DeepSeek V3 0324 vs Mistral Medium 3.5
Mistral Medium 3.5 leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 14.2 to 9.7, and DeepSeek V3 0324 costs 7.0x less per output token ($1.07 vs $7.50 per million). Updated October 22, 2026; 16 benchmarks have a result for both.
DeepSeek V3 0324 or Mistral Medium 3.5: which to pick
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; DeepSeek V3 0324 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3 0324 for output tokens 7.0x cheaper ($1.07 vs $7.50 per million) and work measured by GPQA Diamond or MMLU Pro, where it leads.
- Shared results
- 16
- DeepSeek V3 0324 only
- 19
- Mistral Medium 3.5 only
- 65
- Like-for-like categories
- 6 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 Medium 3.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mistral Medium 3.5
Mistral Medium 3.5 leads, 14.2 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
Mistral Medium 3.5
Mistral Medium 3.5 leads, 7.0 against 0.8.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V3 0324
DeepSeek V3 0324 leads, 61.6% against 34.9%.
Same board, both measured
Math
AIME
No call
Only DeepSeek V3 0324 has a AIME result, 52.2%.
Directional only
Knowledge
MMLU Pro
DeepSeek V3 0324
DeepSeek V3 0324 leads, 79.5% against 75.3%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Medium 3.5 has a Design Arena: websites result, 1142.
Directional only
Long documents
Listed context window
Mistral Medium 3.5
Mistral Medium 3.5 takes 262K tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V3 0324
DeepSeek V3 0324 $0.0008, Mistral Medium 3.5 $0.0053 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Medium 3.5 has the number, $6.02.
Directional only
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, Mistral Medium 3.5 25.5 from 3 benchmarks.
- Widest category
- Agentic work, 26.6 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: DeepSeek V3 0324 47.1% against Mistral Medium 3.5 94.2%, 47.1 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against Mistral Medium 3.5 $7.50 per million output tokens, 7.0x apart.
- Context window
- DeepSeek V3 0324 takes 164K tokens, Mistral Medium 3.5 262K.
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 0324 | Bars | Mistral Medium 3.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 1 | 2 | ||
| Knowledge | 2 | 1 | ||
| General | 0 | 4 | ||
| All shared boards | 3 | 13 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena WebDev | Not measured | 1264 | Only Mistral Medium 3.5 measured |
| AA Coding Index | 21.2 | 46.9 | Mistral Medium 3.5 |
| LiveCodeBench (Vals AI) | 65.5% | Not measured | Only DeepSeek V3 0324 measured |
| SWE-bench Verified (Vals AI) | Not measured | 66.4% | Only Mistral Medium 3.5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 2.9% | Only Mistral Medium 3.5 measured |
| Code migration (Vals AI) | Not measured | 5.1% | Only Mistral Medium 3.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 39.0% | Only Mistral Medium 3.5 measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | Not measured | Only DeepSeek V3 0324 measured |
| SciCode | 39.0% | 40.2% | Mistral Medium 3.5 |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | 33.3% | Mistral Medium 3.5 |
| WeirdML | 36.1% | Not measured | Only DeepSeek V3 0324 measured |
| ALE-Bench | Not measured | 764.0 | Only Mistral Medium 3.5 measured |
| LMArena Text: coding | Not measured | 1460 | Only Mistral Medium 3.5 measured |
| LMArena Text: software and IT | Not measured | 1458 | Only Mistral Medium 3.5 measured |
| LMArena WebDev: React | Not measured | 1254 | Only Mistral Medium 3.5 measured |
| LMArena WebDev: HTML | Not measured | 1308 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 14.2 | Mistral Medium 3.5 |
| Epoch Capabilities Index | Not measured | 141.4 | Only Mistral Medium 3.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 7.0 | Mistral Medium 3.5 |
