Not measured | Only DeepSeek V3.2 measured |
| LiveBench coding | Not measured | 60.0% | Only Mistral Large 4 measured |
| LMArena WebDev | 1362 | 1543 | Mistral Large 4 |
| AA Coding Index | 44.2 | Not measured | Only DeepSeek V3.2 measured |
| LiveCodeBench (Vals AI) | 80.7% | Not measured | Only DeepSeek V3.2 measured |
| SWE-bench Verified (Vals AI) | 67.6% | Not measured | Only DeepSeek V3.2 measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 27.8% | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 5.1% | 78.4% | Mistral Large 4 |
| Code migration (Vals AI) | Not measured | 30.6% | Only Mistral Large 4 measured |
| 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 |
| LiveCodeBench (Artificial Analysis run) | 86.2% | Not measured | Only DeepSeek V3.2 measured |
| SciCode | Not measured | 54.2% | Only Mistral Large 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 35.6% | Not measured | Only DeepSeek V3.2 measured |
| Terminal-Bench | 39.6% | Not measured | Only DeepSeek V3.2 measured |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| ALE-Bench | Not measured | 1213.2 | Only Mistral Large 4 measured |
| LMArena Text: coding | 1453 | 1478 | Mistral Large 4 |
| LMArena Text: software and IT | 1449 | 1467 | Mistral Large 4 |
| LMArena WebDev: React | 1350 | 1559 | Mistral Large 4 |
| LMArena WebDev: HTML | 1371 | 1487 | Mistral Large 4 |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.5 | 38.4 | Mistral Large 4 |
| Epoch Capabilities Index | 146.1 | 150.0 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 28.1% | Only Mistral Large 4 measured |
| LiveBench browser | Not measured | 8.0% | Only Mistral Large 4 measured |
| LiveBench long agentic | Not measured | 11.8% | Only Mistral Large 4 measured |
| Finance Agent (Vals AI) | Not measured | 54.7% | Only Mistral Large 4 measured |
| Tax Agent Bench (Vals AI) | Not measured | 30.4% | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | Not measured | 31.7% | Only Mistral Large 4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 17.5% | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 56.2% | Only Mistral Large 4 measured |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Mistral Large 4 measured |
| τ²-Bench Telecom | 90.6% | Not measured | Only DeepSeek V3.2 measured |
| APEX-Agents | 21.3% | Not measured | Only DeepSeek V3.2 measured |
| Vending-Bench 2 | $1,034 | Not measured | Only DeepSeek V3.2 measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| GPQA Diamond | 80.3% | Not measured | Only DeepSeek V3.2 measured |
| LiveBench reasoning | Not measured | 83.9% | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | Not measured | 12.2% | Only Mistral Large 4 measured |
| GPQA Diamond (Artificial Analysis run) | 84.0% | Not measured | Only DeepSeek V3.2 measured |
| Humanity's Last Exam (Artificial Analysis run) | 24.6% | 35.0% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | Not measured | 88.1% | Only Mistral Large 4 measured |
| ARC-AGI | 57.0% | Not measured | Only DeepSeek V3.2 measured |
| ARC-AGI-2 | 4.0% | Not measured | Only DeepSeek V3.2 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 | 1434 | 1444 | Mistral Large 4 |
| LMArena Text: expert | 1436 | 1444 | Mistral Large 4 |
| LMArena Text: hard prompts in English | 1446 | 1442 | DeepSeek V3.2 |
| LMArena Vision: diagrams | Not measured | 1288 | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| AIME | 84.6% | Not measured | Only DeepSeek V3.2 measured |
| MGSM (Vals AI) | 86.0% | Not measured | Only DeepSeek V3.2 measured |
| AA Math Index | 92.0 | Not measured | Only DeepSeek V3.2 measured |
| AIME 2025 (Artificial Analysis run) | 92.0% | Not measured | Only DeepSeek V3.2 measured |
| 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 | 1435 | 1469 | Mistral Large 4 |
| LMArena Text: mathematical work | 1440 | 1462 | Mistral Large 4 |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| MMLU Pro | 84.9% | Not measured | Only DeepSeek V3.2 measured |
| LegalBench (Vals AI) | 76.1% | Not measured | Only DeepSeek V3.2 measured |
| CaseLaw (Vals AI) | 55.4% | Not measured | Only DeepSeek V3.2 measured |
| CorpFin (Vals AI) | 51.0% | Not measured | Only DeepSeek V3.2 measured |
| TaxEval (Vals AI) | 68.2% | Not measured | Only DeepSeek V3.2 measured |
| MedQA (Vals AI) | 93.9% | Not measured | Only DeepSeek V3.2 measured |
| MedCode (Vals AI) | Not measured | 40.7% | Only Mistral Large 4 measured |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only DeepSeek V3.2 measured |
