Mistral Large vs Mistral Nemo
Updated October 21, 2026. 3 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.
Compare them on price, context and the boards below.
- Shared results
- 3
- Mistral Large only
- 41
- Mistral Nemo only
- 0
- Like-for-like categories
- 3 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
No call
Only Mistral Large has a AA Intelligence Index result, 5.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Mistral Large has a GPQA Diamond result, 47.7%.
Directional only
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large has a MMLU Pro result, 69.7%.
Directional only
Long documents
Listed context window
Mistral Nemo
Mistral Nemo takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Nemo
Mistral Large $0.0050, Mistral Nemo $0.0002 per turn.
List prices
At a glance
- Coding index
- Mistral Large not benchmarked, Mistral Nemo not benchmarked.
- Widest category
- General, 12.2 points apart on average over 1 shared benchmark.
- Widest single gap
- DTBench: Mistral Large 60.8% against Mistral Nemo 48.6%, 12.2 points apart on a 0 to 100 scale.
- Output price
- Mistral Large $6.00 against Mistral Nemo $0.15 per million output tokens, 40.0x apart.
- Context window
- Mistral Large takes 128K tokens, Mistral Nemo 131K.
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 | Bars | Mistral Nemo | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Knowledge | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 3 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index4 boards, none shared
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| LiveCodeBench (Vals AI) | 37.1% | Not measured | Only Mistral Large measured |
| LiveCodeBench (Artificial Analysis run) | 17.8% | Not measured | Only Mistral Large measured |
| LMArena Text: coding | 1275 | Not measured | Only Mistral Large measured |
| LMArena Text: software and IT | 1274 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.8 | Not measured | Only Mistral Large measured |
| Epoch Capabilities Index | 122.1 | 118.7 | Mistral Large |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| GPQA Diamond | 47.7% | Not measured | Only Mistral Large measured |
| GPQA Diamond (Artificial Analysis run) | 35.1% | Not measured | Only Mistral Large measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.5% | Not measured | Only Mistral Large measured |
| LMArena Text: hard prompts | 1257 | Not measured | Only Mistral Large measured |
| LMArena Text: expert | 1208 | Not measured | Only Mistral Large measured |
| LMArena Text: hard prompts in English | 1268 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| AIME | 9.2% | Not measured | Only Mistral Large measured |
| MATH 500 (Vals AI) | 74.4% | Not measured | Only Mistral Large measured |
| MGSM (Vals AI) | 87.2% | Not measured | Only Mistral Large measured |
| LMArena Text: math | 1261 | Not measured | Only Mistral Large measured |
| LMArena Text: mathematical work | 1257 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| MMLU Pro | 69.7% | Not measured | Only Mistral Large measured |
| TaxEval (Vals AI) | 63.8% | Not measured | Only Mistral Large measured |
| MedQA (Vals AI) | 76.2% | Not measured | Only Mistral Large measured |
| MMLU Pro (Artificial Analysis run) | 51.5% | Not measured | Only Mistral Large measured |
| MMLU | 68.8% | 65.3% | Mistral Large |
| LMArena Text: science | 1260 | Not measured | Only Mistral Large measured |
| LMArena Text: medicine and healthcare | 1255 | Not measured | Only Mistral Large measured |
| LMArena Text: legal and government | 1275 | Not measured | Only Mistral Large measured |
| LMArena Text: business and finance | 1238 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 8 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large | Mistral Nemo | Leader |
|---|---|---|---|
| DTBench | 60.8% | 48.6% | Mistral Large |
| LMArena Text | 1265 | Not measured | Only Mistral Large measured |
| LMArena Text: instruction following | 1249 | Not measured | Only Mistral Large measured |
| LMArena Text: creative writing | 1242 | Not measured | Only Mistral Large measured |
| LMArena Text: English | 1284 | Not measured | Only Mistral Large measured |
| LMArena Text: non-English | 1235 | Not measured | Only Mistral Large measured |
| LMArena Text: Chinese | 1239 | Not measured | Only Mistral Large measured |
| LMArena Text: German | 1242 | Not measured | Only Mistral Large measured |
| LMArena Text: Japanese | 1170 | Not measured | Only Mistral Large measured |
| LMArena Text: Korean | 1202 | Not measured | Only Mistral Large measured |
| LMArena Text: French | 1325 | Not measured | Only Mistral Large measured |
| LMArena Text: Spanish | 1268 | Not measured | Only Mistral Large measured |
| LMArena Text: Russian | 1252 | Not measured | Only Mistral Large measured |
| LMArena Text: Polish | 1157 | Not measured | Only Mistral Large measured |
| LMArena Text: multi-turn | 1260 | Not measured | Only Mistral Large measured |
| LMArena Text: longer queries | 1261 | Not measured | Only Mistral Large measured |
| LMArena Text: writing and language | 1261 | Not measured | Only Mistral Large measured |
| LMArena Text: entertainment and media | 1230 | Not measured | Only Mistral Large measured |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large | Mistral Nemo | 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 Nemo costs less
Repository review
50K input + 3K output tokens
Mistral Nemo costs less
Agent loop
200K input + 10K output tokens
Mistral Nemo 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 | Mistral Nemo |
|---|---|---|
| Maker | Mistral AI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | February 26, 2024 | July 19, 2024 |
| Context window | 128K | 131K |
| Input $/Mtok | $2.00 | $0.15 |
| Output $/Mtok | $6.00 | $0.15 |
| 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 better than Mistral Nemo for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Mistral Large or Mistral Nemo?
Mistral Large costs $2.00 per million input tokens and $6.00 per million output tokens; Mistral Nemo costs $0.15 and $0.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large or Mistral Nemo?
Mistral Nemo, with 131K tokens against 128K.
How many benchmarks is the Mistral Large vs Mistral Nemo comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. Mistral Large's coding index rests on 0 independent benchmarks and Mistral Nemo's on 0. Where only one model has a result, the page says so instead of naming a winner.