DeepSeek V3.2 Exp vs Mistral Large 4
Mistral Large 4 leads DeepSeek V3.2 Exp on the Artificial Analysis Intelligence Index, 38.4 to 16.6, and DeepSeek V3.2 Exp costs 10.2x less per output token ($0.41 vs $4.18 per million). Updated October 22, 2026; 40 benchmarks have a result for both.
DeepSeek V3.2 Exp or Mistral Large 4: which to pick
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding.
Pick DeepSeek V3.2 Exp for output tokens 10.2x cheaper ($0.41 vs $4.18 per million) and work measured by LMArena Text: hard prompts in English or LMArena Text: medicine and healthcare, where it leads.
- Shared results
- 40
- DeepSeek V3.2 Exp only
- 19
- Mistral Large 4 only
- 41
- Like-for-like categories
- 7 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 Mistral Large 4 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 16.6.
Same board, both measured
Web design
Design Arena: websites
Mistral Large 4
Mistral Large 4 leads, 1257 against 1178.
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 Exp
DeepSeek V3.2 Exp $0.0005, Mistral Large 4 $0.0034 per turn.
List prices
At a glance
- Coding index
- DeepSeek V3.2 Exp not benchmarked, Mistral Large 4 56.4 from 5 benchmarks.
- Widest category
- Coding, 21.1 points apart on average over 4 shared benchmarks.
- Widest single gap
- LMArena WebDev: DeepSeek V3.2 Exp 1272 against Mistral Large 4 1543, 38.7 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3.2 Exp $0.41 against Mistral Large 4 $4.18 per million output tokens, 10.2x apart.
- Context window
- DeepSeek V3.2 Exp 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 Exp | Bars | Mistral Large 4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 1 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 1 | 3 | ||
| Web design | 0 | 7 | ||
| General | 4 | 13 | ||
| All shared boards | 6 | 34 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | DeepSeek V3.2 Exp | Mistral Large 4 | Leader |
|---|---|---|---|
| Aider polyglot | 74.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| LiveBench coding | Not measured | 60.0% | Only Mistral Large 4 measured |
| LMArena WebDev | 1272 | 1543 | Mistral Large 4 |
| Terminal-Bench 4 (Vals AI) | Not measured | 27.8% | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | Not measured | 78.4% | Only Mistral Large 4 measured |
| 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) | 78.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| SciCode | Not measured | 54.2% | Only Mistral Large 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.1% | Not measured | Only DeepSeek V3.2 Exp measured |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| WeirdML | 39.5% | Not measured | Only DeepSeek V3.2 Exp measured |
| ALE-Bench | Not measured | 1213.2 | Only Mistral Large 4 measured |
| LMArena Text: coding | 1438 | 1478 | Mistral Large 4 |
| LMArena Text: software and IT | 1438 | 1467 | Mistral Large 4 |
| LMArena WebDev: React | Not measured | 1559 | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | 1281 | 1487 | Mistral Large 4 |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.2 Exp | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.6 | 38.4 | Mistral Large 4 |
| Epoch Capabilities Index | 144.9 | 150.0 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | DeepSeek V3.2 Exp | 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 | 33.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| TheAgentCompany | 42.9% | Not measured | Only DeepSeek V3.2 Exp measured |
| Berkeley Function Calling Leaderboard (BFCL) | 56.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | DeepSeek V3.2 Exp | Mistral Large 4 | Leader |
|---|---|---|---|
| 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) | 79.7% | Not measured | Only DeepSeek V3.2 Exp measured |
| Humanity's Last Exam (Artificial Analysis run) | 14.9% | 35.0% | Mistral Large 4 |
| 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 | 1429 | 1444 | Mistral Large 4 |
| LMArena Text: expert | 1422 | 1444 | Mistral Large 4 |
| LMArena Text: hard prompts in English | 1444 | 1442 | DeepSeek V3.2 Exp |
| LMArena Vision: diagrams | Not measured | 1288 | Only Mistral Large 4 measured |
| Kagi LLM Benchmark | 52.2% | Not measured | Only DeepSeek V3.2 Exp measured |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3.2 Exp | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only DeepSeek V3.2 Exp measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only DeepSeek V3.2 Exp 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 | 1422 | 1469 | Mistral Large 4 |
| LMArena Text: mathematical work | 1433 | 1462 | Mistral Large 4 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | DeepSeek V3.2 Exp | Mistral Large 4 | Leader |