| Finance Agent (Vals AI) | Not measured | 32.1% | Only Mistral Medium 3.5 measured |
| Tax Agent Bench (Vals AI) | Not measured | 4.5% | Only Mistral Medium 3.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 9.1% | Only Mistral Medium 3.5 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 11.2% | Only Mistral Medium 3.5 measured |
| τ²-Bench Telecom | 47.1% | 94.2% | Mistral Medium 3.5 |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | 34.9% | DeepSeek V3 0324 |
| GPQA Diamond (Artificial Analysis run) | 65.5% | 74.8% | Mistral Medium 3.5 |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 13.8% | Mistral Medium 3.5 |
| GPQA Diamond (Epoch AI run) | 67.6% | Not measured | Only DeepSeek V3 0324 measured |
| SimpleBench | 27.2% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: hard prompts | Not measured | 1436 | Only Mistral Medium 3.5 measured |
| LMArena Text: expert | Not measured | 1432 | Only Mistral Medium 3.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1445 | Only Mistral Medium 3.5 measured |
| LMArena Vision: diagrams | Not measured | 1254 | Only Mistral Medium 3.5 measured |
| LMArena Vision: homework | Not measured | 1230 | Only Mistral Medium 3.5 measured |
| Kagi LLM Benchmark | Not measured | 41.4% | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AIME | 52.2% | Not measured | Only DeepSeek V3 0324 measured |
| MATH 500 (Vals AI) | 88.6% | Not measured | Only DeepSeek V3 0324 measured |
| MGSM (Vals AI) | 91.7% | Not measured | Only DeepSeek V3 0324 measured |
| AA Math Index | 41.0 | Not measured | Only DeepSeek V3 0324 measured |
| AIME 2025 (Artificial Analysis run) | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| OTIS Mock AIME | 37.8% | Not measured | Only DeepSeek V3 0324 measured |
| ProofBench | Not measured | 9.0% | Only Mistral Medium 3.5 measured |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: math | Not measured | 1431 | Only Mistral Medium 3.5 measured |
| LMArena Text: mathematical work | Not measured | 1440 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | 75.3% | DeepSeek V3 0324 |
| LegalBench (Vals AI) | 77.7% | Not measured | Only DeepSeek V3 0324 measured |
| CaseLaw (Vals AI) | Not measured | 44.2% | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | 54.7% | 58.8% | Mistral Medium 3.5 |
| TaxEval (Vals AI) | 71.1% | 68.0% | DeepSeek V3 0324 |
| MortgageTax (Vals AI) | Not measured | 28.9% | Only Mistral Medium 3.5 measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only DeepSeek V3 0324 measured |
| MedCode (Vals AI) | Not measured | 33.8% | Only Mistral Medium 3.5 measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only DeepSeek V3 0324 measured |
| LMArena Text: science | Not measured | 1428 | Only Mistral Medium 3.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1409 | Only Mistral Medium 3.5 measured |
| LMArena Text: legal and government | Not measured | 1437 | Only Mistral Medium 3.5 measured |
| LMArena Text: business and finance | Not measured | 1426 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 5 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1142 | Only Mistral Medium 3.5 measured |
| Design Arena: UI components | Not measured | 1076 | Only Mistral Medium 3.5 measured |
| Design Arena: game dev | Not measured | 1079 | Only Mistral Medium 3.5 measured |
| Design Arena: data viz | Not measured | 1120 | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | Not measured | 1060 | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | Not measured | 1121 | Only Mistral Medium 3.5 measured |
| Design Arena: SVG | Not measured | 949 | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | Not measured | 1062 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 37.6% | Only Mistral Medium 3.5 measured |
| MedScribe (Vals AI) | Not measured | 67.7% | Only Mistral Medium 3.5 measured |
