Mistral Medium 3.5 vs o3 Pro
o3 Pro leads Mistral Medium 3.5 on the Artificial Analysis Intelligence Index, 21.9 to 14.2, and Mistral Medium 3.5 costs 10.7x less per output token ($7.50 vs $80.00 per million). Updated October 21, 2026; 6 benchmarks have a result for both.
Mistral Medium 3.5 or o3 Pro: which to pick
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; o3 Pro has none, so the two cannot be ranked on coding.
Pick o3 Pro for work measured by AA Intelligence Index or Epoch Capabilities Index, where it leads.
- Shared results
- 6
- Mistral Medium 3.5 only
- 75
- o3 Pro only
- 6
- Like-for-like categories
- 3 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
o3 Pro
o3 Pro leads, 21.9 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
No call
Only Mistral Medium 3.5 has a GPQA Diamond result, 34.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.5 has a MMLU Pro result, 75.3%.
Directional only
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 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Medium 3.5
Mistral Medium 3.5 $0.0053, o3 Pro $0.060 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
- Mistral Medium 3.5 25.5 from 3 benchmarks, o3 Pro not benchmarked.
- Widest category
- Reasoning, 20.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- Kagi LLM Benchmark: Mistral Medium 3.5 41.4% against o3 Pro 72.1%, 30.7 points apart on a 0 to 100 scale.
- Output price
- Mistral Medium 3.5 $7.50 against o3 Pro $80.00 per million output tokens, 10.7x apart.
- Context window
- Mistral Medium 3.5 takes 262K tokens, o3 Pro 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 Pro | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 2 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 6 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index15 boards, none shared
| Benchmark | Mistral Medium 3.5 | o3 Pro | Leader |
|---|---|---|---|
| Aider polyglot | Not measured | 84.9% | Only o3 Pro 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 |
| 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 |
| SciCode | 40.2% | Not measured | Only Mistral Medium 3.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 33.3% | Not measured | Only Mistral Medium 3.5 measured |
| WeirdML | Not measured | 58.2% | Only o3 Pro measured |
| ALE-Bench | 764.0 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: coding | 1460 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: software and IT | 1458 | Not measured | Only Mistral Medium 3.5 measured |
| 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 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.5 | o3 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.2 | 21.9 | o3 Pro |
| Epoch Capabilities Index | 141.4 | 147.3 | o3 Pro |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Medium 3.5 | o3 Pro | 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% | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 35 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Medium 3.5 | o3 Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 34.9% | Not measured | Only Mistral Medium 3.5 measured |
| GPQA Diamond (Artificial Analysis run) | 74.8% | 84.5% | o3 Pro |
| Humanity's Last Exam (Artificial Analysis run) | 13.8% | Not measured | Only Mistral Medium 3.5 measured |
| ARC-AGI | Not measured | 59.3% | Only o3 Pro measured |
| ARC-AGI-2 | Not measured | 4.9% | Only o3 Pro measured |
| LMArena Text: hard prompts | 1436 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: expert | 1432 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: hard prompts in English | 1445 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: diagrams | 1254 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: homework | 1230 | Not measured | Only Mistral Medium 3.5 measured |
| Kagi LLM Benchmark | 41.4% | 72.1% | o3 Pro |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Mistral Medium 3.5 | o3 Pro | Leader |
|---|---|---|---|
| ProofBench | 9.0% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: math | 1431 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: mathematical work | 1440 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Mistral Medium 3.5 | o3 Pro | Leader |
|---|---|---|---|
| MMLU Pro | 75.3% | Not measured | Only Mistral Medium 3.5 measured |
| CaseLaw (Vals AI) | 44.2% | Not measured | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | 58.8% | Not measured | Only Mistral Medium 3.5 measured |
| TaxEval (Vals AI) | 68.0% | Not measured | Only Mistral Medium 3.5 measured |
| MortgageTax (Vals AI) | 28.9% | Not measured | Only Mistral Medium 3.5 measured |
| MedCode (Vals AI) | 33.8% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: science | 1428 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: medicine and healthcare | 1409 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: legal and government | 1437 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: business and finance | 1426 | Not measured | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Medium 3.5 | o3 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1142 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: UI components | 1079 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: game dev | 1079 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: data viz | 1120 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: 3D | 1061 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: all code categories | 1121 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: SVG | 950 | Not measured | Only Mistral Medium 3.5 measured |
| Design Arena: ASCII art | 1063 | 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 index02
| Benchmark | Mistral Medium 3.5 | o3 Pro | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 37.6% | Not measured | Only Mistral Medium 3.5 measured |
| MedScribe (Vals AI) | 67.7% | Not measured | Only Mistral Medium 3.5 measured |
| Vals Multimodal Index | 34.8% | Not measured | Only Mistral Medium 3.5 measured |
| IFBench | 68.8% | Not measured | Only Mistral Medium 3.5 measured |
| Long context reasoning (AA-LCR) | 69.3% | Not measured | Only Mistral Medium 3.5 measured |
| DTBench | 75.5% | 86.9% | o3 Pro |
| LMCA | 26.1% | 38.5% | o3 Pro |
| Fiction.LiveBench | Not measured | 97.2% | Only o3 Pro measured |
| Creative writing (Lech Mazur) | Not measured | 84.4% | Only o3 Pro measured |
| Surface Evolver Bench | 26.9% | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text | 1421 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: instruction following | 1415 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: creative writing | 1374 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision | 1222 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: English | 1433 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: non-English | 1404 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Chinese | 1444 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: German | 1453 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Korean | 1384 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: French | 1448 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Spanish | 1411 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Russian | 1395 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: Polish | 1430 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: multi-turn | 1423 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: longer queries | 1415 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: writing and language | 1384 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Text: entertainment and media | 1382 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: English | 1240 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: Chinese | 1244 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: reading text | 1233 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: humor | 1216 | Not measured | Only Mistral Medium 3.5 measured |
| LMArena Vision: creative writing | 1198 | Not measured | 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 | Mistral Medium 3.5 | o3 Pro | 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 Pro |
|---|---|---|
| Maker | Mistral AI | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 30, 2026 | June 10, 2025 |
| Context window | 262K | 200K |
| Input $/Mtok | $1.50 | $20.00 |
| Output $/Mtok | $7.50 | $80.00 |
| Coding index | 25.5 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $6.02 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Medium 3.5 better than o3 Pro for coding?
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; o3 Pro has none, so the two cannot be ranked on coding. Pick o3 Pro for work measured by AA Intelligence Index or Epoch Capabilities Index, where it leads.
Which is cheaper, Mistral Medium 3.5 or o3 Pro?
Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; o3 Pro costs $20.00 and $80.00. Cost per solved task is known for Mistral Medium 3.5 only.
Which has the bigger context window, Mistral Medium 3.5 or o3 Pro?
Mistral Medium 3.5, with 262K tokens against 200K.
How many benchmarks is the Mistral Medium 3.5 vs o3 Pro comparison based on?
6 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3.5's coding index rests on 3 independent benchmarks and o3 Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.