Mistral Medium 3.1 vs o1
Updated October 21, 2026. 51 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Mistral Medium 3.1 has the edge where output tokens cost 30.0x less, and where what matters is AA Coding Index or LiveCodeBench (Vals AI), where it leads.
- Shared results
- 51
- Mistral Medium 3.1 only
- 23
- o1 only
- 17
- 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, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
o1
o1 leads, 15.2 against 9.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.1 has a AA Agentic Index result, 1.9.
Directional only
Reasoning
GPQA Diamond
No call
Only o1 has a GPQA Diamond result, 73.2%.
Directional only
Math
AIME
o1
o1 leads, 71.5% against 42.3%.
Same board, both measured
Knowledge
MMLU Pro
o1
o1 leads, 83.5% against 75.3%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Medium 3.1 has a Design Arena: websites result, 1133.
Directional only
Long documents
Listed context window
o1
o1 takes 200K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Medium 3.1
Mistral Medium 3.1 $0.0014, o1 $0.045 per turn.
List prices
At a glance
- Coding index
- Mistral Medium 3.1 not benchmarked, o1 not benchmarked.
- Widest category
- Agentic work, 21.9 points apart on average over 1 shared benchmark.
- Widest single gap
- IFBench: Mistral Medium 3.1 39.8% against o1 70.3%, 30.5 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.1 $2.00 against o1 $60.00 per million output tokens, 30.0x apart.
- Context window
- Mistral Medium 3.1 takes 131K tokens, o1 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 3.1 | Bars | o1 | Ties |
|---|---|---|---|---|
| Coding | 2 | 4 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 3 | 3 | ||
| Math | 3 | 2 | ||
| Knowledge | 4 | 5 | ||
| General | 17 | 6 | ||
| All shared boards | 29 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index24
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 61.7% | Only o1 measured |
| AA Coding Index | 20.5 | 39.7 | o1 |
| LiveCodeBench (Vals AI) | 44.8% | 50.3% | o1 |
| LiveCodeBench (Artificial Analysis run) | 40.6% | 67.9% | o1 |
| SciCode | 32.4% | Not measured | Only Mistral Medium 3.1 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 10.6% | 12.9% | o1 |
| WeirdML | Not measured | 46.1% | Only o1 measured |
| ALE-Bench | 210.2 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: coding | 1433 | 1367 | Mistral Medium 3.1 |
| LMArena Text: software and IT | 1436 | 1366 | Mistral Medium 3.1 |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.2 | 15.2 | o1 |
| Epoch Capabilities Index | Not measured | 141.7 | Only o1 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.9 | Not measured | Only Mistral Medium 3.1 measured |
| τ²-Bench Telecom | 40.6% | 62.6% | o1 |
| METR time horizons | Not measured | 51.1% | Only o1 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 73.2% | Only o1 measured |
| MMMU Pro (Vals AI) | 63.0% | 77.4% | o1 |
| GPQA Diamond (Artificial Analysis run) | 58.8% | 74.7% | o1 |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 7.0% | o1 |
| GPQA Diamond (Epoch AI run) | Not measured | 76.8% | Only o1 measured |
| ARC-AGI | Not measured | 30.7% | Only o1 measured |
| SimpleBench | Not measured | 40.1% | Only o1 measured |
| Chess puzzles | Not measured | 10.0% | Only o1 measured |
| VPCT | Not measured | 37.0% | Only o1 measured |
| LMArena Text: hard prompts | 1426 | 1371 | Mistral Medium 3.1 |
| LMArena Text: expert | 1408 | 1361 | Mistral Medium 3.1 |
| LMArena Text: hard prompts in English | 1435 | 1372 | Mistral Medium 3.1 |
| LMArena Vision: diagrams | 1175 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: homework | 1165 | Not measured | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| AIME | 42.3% | 71.5% | o1 |
| MATH 500 (Vals AI) | 87.0% | 90.4% | o1 |
| MGSM (Vals AI) | 90.9% | 89.3% | Mistral Medium 3.1 |
| AA Math Index | 38.3 | Not measured | Only Mistral Medium 3.1 measured |
| AIME 2025 (Artificial Analysis run) | 38.3% | Not measured | Only Mistral Medium 3.1 measured |
| OTIS Mock AIME | Not measured | 73.3% | Only o1 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 14.7% | Only o1 measured |
| MATH level 5 | Not measured | 94.7% | Only o1 measured |
| LMArena Text: math | 1408 | 1388 | Mistral Medium 3.1 |
| LMArena Text: mathematical work | 1412 | 1390 | Mistral Medium 3.1 |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index45
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | 83.5% | o1 |
| LegalBench (Vals AI) | 62.0% | 80.4% | o1 |
| CorpFin (Vals AI) | 50.7% | Not measured | Only Mistral Medium 3.1 measured |
| TaxEval (Vals AI) | 70.3% | 74.3% | o1 |
