Mistral Large 2407 vs Mistral Medium 3
Updated October 21, 2026. 11 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 Large 2407 has the edge where what matters is LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
- Shared results
- 11
- Mistral Large 2407 only
- 6
- Mistral Medium 3 only
- 46
- 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
Mistral Medium 3
Mistral Medium 3 leads, 9.0 against 7.6.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mistral Medium 3 has a Design Arena: websites result, 1079.
Directional only
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Medium 3
Mistral Large 2407 $0.0050, Mistral Medium 3 $0.0014 per turn.
List prices
At a glance
- Coding index
- Mistral Large 2407 not benchmarked, Mistral Medium 3 not benchmarked.
- Widest category
- Math, 30.3 points apart on average over 2 shared benchmarks.
- Widest single gap
- AIME 2025 (Artificial Analysis run): Mistral Large 2407 0.0% against Mistral Medium 3 30.3%, 30.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 2407 $6.00 against Mistral Medium 3 $2.00 per million output tokens, 3.0x apart.
- Context window
- Both take 131K tokens.
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 Large 2407 | Bars | Mistral Medium 3 | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 3 | ||
| All shared boards | 1 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 26.7% | 40.0% | Mistral Medium 3 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 3.8% | Only Mistral Medium 3 measured |
| LMArena Text: coding | Not measured | 1385 | Only Mistral Medium 3 measured |
| LMArena Text: software and IT | Not measured | 1385 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.6 | 9.0 | Mistral Medium 3 |
| Epoch Capabilities Index | Not measured | 134.0 | Only Mistral Medium 3 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 33.0% | 24.3% | Mistral Large 2407 |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 47.2% | 57.8% | Mistral Medium 3 |
| Humanity's Last Exam (Artificial Analysis run) | 2.9% | 4.1% | Mistral Medium 3 |
| GPQA Diamond (Epoch AI run) | 49.0% | Not measured | Only Mistral Large 2407 measured |
| SimpleBench | 22.5% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text: hard prompts | Not measured | 1364 | Only Mistral Medium 3 measured |
| LMArena Text: expert | Not measured | 1342 | Only Mistral Medium 3 measured |
| LMArena Text: hard prompts in English | Not measured | 1374 | Only Mistral Medium 3 measured |
| LMArena Vision: diagrams | Not measured | 1155 | Only Mistral Medium 3 measured |
| LMArena Vision: homework | Not measured | 1165 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 12 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Math Index | 0.0 | 30.3 | Mistral Medium 3 |
| AIME 2025 (Artificial Analysis run) | 0.0% | 30.3% | Mistral Medium 3 |
| OTIS Mock AIME | 8.5% | Not measured | Only Mistral Large 2407 measured |
| MATH level 5 | 44.8% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text: math | Not measured | 1353 | Only Mistral Medium 3 measured |
| LMArena Text: mathematical work | Not measured | 1354 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 68.3% | 76.0% | Mistral Medium 3 |
| MMLU | 80.0% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text: science | Not measured | 1381 | Only Mistral Medium 3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1381 | Only Mistral Medium 3 measured |
| LMArena Text: legal and government | Not measured | 1384 | Only Mistral Medium 3 measured |
| LMArena Text: business and finance | Not measured | 1352 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1079 | Only Mistral Medium 3 measured |
| Design Arena: UI components | Not measured | 1024 | Only Mistral Medium 3 measured |
| Design Arena: game dev | Not measured | 1018 | Only Mistral Medium 3 measured |
| Design Arena: data viz | Not measured | 1034 | Only Mistral Medium 3 measured |
| Design Arena: 3D | Not measured | 1083 | Only Mistral Medium 3 measured |
| Design Arena: all code categories | Not measured | 1069 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | Leader |
|---|---|---|---|
| IFBench | 31.6% | 39.3% | Mistral Medium 3 |
| Long context reasoning (AA-LCR) | 2.0% | 31.3% | Mistral Medium 3 |
| DTBench | 61.2% | 62.3% | Mistral Medium 3 |
| Creative writing (Lech Mazur) | 69.0% | Not measured | Only Mistral Large 2407 measured |
| LMArena Text | Not measured | 1370 | Only Mistral Medium 3 measured |
| LMArena Text: instruction following | Not measured | 1338 | Only Mistral Medium 3 measured |
| LMArena Text: creative writing | Not measured | 1343 | Only Mistral Medium 3 measured |
| LMArena Vision | Not measured | 1157 | Only Mistral Medium 3 measured |
| LMArena Text: English | Not measured | 1385 | Only Mistral Medium 3 measured |
| LMArena Text: non-English | Not measured | 1353 | Only Mistral Medium 3 measured |
| LMArena Text: Chinese | Not measured | 1374 | Only Mistral Medium 3 measured |
| LMArena Text: German | Not measured | 1377 | Only Mistral Medium 3 measured |
| LMArena Text: Japanese | Not measured | 1316 | Only Mistral Medium 3 measured |
| LMArena Text: Korean | Not measured | 1304 | Only Mistral Medium 3 measured |
| LMArena Text: French | Not measured | 1368 | Only Mistral Medium 3 measured |
| LMArena Text: Spanish | Not measured | 1364 | Only Mistral Medium 3 measured |
| LMArena Text: Russian | Not measured | 1359 | Only Mistral Medium 3 measured |
| LMArena Text: Polish | Not measured | 1371 | Only Mistral Medium 3 measured |
| LMArena Text: multi-turn | Not measured | 1384 | Only Mistral Medium 3 measured |
| LMArena Text: longer queries | Not measured | 1360 | Only Mistral Medium 3 measured |
| LMArena Text: writing and language | Not measured | 1352 | Only Mistral Medium 3 measured |
| LMArena Text: entertainment and media | Not measured | 1335 | Only Mistral Medium 3 measured |
| LMArena Vision: English | Not measured | 1172 | Only Mistral Medium 3 measured |
| LMArena Vision: Chinese | Not measured | 1161 | Only Mistral Medium 3 measured |
| LMArena Vision: reading text | Not measured | 1154 | Only Mistral Medium 3 measured |
| LMArena Vision: humor | Not measured | 1145 | Only Mistral Medium 3 measured |
| LMArena Vision: captioning | Not measured | 1094 | Only Mistral Medium 3 measured |
| LMArena Vision: recognizing things | Not measured | 1141 | Only Mistral Medium 3 measured |
| LMArena Vision: creative writing | Not measured | 1146 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 2407 | Mistral Medium 3 | 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 costs less
Repository review
50K input + 3K output tokens
Mistral Medium 3 costs less
Agent loop
200K input + 10K output tokens
Mistral Medium 3 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 Large 2407 | Mistral Medium 3 |
|---|---|---|
| Maker | Mistral AI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | November 19, 2024 | May 7, 2025 |
| Context window | 131K | 131K |
| Input $/Mtok | $2.00 | $0.40 |
| Output $/Mtok | $6.00 | $2.00 |
| 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 Large 2407 better than Mistral Medium 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Mistral Large 2407 has the edge where what matters is LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.
Which is cheaper, Mistral Large 2407 or Mistral Medium 3?
Mistral Large 2407 costs $2.00 per million input tokens and $6.00 per million output tokens; Mistral Medium 3 costs $0.40 and $2.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 2407 or Mistral Medium 3?
Neither: both take 131K tokens.
How many benchmarks is the Mistral Large 2407 vs Mistral Medium 3 comparison based on?
11 benchmarks have a result for both models as of October 21, 2026. Mistral Large 2407's coding index rests on 0 independent benchmarks and Mistral Medium 3's on 0. Where only one model has a result, the page says so instead of naming a winner.