Mistral Large 3 2512 vs Nemotron 3 Super
Nemotron 3 Super leads Mistral Large 3 2512 on the Artificial Analysis Intelligence Index, 12.8 to 9.3, and Nemotron 3 Super costs 3.3x less per output token ($0.45 vs $1.50 per million). Updated October 22, 2026; 4 benchmarks have a result for both.
Mistral Large 3 2512 or Nemotron 3 Super: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Large 3 2512 for work measured by AA Coding Index or AA Intelligence Index, where it leads.
- Shared results
- 4
- Mistral Large 3 2512 only
- 24
- Nemotron 3 Super only
- 35
- 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Nemotron 3 Super
Nemotron 3 Super leads, 12.8 against 9.3.
Same board, both measured
Agentic work
AA Agentic Index
Nemotron 3 Super
Nemotron 3 Super leads, 1.7 against 1.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Mistral Large 3 2512 has a GPQA Diamond result, 68.4%.
Directional only
Math
AIME
No call
Only Mistral Large 3 2512 has a AIME result, 42.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Large 3 2512 has a MMLU Pro result, 79.8%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Large 3 2512 has a Design Arena: websites result, 1162.
Directional only
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Nemotron 3 Super
Mistral Large 3 2512 $0.0013, Nemotron 3 Super $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Mistral Large 3 2512 has the number, $0.77.
Directional only
At a glance
- Coding index
- Mistral Large 3 2512 not benchmarked, Nemotron 3 Super not benchmarked.
- Widest category
- Coding, 9.6 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Coding Index: Mistral Large 3 2512 20.1 against Nemotron 3 Super 37.7, 17.6 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 3 2512 $1.50 against Nemotron 3 Super $0.45 per million output tokens, 3.3x 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 | Nemotron 3 Super | Ties |
|---|---|---|---|---|
| Coding | 1 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| All shared boards | 1 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
| Benchmark | Mistral Large 3 2512 | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Coding Index | 20.1 | 37.7 | Nemotron 3 Super |
| LiveCodeBench (Vals AI) | 55.3% | Not measured | Only Mistral Large 3 2512 measured |
| SWE-bench Verified (Vals AI) | 41.4% | Not measured | Only Mistral Large 3 2512 measured |
| SciCode | Not measured | 36.2% | Only Nemotron 3 Super measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 28.8% | Only Nemotron 3 Super measured |
| WeirdML | Not measured | 38.0% | Only Nemotron 3 Super measured |
| ALE-Bench | 264.7 | 213.9 | Mistral Large 3 2512 |
| LMArena Text: coding | Not measured | 1403 | Only Nemotron 3 Super measured |
| LMArena Text: software and IT | Not measured | 1409 | Only Nemotron 3 Super 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 3 2512 | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.3 | 12.8 | Nemotron 3 Super |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 3 2512 | Nemotron 3 Super | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | 1.7 | Nemotron 3 Super |
| τ²-Bench Telecom | Not measured | 67.8% | Only Nemotron 3 Super measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Mistral Large 3 2512 | Nemotron 3 Super | Leader |
|---|---|---|---|
| GPQA Diamond | 68.4% | Not measured | Only Mistral Large 3 2512 measured |
| MMMU Pro (Vals AI) | 66.2% | Not measured | Only Mistral Large 3 2512 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.0% | Only Nemotron 3 Super measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 20.8% | Only Nemotron 3 Super measured |
| LMArena Text: hard prompts | Not measured | 1386 | Only Nemotron 3 Super measured |
| LMArena Text: expert | Not measured | 1398 | Only Nemotron 3 Super measured |
| LMArena Text: hard prompts in English | Not measured | 1397 | Only Nemotron 3 Super measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mistral Large 3 2512 | Nemotron 3 Super | 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 |
| LMArena Text: math | Not measured | 1380 | Only Nemotron 3 Super measured |
| LMArena Text: mathematical work | Not measured | 1405 | Only Nemotron 3 Super measured |
| MathArena | Not measured | 16.6% | Only Nemotron 3 Super measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Mistral Large 3 2512 | Nemotron 3 Super | Leader |
|---|---|---|---|
| MMLU Pro | 79.8% | Not measured | Only Mistral Large 3 2512 measured |
| LegalBench (Vals AI) | 79.1% | Not measured | Only Mistral Large 3 2512 measured |
| CaseLaw (Vals AI) | 61.4% | Not measured | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | 61.0% | Not measured | Only Mistral Large 3 2512 measured |
