Mistral Medium 3.5 vs o3
Updated October 21, 2026. 59 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick o3 for coding: it scores 70.7 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5.
Pick Mistral Medium 3.5 when output tokens cost 1.1x less, or when the context window is larger, 262K against 200K tokens.
- Shared results
- 59
- Mistral Medium 3.5 only
- 21
- o3 only
- 38
- Like-for-like categories
- 8 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
o3
o3 scores 70.7 against 9.2.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
o3
o3 leads, 20.2 against 14.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.5 has a AA Agentic Index result, 7.0.
Directional only
Reasoning
GPQA Diamond
o3
o3 leads, 84.1% against 34.9%.
Same board, both measured
Math
AIME
No call
Only o3 has a AIME result, 85.3%.
Directional only
Knowledge
MMLU Pro
o3
o3 leads, 85.6% against 75.3%.
Same board, both measured
Web design
Design Arena: websites
Mistral Medium 3.5
Mistral Medium 3.5 leads, 1142 against 1036.
Same board, both measured
Long documents
Listed context window
Mistral Medium 3.5
Mistral Medium 3.5 takes 262K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Medium 3.5
Mistral Medium 3.5 $0.0053, o3 $0.0060 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
o3
Mistral Medium 3.5 $6.02, o3 $0.571.
Published attempt cost and pass rate
At a glance
- Coding index
- Mistral Medium 3.5 9.2 from 1 benchmark, o3 70.7 from 2 benchmarks.
- Widest category
- Agentic work, 13.5 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond: Mistral Medium 3.5 34.9% against o3 84.1%, 49.2 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.5 $7.50 against o3 $8.00 per million output tokens, 1.1x apart.
- Context window
- Mistral Medium 3.5 takes 262K tokens, o3 200K.
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 | Mistral Medium 3.5 | Bars | o3 | Ties |
|---|---|---|---|---|
| Coding | 2 | 2 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 4 | 4 | ||
| Math | 2 | 0 | ||
| Knowledge | 2 | 7 | ||
| Web design | 4 | 1 | ||
| General | 18 | 10 | ||
| All shared boards | 33 | 26 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index22
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 81.3% | Only o3 measured |
| SWE-bench Verified | Not measured | 58.4% | Only o3 measured |
| SWE-bench Multimodal | Not measured | 36.0% | Only o3 measured |
| LMArena WebDev | 1264 | Not measured | Only Mistral Medium 3.5 measured |
| AA Coding Index | 46.9 | Not measured | Only Mistral Medium 3.5 measured |
| LiveCodeBench (Vals AI) | Not measured | 83.9% | Only o3 measured |
| SWE-bench Verified (Vals AI) | 66.4% | Not measured | Only Mistral Medium 3.5 measured |
| Vibe Code Bench (Vals AI) | 2.9% | Not measured | Only Mistral Medium 3.5 measured |
| Code migration (Vals AI) | 5.1% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 39.0% | Not measured | Only Mistral Medium 3.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 80.8% | Only o3 measured |
| SciCode | 40.2% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | 37.1% | o3 |
| GSO-Bench | Not measured | 8.8% | Only o3 measured |
| WeirdML | Not measured | 52.4% | Only o3 measured |
| ALE-Bench | 764.0 | 933.5 | o3 |
| LMArena Text: coding | 1460 | 1407 | Mistral Medium 3.5 |
| LMArena Text: software and IT | 1458 | 1415 | Mistral Medium 3.5 |
| LMArena WebDev: React | 1254 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena WebDev: HTML | 1308 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 18 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.2 | 20.2 | o3 |
| Epoch Capabilities Index | 141.4 | 146.7 | o3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| AA Agentic Index | 7.0 | Not measured | Only Mistral Medium 3.5 measured |
| Finance Agent (Vals AI) | 32.1% | Not measured | Only Mistral Medium 3.5 measured |