|---|---|---|---|
| MedCode (Vals AI) | Not measured | 40.7% | Only Mistral Large 4 measured |
| MMLU Pro (Artificial Analysis run) | 85.0% | Not measured | Only DeepSeek V3.2 Exp measured |
| SimpleQA Verified | Not measured | 20.0% | Only Mistral Large 4 measured |
| LMArena Text: science | 1443 | 1448 | Mistral Large 4 |
| LMArena Text: medicine and healthcare | 1468 | 1433 | DeepSeek V3.2 Exp |
| LMArena Text: legal and government | 1419 | 1425 | Mistral Large 4 |
| LMArena Text: business and finance | 1412 | 1439 | Mistral Large 4 |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | DeepSeek V3.2 Exp | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1178 | 1257 | Mistral Large 4 |
| Design Arena: UI components | 1164 | 1272 | Mistral Large 4 |
| Design Arena: game dev | 1144 | 1225 | Mistral Large 4 |
| Design Arena: data viz | 1152 | 1275 | Mistral Large 4 |
| Design Arena: 3D | 1148 | 1252 | Mistral Large 4 |
| Design Arena: all code categories | 1170 | 1259 | Mistral Large 4 |
| Design Arena: SVG | 1031 | 1232 | Mistral Large 4 |
| Design Arena: ASCII art | Not measured | 1202 | Only Mistral Large 4 measured |
| LiveBench design | Not measured | 65.6% | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index413
| Benchmark | DeepSeek V3.2 Exp | 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 | 54.1% | Not measured | Only DeepSeek V3.2 Exp measured |
| Long context reasoning (AA-LCR) | 72.3% | 81.3% | Mistral Large 4 |
| DTBench | 87.7% | 88.2% | Mistral Large 4 |
| LMCA | 29.1% | 35.8% | Mistral Large 4 |
| Fiction.LiveBench | 83.3% | Not measured | Only DeepSeek V3.2 Exp measured |
| CL-bench | 13.2% | Not measured | Only DeepSeek V3.2 Exp 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 | 9.5% | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text | 1425 | 1431 | Mistral Large 4 |
| LMArena Text: instruction following | 1401 | 1422 | Mistral Large 4 |
| LMArena Text: creative writing | 1404 | 1363 | DeepSeek V3.2 Exp |
| LMArena Vision | Not measured | 1272 | Only Mistral Large 4 measured |
| LMArena Text: English | 1441 | 1433 | DeepSeek V3.2 Exp |
| LMArena Text: non-English | 1404 | 1422 | Mistral Large 4 |
| LMArena Text: Chinese | 1461 | 1492 | Mistral Large 4 |
| LMArena Text: German | 1440 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: Japanese | 1331 | 1415 | Mistral Large 4 |
| LMArena Text: Korean | 1372 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: French | 1434 | 1492 | Mistral Large 4 |
| LMArena Text: Spanish | 1441 | 1455 | Mistral Large 4 |
| LMArena Text: Russian | 1412 | 1417 | Mistral Large 4 |
| LMArena Text: Polish | 1435 | Not measured | Only DeepSeek V3.2 Exp measured |
| LMArena Text: multi-turn | 1422 | 1435 | Mistral Large 4 |
| LMArena Text: longer queries | 1418 | 1428 | Mistral Large 4 |
| LMArena Text: writing and language | 1407 | 1386 | DeepSeek V3.2 Exp |
| LMArena Text: entertainment and media | 1407 | 1378 | DeepSeek V3.2 Exp |
| 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 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3.2 Exp | 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 Exp costs less
Repository review
50K input + 3K output tokens
DeepSeek V3.2 Exp costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3.2 Exp 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 Exp | Mistral Large 4 |
|---|---|---|
| Maker | DeepSeek | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | September 29, 2025 | October 6, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.27 | $1.36 |
| Output $/Mtok | $0.41 | $4.18 |
| Coding index | Not benchmarked | 56.4 |
| Independent measurements behind it | 1 | 5 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3.2 Exp better than Mistral Large 4 for coding?
Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; DeepSeek V3.2 Exp has none, so the two cannot be ranked on coding. Pick DeepSeek V3.2 Exp for output tokens 10.2x cheaper ($0.41 vs $4.18 per million) and work measured by LMArena Text: hard prompts in English or LMArena Text: medicine and healthcare, where it leads.
Which is cheaper, DeepSeek V3.2 Exp or Mistral Large 4?
DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 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 V3.2 Exp or Mistral Large 4?
Mistral Large 4, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3.2 Exp vs Mistral Large 4 comparison based on?
40 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark and Mistral Large 4's on 5. Where only one model has a result, the page says so instead of naming a winner.