Llama 4 Scout vs Mistral Large 3 2512
Mistral Large 3 2512 leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 9.3 to 6.5, and Llama 4 Scout costs 3.0x less per output token ($0.50 vs $1.50 per million). Updated October 21, 2026; 22 benchmarks have a result for both.
Llama 4 Scout or Mistral Large 3 2512: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Llama 4 Scout for output tokens 3.0x cheaper ($0.50 vs $1.50 per million) and a larger context window (1.31M against 262K tokens).
- Shared results
- 22
- Llama 4 Scout only
- 60
- Mistral Large 3 2512 only
- 6
- Like-for-like categories
- 8 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
Mistral Large 3 2512
Mistral Large 3 2512 leads, 9.3 against 6.5.
Same board, both measured
Agentic work
AA Agentic Index
Mistral Large 3 2512
Mistral Large 3 2512 leads, 1.0 against 0.5.
Same board, both measured
Reasoning
GPQA Diamond
Mistral Large 3 2512
Mistral Large 3 2512 leads, 68.4% against 47.0%.
Same board, both measured
Math
AIME
Mistral Large 3 2512
Mistral Large 3 2512 leads, 42.9% against 19.0%.
Same board, both measured
Knowledge
MMLU Pro
Mistral Large 3 2512
Mistral Large 3 2512 leads, 79.8% against 69.6%.
Same board, both measured
Web design
Design Arena: websites
Mistral Large 3 2512
Mistral Large 3 2512 leads, 1162 against 750.
Same board, both measured
Long documents
Listed context window
Llama 4 Scout
Llama 4 Scout takes 1.31M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 4 Scout
Llama 4 Scout $0.0004, Mistral Large 3 2512 $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Mistral Large 3 2512
Llama 4 Scout $1.276, Mistral Large 3 2512 $0.77.
Published attempt cost and pass rate
At a glance
- Coding index
- Llama 4 Scout not benchmarked, Mistral Large 3 2512 not benchmarked.
- Widest category
- Web design, 41.1 points apart on average over 5 shared benchmarks.
- Widest single gap
- Design Arena: websites: Llama 4 Scout 750 against Mistral Large 3 2512 1162, 51.5 points apart on a 0 to 100 scale.
- Output price
- Llama 4 Scout $0.50 against Mistral Large 3 2512 $1.50 per million output tokens, 3.0x apart.
- Context window
- Llama 4 Scout takes 1.31M tokens, Mistral Large 3 2512 262K.
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 | Llama 4 Scout | Bars | Mistral Large 3 2512 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Math | 1 | 1 | ||
| Knowledge | 1 | 5 | ||
| Web design | 0 | 5 | ||
| General | 1 | 2 | ||
| All shared boards | 3 | 19 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SWE-bench Verified | 9.1% | Not measured | Only Llama 4 Scout measured |
| AA Coding Index | 8.2 | 20.1 | Mistral Large 3 2512 |
| LiveCodeBench (Vals AI) | 38.5% | 55.3% | Mistral Large 3 2512 |
| SWE-bench Verified (Vals AI) | Not measured | 41.4% | Only Mistral Large 3 2512 measured |
| LiveCodeBench (Artificial Analysis run) | 29.9% | Not measured | Only Llama 4 Scout measured |
| SciCode | 21.3% | Not measured | Only Llama 4 Scout measured |
| Terminal-Bench Hard (Artificial Analysis run) | 1.5% | Not measured | Only Llama 4 Scout measured |
| ALE-Bench | Not measured | 264.7 | Only Mistral Large 3 2512 measured |
| LMArena Text: coding | 1286 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: software and IT | 1286 | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Intelligence Index | 6.5 | 9.3 | Mistral Large 3 2512 |
| Epoch Capabilities Index | 129.6 | Not measured | Only Llama 4 Scout measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AA Agentic Index | 0.5 | 1.0 | Mistral Large 3 2512 |
| τ²-Bench Telecom | 15.5% | Not measured | Only Llama 4 Scout measured |
| Berkeley Function Calling Leaderboard (BFCL) | 28.1% | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| GPQA Diamond | 47.0% | 68.4% | Mistral Large 3 2512 |
| MMMU Pro (Vals AI) | 58.8% | 66.2% | Mistral Large 3 2512 |
| GPQA Diamond (Artificial Analysis run) | 58.7% | Not measured | Only Llama 4 Scout measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.8% | Not measured | Only Llama 4 Scout measured |
| GPQA Diamond (Epoch AI run) | 51.8% | Not measured | Only Llama 4 Scout measured |
| ARC-AGI | 0.5% | Not measured | Only Llama 4 Scout measured |
| ARC-AGI-2 | 0.0% | Not measured | Only Llama 4 Scout measured |
| LMArena Text: hard prompts | 1266 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: expert | 1235 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: hard prompts in English | 1293 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: diagrams | 1125 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: homework | 1148 | Not measured | Only Llama 4 Scout measured |
| Kagi LLM Benchmark | 36.9% | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 9 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| AIME | 19.0% | 42.9% | Mistral Large 3 2512 |
