Mistral Large 3 2512 vs Mistral Medium 3.5
Mistral Medium 3.5 leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 14.2 to 9.3, and Mistral Large 3 2512 costs 5.0x less per output token ($1.50 vs $7.50 per million). Updated October 21, 2026; 22 benchmarks have a result for both.
Mistral Large 3 2512 or Mistral Medium 3.5: which to pick
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for output tokens 5.0x cheaper ($1.50 vs $7.50 per million) and a lower cost per solved task ($0.77 against $6.02).
- Shared results
- 22
- Mistral Large 3 2512 only
- 6
- Mistral Medium 3.5 only
- 59
- Like-for-like categories
- 7 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 9.3.
Same board, both measured
Agentic work
AA Agentic Index
Mistral Medium 3.5
Mistral Medium 3.5 leads, 7.0 against 1.0.
Same board, both measured
Reasoning
GPQA Diamond
Mistral Large 3 2512
Mistral Large 3 2512 leads, 68.4% against 34.9%.
Same board, both measured
Math
AIME
No call
Only Mistral Large 3 2512 has a AIME result, 42.9%.
Directional only
Knowledge
MMLU Pro
Mistral Large 3 2512
Mistral Large 3 2512 leads, 79.8% against 75.3%.
Same board, both measured
Web design
Design Arena: websites
Mistral Large 3 2512
Mistral Large 3 2512 leads, 1162 against 1142.
Same board, both measured
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large 3 2512
Mistral Large 3 2512 $0.0013, Mistral Medium 3.5 $0.0053 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Mistral Large 3 2512
Mistral Large 3 2512 $0.77, Mistral Medium 3.5 $6.02.
Published attempt cost and pass rate
At a glance
- Coding index
- Mistral Large 3 2512 not benchmarked, Mistral Medium 3.5 25.5 from 3 benchmarks.
- Widest category
- Reasoning, 33.6 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond: Mistral Large 3 2512 68.4% against Mistral Medium 3.5 34.9%, 33.6 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Mistral Medium 3.5 $7.50 per million output tokens, 5.0x apart.
- Context window
- Both take 262K 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 3 2512 | Bars | Mistral Medium 3.5 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 0 | ||
| Knowledge | 5 | 0 | ||
| Web design | 8 | 0 | ||
| General | 0 | 3 | ||
| All shared boards | 14 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1264 | Only Mistral Medium 3.5 measured |
| AA Coding Index | 20.1 | 46.9 | Mistral Medium 3.5 |
| LiveCodeBench (Vals AI) | 55.3% | Not measured | Only Mistral Large 3 2512 measured |
| SWE-bench Verified (Vals AI) | 41.4% | 66.4% | Mistral Medium 3.5 |
| 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 |
| SciCode | Not measured | 40.2% | Only Mistral Medium 3.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 33.3% | Only Mistral Medium 3.5 measured |
| ALE-Bench | 264.7 | 764.0 | Mistral Medium 3.5 |
| 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 25 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | 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 index01
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 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 | Not measured | 94.2% | 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 index10
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 68.4% | 34.9% | Mistral Large 3 2512 |
| MMMU Pro (Vals AI) | 66.2% | Not measured | Only Mistral Large 3 2512 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 74.8% | Only Mistral Medium 3.5 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 13.8% | Only Mistral Medium 3.5 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 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AIME | 42.9% | Not measured | Only Mistral Large 3 2512 measured |
| MGSM (Vals AI) | 85.4% | Not measured | Only Mistral Large 3 2512 measured |
| ProofBench | Not measured | 9.0% | Only Mistral Medium 3.5 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 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| MMLU Pro | 79.8% | 75.3% | Mistral Large 3 2512 |
| LegalBench (Vals AI) | 79.1% | Not measured | Only Mistral Large 3 2512 measured |
| CaseLaw (Vals AI) | 61.4% | 44.2% | Mistral Large 3 2512 |
| CorpFin (Vals AI) | 61.0% | 58.8% | Mistral Large 3 2512 |
| TaxEval (Vals AI) | 73.1% | 68.0% | Mistral Large 3 2512 |
| MortgageTax (Vals AI) | 52.1% | 28.9% | Mistral Large 3 2512 |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| MedCode (Vals AI) | Not measured | 33.8% | Only Mistral Medium 3.5 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 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | 1142 | Mistral Large 3 2512 |
| Design Arena: UI components | 1102 | 1079 | Mistral Large 3 2512 |
| Design Arena: game dev | 1080 | 1079 | Mistral Large 3 2512 |
| Design Arena: data viz | 1136 | 1120 | Mistral Large 3 2512 |
| Design Arena: 3D | 1100 | 1061 | Mistral Large 3 2512 |
| Design Arena: all code categories | 1142 | 1121 | Mistral Large 3 2512 |
| Design Arena: SVG | 993 | 950 | Mistral Large 3 2512 |
| Design Arena: ASCII art | 1069 | 1063 | Mistral Large 3 2512 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Large 3 2512 | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 24.6% | 37.6% | Mistral Medium 3.5 |
| 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 | Not measured | 68.8% | Only Mistral Medium 3.5 measured |
| Long context reasoning (AA-LCR) | Not measured | 69.3% | Only Mistral Medium 3.5 measured |
| DTBench | 65.1% | 75.5% | Mistral Medium 3.5 |
| LMCA | 16.7% | 26.1% | Mistral Medium 3.5 |
| 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 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 3 2512 | 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
Mistral Large 3 2512 costs less
Repository review
50K input + 3K output tokens
Mistral Large 3 2512 costs less
Agent loop
200K input + 10K output tokens
Mistral Large 3 2512 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 3 2512 | Mistral Medium 3.5 |
|---|---|---|
| Maker | Mistral AI | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | December 1, 2025 | April 30, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.50 | $1.50 |
| Output $/Mtok | $1.50 | $7.50 |
| Coding index | Not benchmarked | 25.5 |
| Independent measurements behind it | 1 | 3 |
| Cost per solved task | $0.77 | $6.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Mistral Medium 3.5 for coding?
Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; Mistral Large 3 2512 has none, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for output tokens 5.0x cheaper ($1.50 vs $7.50 per million) and a lower cost per solved task ($0.77 against $6.02).
Which is cheaper, Mistral Large 3 2512 or Mistral Medium 3.5?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Per solved SWE-bench Verified task, Mistral Large 3 2512 costs $0.77 and Mistral Medium 3.5 $6.02.
Which has the bigger context window, Mistral Large 3 2512 or Mistral Medium 3.5?
Neither: both take 262K tokens.
How many benchmarks is the Mistral Large 3 2512 vs Mistral Medium 3.5 comparison based on?
22 benchmarks have a result for both models as of October 21, 2026. Mistral Large 3 2512's coding index rests on 1 independent benchmark and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.