| Tax Agent Bench (Vals AI) | 4.5% | Not measured | Only Mistral Medium 3.5 measured |
| Legal Research Bench (Vals AI) | 9.1% | Not measured | Only Mistral Medium 3.5 measured |
| Excel Modeling Benchmark (Vals AI) | 11.2% | Not measured | Only Mistral Medium 3.5 measured |
| τ²-Bench Telecom | 94.2% | 80.7% | Mistral Medium 3.5 |
| METR time horizons | Not measured | 65.4% | Only o3 measured |
| GDPval | Not measured | 30.8% | Only o3 measured |
| DeepResearch Bench | Not measured | 45.2% | Only o3 measured |
| OSWorld | Not measured | 23.0% | Only o3 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| GPQA Diamond | 34.9% | 84.1% | o3 |
| MMMU Pro (Vals AI) | Not measured | 80.4% | Only o3 measured |
| GPQA Diamond (Artificial Analysis run) | 74.8% | 82.7% | o3 |
| Humanity's Last Exam (Artificial Analysis run) | 13.8% | 20.1% | o3 |
| GPQA Diamond (Epoch AI run) | Not measured | 81.8% | Only o3 measured |
| ARC-AGI | Not measured | 60.8% | Only o3 measured |
| ARC-AGI-2 | Not measured | 6.5% | Only o3 measured |
| SimpleBench | Not measured | 53.1% | Only o3 measured |
| Chess puzzles | Not measured | 37.0% | Only o3 measured |
| Mystery game puzzles | Not measured | 29.0% | Only o3 measured |
| VPCT | Not measured | 52.0% | Only o3 measured |
| LMArena Text: hard prompts | 1436 | 1402 | Mistral Medium 3.5 |
| LMArena Text: expert | 1432 | 1402 | Mistral Medium 3.5 |
| LMArena Text: hard prompts in English | 1445 | 1411 | Mistral Medium 3.5 |
| LMArena Vision: diagrams | 1254 | 1220 | Mistral Medium 3.5 |
| LMArena Vision: homework | 1230 | 1234 | o3 |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| AIME | Not measured | 85.3% | Only o3 measured |
| MATH 500 (Vals AI) | Not measured | 94.6% | Only o3 measured |
| MGSM (Vals AI) | Not measured | 91.8% | Only o3 measured |
| AA Math Index | Not measured | 88.3 | Only o3 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 88.3% | Only o3 measured |
| OTIS Mock AIME | Not measured | 84.4% | Only o3 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 33.3% | Only o3 measured |
| ProofBench | 9.0% | Not measured | Only Mistral Medium 3.5 measured |
| MATH level 5 | Not measured | 97.8% | Only o3 measured |
| LMArena Text: math | 1431 | 1426 | Mistral Medium 3.5 |
| LMArena Text: mathematical work | 1440 | 1423 | Mistral Medium 3.5 |
| Neither model has a result on the other 2 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index27
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | 85.6% | o3 |
| LegalBench (Vals AI) | Not measured | 83.8% | Only o3 measured |
| CaseLaw (Vals AI) | 44.2% | Not measured | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | 58.8% | 59.7% | o3 |
| TaxEval (Vals AI) | 68.0% | 74.6% | o3 |
| MortgageTax (Vals AI) | 28.9% | 65.7% | o3 |
| MedQA (Vals AI) | Not measured | 96.1% | Only o3 measured |
| MedCode (Vals AI) | 33.8% | 47.3% | o3 |
| MMLU Pro (Artificial Analysis run) | Not measured | 85.3% | Only o3 measured |
| SimpleQA Verified | Not measured | 49.4% | Only o3 measured |
| GeoBench | Not measured | 74.0% | Only o3 measured |
| LMArena Text: science | 1428 | 1429 | o3 |
| LMArena Text: medicine and healthcare | 1409 | 1448 | o3 |
| LMArena Text: legal and government | 1437 | 1428 | Mistral Medium 3.5 |
| LMArena Text: business and finance | 1426 | 1393 | Mistral Medium 3.5 |
| Neither model has a result on the other 2 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1142 | 1036 | Mistral Medium 3.5 |
| Design Arena: UI components | 1079 | 1016 | Mistral Medium 3.5 |
| Design Arena: game dev | 1079 | 1034 | Mistral Medium 3.5 |
| Design Arena: data viz | 1120 | 1200 | o3 |
| Design Arena: 3D | 1061 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | 1122 | 1021 | Mistral Medium 3.5 |
| Design Arena: SVG | 949 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | 1062 | Not measured | 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 index1810