| TaxEval (Vals AI) | 73.1% | Not measured | Only Mistral Large 3 2512 measured |
| MortgageTax (Vals AI) | 52.1% | Not measured | Only Mistral Large 3 2512 measured |
| MedQA (Vals AI) | 82.2% | Not measured | Only Mistral Large 3 2512 measured |
| LMArena Text: science | Not measured | 1387 | Only Nemotron 3 Super measured |
| LMArena Text: medicine and healthcare | Not measured | 1383 | Only Nemotron 3 Super measured |
| LMArena Text: legal and government | Not measured | 1392 | Only Nemotron 3 Super measured |
| LMArena Text: business and finance | Not measured | 1364 | Only Nemotron 3 Super measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mistral Large 3 2512 | Nemotron 3 Super | Leader |
|---|---|---|---|
| Design Arena: websites | 1162 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: UI components | 1099 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: game dev | 1079 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: data viz | 1137 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: 3D | 1099 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: all code categories | 1141 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: SVG | 992 | Not measured | Only Mistral Large 3 2512 measured |
| Design Arena: ASCII art | 1069 | Not measured | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
| Benchmark | Mistral Large 3 2512 | Nemotron 3 Super | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 24.6% | Not measured | Only Mistral Large 3 2512 measured |
| IFBench | Not measured | 71.5% | Only Nemotron 3 Super measured |
| Long context reasoning (AA-LCR) | Not measured | 65.7% | Only Nemotron 3 Super measured |
| DTBench | 65.1% | Not measured | Only Mistral Large 3 2512 measured |
| LMCA | 16.7% | Not measured | Only Mistral Large 3 2512 measured |
| LMArena Text | Not measured | 1378 | Only Nemotron 3 Super measured |
| LMArena Text: instruction following | Not measured | 1347 | Only Nemotron 3 Super measured |
| LMArena Text: creative writing | Not measured | 1317 | Only Nemotron 3 Super measured |
| LMArena Text: English | Not measured | 1400 | Only Nemotron 3 Super measured |
| LMArena Text: non-English | Not measured | 1356 | Only Nemotron 3 Super measured |
| LMArena Text: Chinese | Not measured | 1431 | Only Nemotron 3 Super measured |
| LMArena Text: German | Not measured | 1341 | Only Nemotron 3 Super measured |
| LMArena Text: French | Not measured | 1403 | Only Nemotron 3 Super measured |
| LMArena Text: Spanish | Not measured | 1418 | Only Nemotron 3 Super measured |
| LMArena Text: Russian | Not measured | 1336 | Only Nemotron 3 Super measured |
| LMArena Text: Polish | Not measured | 1346 | Only Nemotron 3 Super measured |
| LMArena Text: multi-turn | Not measured | 1369 | Only Nemotron 3 Super measured |
| LMArena Text: longer queries | Not measured | 1362 | Only Nemotron 3 Super measured |
| LMArena Text: writing and language | Not measured | 1332 | Only Nemotron 3 Super measured |
| LMArena Text: entertainment and media | Not measured | 1336 | Only Nemotron 3 Super 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 3 2512 | Nemotron 3 Super | 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
Nemotron 3 Super costs less
Repository review
50K input + 3K output tokens
Nemotron 3 Super costs less
Agent loop
200K input + 10K output tokens
Nemotron 3 Super 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 | NVIDIA Nemotron 3 Super |
|---|---|---|
| Maker | Mistral AI | NVIDIA |
| Weights | No public weights listed | Open weights |
| Released | December 1, 2025 | March 11, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.50 | $0.085 |
| Output $/Mtok | $1.50 | $0.45 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.77 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 3 2512 better than Nemotron 3 Super for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Large 3 2512 for work measured by AA Coding Index or AA Intelligence Index, where it leads.
Which is cheaper, Mistral Large 3 2512 or Nemotron 3 Super?
Mistral Large 3 2512 costs $0.50 per million input tokens and $1.50 per million output tokens; Nemotron 3 Super costs $0.085 and $0.45. Cost per solved task is known for Mistral Large 3 2512 only.
Which has the bigger context window, Mistral Large 3 2512 or Nemotron 3 Super?
Neither: both take 262K tokens.
How many benchmarks is the Mistral Large 3 2512 vs Nemotron 3 Super comparison based on?
4 benchmarks have a result for both models as of October 22, 2026. Mistral Large 3 2512's coding index rests on 1 independent benchmark and Nemotron 3 Super's on 0. Where only one model has a result, the page says so instead of naming a winner.