| MortgageTax (Vals AI) | 36.5% | Not measured | Only Mistral Medium 3.1 measured |
| MedQA (Vals AI) | 78.2% | 96.5% | o1 |
| MMLU Pro (Artificial Analysis run) | 68.3% | 84.1% | o1 |
| SimpleQA Verified | Not measured | 41.1% | Only o1 measured |
| GeoBench | Not measured | 80.0% | Only o1 measured |
| LMArena Text: science | 1444 | 1369 | Mistral Medium 3.1 |
| LMArena Text: medicine and healthcare | 1449 | 1355 | Mistral Medium 3.1 |
| LMArena Text: legal and government | 1439 | 1368 | Mistral Medium 3.1 |
| LMArena Text: business and finance | 1418 | 1328 | Mistral Medium 3.1 |
| Neither model has a result on the other 4 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1133 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: UI components | 1099 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: game dev | 1074 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: data viz | 1144 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: 3D | 1081 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: all code categories | 1120 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: SVG | 993 | Not measured | Only Mistral Medium 3.1 measured |
| Design Arena: ASCII art | 997 | Not measured | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index176
| Benchmark | Mistral Medium 3.1 | o1 | Leader |
|---|---|---|---|
| IFBench | 39.8% | 70.3% | o1 |
| Long context reasoning (AA-LCR) | 42.7% | 65.0% | o1 |
| DTBench | 67.5% | 74.7% | o1 |
| LMCA | 19.1% | 22.3% | o1 |
| Fiction.LiveBench | Not measured | 83.3% | Only o1 measured |
| Creative writing (Lech Mazur) | Not measured | 70.2% | Only o1 measured |
| LMArena Text | 1424 | 1366 | Mistral Medium 3.1 |
| LMArena Text: instruction following | 1398 | 1367 | Mistral Medium 3.1 |
| LMArena Text: creative writing | 1391 | 1347 | Mistral Medium 3.1 |
| LMArena Vision | 1172 | 1168 | Mistral Medium 3.1 |
| LMArena Text: English | 1438 | 1372 | Mistral Medium 3.1 |
| LMArena Text: non-English | 1408 | 1358 | Mistral Medium 3.1 |
| LMArena Text: Chinese | 1447 | 1394 | Mistral Medium 3.1 |
| LMArena Text: German | 1432 | 1337 | Mistral Medium 3.1 |
| LMArena Text: Japanese | 1379 | 1346 | Mistral Medium 3.1 |
| LMArena Text: Korean | 1380 | 1396 | o1 |
| LMArena Text: French | 1460 | 1344 | Mistral Medium 3.1 |
| LMArena Text: Spanish | 1433 | 1345 | Mistral Medium 3.1 |
| LMArena Text: Russian | 1411 | 1356 | Mistral Medium 3.1 |
| LMArena Text: Polish | 1430 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Text: multi-turn | 1418 | 1355 | Mistral Medium 3.1 |
| LMArena Text: longer queries | 1406 | 1378 | Mistral Medium 3.1 |
| LMArena Text: writing and language | 1395 | 1360 | Mistral Medium 3.1 |
| LMArena Text: entertainment and media | 1390 | 1358 | Mistral Medium 3.1 |
| LMArena Vision: English | 1179 | 1162 | Mistral Medium 3.1 |
| LMArena Vision: Chinese | 1190 | 1235 | o1 |
| LMArena Vision: reading text | 1175 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: humor | 1168 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: captioning | 1145 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: recognizing things | 1147 | Not measured | Only Mistral Medium 3.1 measured |
| LMArena Vision: creative writing | 1200 | Not measured | Only Mistral Medium 3.1 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 | Mistral Medium 3.1 | o1 | 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 3.1 costs less
Repository review
50K input + 3K output tokens
Mistral Medium 3.1 costs less
Agent loop
200K input + 10K output tokens
Mistral Medium 3.1 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 3.1 | OpenAI o1 |
|---|---|---|
| Maker | Mistral AI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | August 13, 2025 | December 17, 2024 |
| Context window | 131K | 200K |
| Input $/Mtok | $0.40 | $15.00 |
| Output $/Mtok | $2.00 | $60.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.1 better than o1 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Mistral Medium 3.1 has the edge where output tokens cost 30.0x less, and where what matters is AA Coding Index or LiveCodeBench (Vals AI), where it leads.
Which is cheaper, Mistral Medium 3.1 or o1?
Mistral Medium 3.1 costs $0.40 per million input tokens and $2.00 per million output tokens; o1 costs $15.00 and $60.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Medium 3.1 or o1?
o1, with 200K tokens against 131K.
How many benchmarks is the Mistral Medium 3.1 vs o1 comparison based on?
51 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3.1's coding index rests on 0 independent benchmarks and o1's on 0. Where only one model has a result, the page says so instead of naming a winner.