| Benchmark | Mistral Medium 3.5 | o3 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 37.6% | 41.8% | o3 |
| MedScribe (Vals AI) | 67.7% | 76.7% | o3 |
| Vals Multimodal Index | 34.8% | Not measured | Only Mistral Medium 3.5 measured |
| IFBench | 68.8% | 71.4% | o3 |
| Long context reasoning (AA-LCR) | 69.3% | 74.7% | o3 |
| DTBench | 75.5% | 84.8% | o3 |
| LMCA | 26.1% | 39.7% | o3 |
| Fiction.LiveBench | Not measured | 88.9% | Only o3 measured |
| Creative writing (Lech Mazur) | Not measured | 83.9% | Only o3 measured |
| CL-bench | Not measured | 17.8% | Only o3 measured |
| Surface Evolver Bench | 26.9% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text | 1421 | 1410 | Mistral Medium 3.5 |
| LMArena Text: instruction following | 1415 | 1368 | Mistral Medium 3.5 |
| LMArena Text: creative writing | 1374 | 1359 | Mistral Medium 3.5 |
| LMArena Vision | 1222 | 1214 | Mistral Medium 3.5 |
| LMArena Text: English | 1433 | 1417 | Mistral Medium 3.5 |
| LMArena Text: non-English | 1404 | 1401 | Mistral Medium 3.5 |
| LMArena Text: Chinese | 1444 | 1437 | Mistral Medium 3.5 |
| LMArena Text: German | 1453 | 1420 | Mistral Medium 3.5 |
| LMArena Text: Japanese | Not measured | 1403 | Only o3 measured |
| LMArena Text: Korean | 1384 | 1370 | Mistral Medium 3.5 |
| LMArena Text: French | 1448 | 1430 | Mistral Medium 3.5 |
| LMArena Text: Spanish | 1411 | 1395 | Mistral Medium 3.5 |
| LMArena Text: Russian | 1395 | 1406 | o3 |
| LMArena Text: Polish | 1430 | 1438 | o3 |
| LMArena Text: multi-turn | 1423 | 1405 | Mistral Medium 3.5 |
| LMArena Text: longer queries | 1415 | 1372 | Mistral Medium 3.5 |
| LMArena Text: writing and language | 1384 | 1372 | Mistral Medium 3.5 |
| LMArena Text: entertainment and media | 1382 | 1373 | Mistral Medium 3.5 |
| LMArena Vision: English | 1240 | 1221 | Mistral Medium 3.5 |
| LMArena Vision: Chinese | 1244 | 1237 | Mistral Medium 3.5 |
| LMArena Vision: reading text | 1233 | 1218 | Mistral Medium 3.5 |
| LMArena Vision: humor | 1216 | 1222 | o3 |
| LMArena Vision: captioning | Not measured | 1210 | Only o3 measured |
| LMArena Vision: recognizing things | Not measured | 1234 | Only o3 measured |
| LMArena Vision: creative writing | 1198 | 1201 | o3 |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Medium 3.5 | o3 | 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
Mistral Medium 3.5 costs less
Repository review
50K input + 3K output tokens
Mistral Medium 3.5 costs less
Agent loop
200K input + 10K output tokens
Mistral Medium 3.5 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 | Mistral Medium 3.5 | OpenAI o3 |
|---|---|---|
| Maker | Mistral AI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 30, 2026 | April 16, 2025 |
| Context window | 262K | 200K |
| Input $/Mtok | $1.50 | $2.00 |
| Output $/Mtok | $7.50 | $8.00 |
| Coding index | 9.2 | 70.7 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | $6.02 | $0.571 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than o3 for coding?
Pick o3 for coding: it scores 70.7 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5. Pick Mistral Medium 3.5 when output tokens cost 1.1x less, or when the context window is larger, 262K against 200K tokens.
Which is cheaper, Mistral Medium 3.5 or o3?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; o3 costs $2.00 and $8.00. Per solved SWE-bench Verified task, Mistral Medium 3.5 costs $6.02 and o3 $0.571.
Which has the bigger context window, Mistral Medium 3.5 or o3?
Mistral Medium 3.5, with 262K tokens against 200K.
How many benchmarks is the Mistral Medium 3.5 vs o3 comparison based on?
59 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3.5's coding index rests on 1 independent benchmark and o3's on 2. Where only one model has a result, the page says so instead of naming a winner.