| Vals Multimodal Index | Not measured | 34.8% | Only Mistral Medium 3.5 measured |
| IFBench | 41.0% | 68.8% | Mistral Medium 3.5 |
| Long context reasoning (AA-LCR) | 40.7% | 69.3% | Mistral Medium 3.5 |
| DTBench | 64.8% | 75.5% | Mistral Medium 3.5 |
| LMCA | 15.5% | 26.1% | Mistral Medium 3.5 |
| Fiction.LiveBench | 50.0% | Not measured | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | 77.0% | Not measured | Only DeepSeek V3 0324 measured |
| Surface Evolver Bench | Not measured | 26.9% | Only Mistral Medium 3.5 measured |
| LMArena Text | Not measured | 1421 | Only Mistral Medium 3.5 measured |
| LMArena Text: instruction following | Not measured | 1415 | Only Mistral Medium 3.5 measured |
| LMArena Text: creative writing | Not measured | 1374 | Only Mistral Medium 3.5 measured |
| LMArena Vision | Not measured | 1222 | Only Mistral Medium 3.5 measured |
| LMArena Text: English | Not measured | 1433 | Only Mistral Medium 3.5 measured |
| LMArena Text: non-English | Not measured | 1404 | Only Mistral Medium 3.5 measured |
| LMArena Text: Chinese | Not measured | 1444 | Only Mistral Medium 3.5 measured |
| LMArena Text: German | Not measured | 1453 | Only Mistral Medium 3.5 measured |
| LMArena Text: Korean | Not measured | 1384 | Only Mistral Medium 3.5 measured |
| LMArena Text: French | Not measured | 1448 | Only Mistral Medium 3.5 measured |
| LMArena Text: Spanish | Not measured | 1411 | Only Mistral Medium 3.5 measured |
| LMArena Text: Russian | Not measured | 1395 | Only Mistral Medium 3.5 measured |
| LMArena Text: Polish | Not measured | 1430 | Only Mistral Medium 3.5 measured |
| LMArena Text: multi-turn | Not measured | 1423 | Only Mistral Medium 3.5 measured |
| LMArena Text: longer queries | Not measured | 1415 | Only Mistral Medium 3.5 measured |
| LMArena Text: writing and language | Not measured | 1384 | Only Mistral Medium 3.5 measured |
| LMArena Text: entertainment and media | Not measured | 1382 | Only Mistral Medium 3.5 measured |
| LMArena Vision: English | Not measured | 1240 | Only Mistral Medium 3.5 measured |
| LMArena Vision: Chinese | Not measured | 1244 | Only Mistral Medium 3.5 measured |
| LMArena Vision: reading text | Not measured | 1233 | Only Mistral Medium 3.5 measured |
| LMArena Vision: humor | Not measured | 1216 | Only Mistral Medium 3.5 measured |
| LMArena Vision: creative writing | Not measured | 1198 | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | Mistral Medium 3.5 | 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 0324 costs less
Repository review
50K input + 3K output tokens
DeepSeek V3 0324 costs less
Agent loop
200K input + 10K output tokens
DeepSeek V3 0324 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 0324 | Mistral Medium 3.5 |
|---|---|---|
| Maker | DeepSeek | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | March 24, 2025 | April 30, 2026 |
| Context window | 164K | 262K |
| Input $/Mtok | $0.27 | $1.50 |
| Output $/Mtok | $1.07 | $7.50 |
| Coding index | Not benchmarked | 25.5 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | $6.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 better than Mistral Medium 3.5 for coding?
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; DeepSeek V3 0324 has none, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for output tokens 7.0x cheaper ($1.07 vs $7.50 per million) and work measured by GPQA Diamond or MMLU Pro, where it leads.
Which is cheaper, DeepSeek V3 0324 or Mistral Medium 3.5?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, DeepSeek V3 0324 or Mistral Medium 3.5?
Mistral Medium 3.5, with 262K tokens against 164K.
How many benchmarks is the DeepSeek V3 0324 vs Mistral Medium 3.5 comparison based on?
16 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3 0324's coding index rests on 0 independent benchmarks and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.