| SimpleQA Verified | Not measured | 20.0% | Only Mistral Large 4 measured |
| LMArena Text: science | 1446 | 1448 | Mistral Large 4 |
| LMArena Text: medicine and healthcare | 1440 | 1433 | DeepSeek V3.2 |
| LMArena Text: legal and government | 1425 | 1425 | DeepSeek V3.2 |
| LMArena Text: business and finance | 1410 | 1439 | Mistral Large 4 |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1175 | 1258 | Mistral Large 4 |
| Design Arena: UI components | 1149 | 1275 | Mistral Large 4 |
| Design Arena: game dev | 1132 | 1226 | Mistral Large 4 |
| Design Arena: data viz | 1158 | 1274 | Mistral Large 4 |
| Design Arena: 3D | 1133 | 1253 | Mistral Large 4 |
| Design Arena: all code categories | 1164 | 1259 | Mistral Large 4 |
| Design Arena: SVG | 1032 | 1232 | Mistral Large 4 |
| Design Arena: ASCII art | 1082 | 1203 | Mistral Large 4 |
| LiveBench design | Not measured | 65.6% | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index512
| Benchmark | DeepSeek V3.2 | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.5% | Only Mistral Large 4 measured |
| MedScribe (Vals AI) | Not measured | 80.4% | Only Mistral Large 4 measured |
| IFBench | 60.7% | Not measured | Only DeepSeek V3.2 measured |
| Long context reasoning (AA-LCR) | 73.3% | 81.3% | Mistral Large 4 |
| DTBench | 85.6% | 88.2% | Mistral Large 4 |
| LMCA | 28.8% | 35.8% | Mistral Large 4 |
| CL-bench | 12.4% | Not measured | Only DeepSeek V3.2 measured |
| Surface Evolver Bench | Not measured | 28.1% | Only Mistral Large 4 measured |
| Furniture assembly | Not measured | 20.8% | Only Mistral Large 4 measured |
| CL-bench Life | 7.4% | Not measured | Only DeepSeek V3.2 measured |
| LMArena Text | 1425 | 1431 | Mistral Large 4 |
| LMArena Text: instruction following | 1413 | 1422 | Mistral Large 4 |
| LMArena Text: creative writing | 1400 | 1363 | DeepSeek V3.2 |
| LMArena Vision | Not measured | 1272 | Only Mistral Large 4 measured |
| LMArena Text: English | 1439 | 1433 | DeepSeek V3.2 |
| LMArena Text: non-English | 1409 | 1422 | Mistral Large 4 |
| LMArena Text: Chinese | 1455 | 1492 | Mistral Large 4 |
| LMArena Text: German | 1413 | Not measured | Only DeepSeek V3.2 measured |
| LMArena Text: Japanese | 1374 | 1415 | Mistral Large 4 |
| LMArena Text: Korean | 1370 | Not measured | Only DeepSeek V3.2 measured |
| LMArena Text: French | 1429 | 1492 | Mistral Large 4 |
| LMArena Text: Spanish | 1424 | 1455 | Mistral Large 4 |
| LMArena Text: Russian | 1424 | 1417 | DeepSeek V3.2 |
| LMArena Text: Polish | 1419 | Not measured | Only DeepSeek V3.2 measured |
| LMArena Text: multi-turn | 1427 | 1435 | Mistral Large 4 |
| LMArena Text: longer queries | 1428 | 1428 | Mistral Large 4 |
| LMArena Text: writing and language | 1407 | 1386 | DeepSeek V3.2 |
| LMArena Text: entertainment and media | 1395 | 1378 | DeepSeek V3.2 |
| 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 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.2 | 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 V3.2 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.2 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.2 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 V3.2 | Mistral Large 4 |
|---|---|---|
| Maker | DeepSeek | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | December 1, 2025 | October 6, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.28 | $1.36 |
| Output $/Mtok | $0.42 | $4.18 |
| Coding index | 54.4 | 55.3 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $0.99 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.2 better than Mistral Large 4 for coding?
DeepSeek V3.2 and Mistral Large 4 are level for coding, 54.4 against 55.3 on the Vibe Coding Index, so price and context decide. Pick DeepSeek V3.2 when output tokens cost 10.0x less, or when what matters is LMArena Text: hard prompts in English or LMArena Text: medicine and healthcare, where it leads. Pick Mistral Large 4 when the context window is larger, 1.05M against 164K tokens, or when what matters is LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, DeepSeek V3.2 or Mistral Large 4?
DeepSeek V3.2 costs $0.28 per million input tokens and $0.42 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for DeepSeek V3.2 only.
Which has the bigger context window, DeepSeek V3.2 or Mistral Large 4?
Mistral Large 4, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.2 vs Mistral Large 4 comparison based on?
43 benchmarks have a result for both models as of October 21, 2026. DeepSeek V3.2'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.