| MATH 500 (Vals AI) | 79.2% | Not measured | Only Llama 4 Scout measured |
| MGSM (Vals AI) | 88.0% | 85.4% | Llama 4 Scout |
| AA Math Index | 14.0 | Not measured | Only Llama 4 Scout measured |
| AIME 2025 (Artificial Analysis run) | 14.0% | Not measured | Only Llama 4 Scout measured |
| OTIS Mock AIME | 7.8% | Not measured | Only Llama 4 Scout measured |
| MATH level 5 | 62.3% | Not measured | Only Llama 4 Scout measured |
| LMArena Text: math | 1287 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: mathematical work | 1286 | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| MMLU Pro | 69.6% | 79.8% | Mistral Large 3 2512 |
| LegalBench (Vals AI) | 72.0% | 79.1% | Mistral Large 3 2512 |
| CaseLaw (Vals AI) | Not measured | 61.4% | Only Mistral Large 3 2512 measured |
| CorpFin (Vals AI) | 46.8% | 61.0% | Mistral Large 3 2512 |
| TaxEval (Vals AI) | 55.2% | 73.1% | Mistral Large 3 2512 |
| MortgageTax (Vals AI) | 57.8% | 52.1% | Llama 4 Scout |
| MedQA (Vals AI) | 50.9% | 82.2% | Mistral Large 3 2512 |
| MedCode (Vals AI) | 23.3% | Not measured | Only Llama 4 Scout measured |
| MMLU Pro (Artificial Analysis run) | 75.2% | Not measured | Only Llama 4 Scout measured |
| LMArena Text: science | 1278 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: medicine and healthcare | 1275 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: legal and government | 1285 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: business and finance | 1257 | Not measured | Only Llama 4 Scout measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| Design Arena: websites | 750 | 1162 | Mistral Large 3 2512 |
| Design Arena: UI components | 768 | 1102 | Mistral Large 3 2512 |
| Design Arena: game dev | 773 | 1080 | Mistral Large 3 2512 |
| Design Arena: data viz | 896 | 1136 | Mistral Large 3 2512 |
| Design Arena: 3D | Not measured | 1100 | Only Mistral Large 3 2512 measured |
| Design Arena: all code categories | 790 | 1142 | Mistral Large 3 2512 |
| Design Arena: SVG | Not measured | 993 | Only Mistral Large 3 2512 measured |
| Design Arena: ASCII art | Not measured | 1069 | Only Mistral Large 3 2512 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Llama 4 Scout | Mistral Large 3 2512 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 34.8% | 24.6% | Llama 4 Scout |
| MedScribe (Vals AI) | 50.6% | Not measured | Only Llama 4 Scout measured |
| IFBench | 39.5% | Not measured | Only Llama 4 Scout measured |
| Long context reasoning (AA-LCR) | 27.7% | Not measured | Only Llama 4 Scout measured |
| DTBench | 57.9% | 65.1% | Mistral Large 3 2512 |
| LMCA | 12.0% | 16.7% | Mistral Large 3 2512 |
| Fiction.LiveBench | 36.0% | Not measured | Only Llama 4 Scout measured |
| LMArena Text | 1279 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: instruction following | 1248 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: creative writing | 1249 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision | 1118 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: English | 1304 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: non-English | 1252 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: Chinese | 1255 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: German | 1273 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: Japanese | 1206 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: Korean | 1207 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: French | 1283 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: Spanish | 1278 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: Russian | 1263 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: Polish | 1265 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: multi-turn | 1280 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: longer queries | 1265 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: writing and language | 1269 | Not measured | Only Llama 4 Scout measured |
| LMArena Text: entertainment and media | 1242 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: English | 1143 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: Chinese | 1106 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: reading text | 1117 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: humor | 1102 | Not measured | Only Llama 4 Scout measured |
| LMArena Vision: creative writing | 1126 | Not measured | Only Llama 4 Scout 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 | Llama 4 Scout | Mistral Large 3 2512 | 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
Llama 4 Scout costs less
Repository review
50K input + 3K output tokens
Llama 4 Scout costs less
Agent loop
200K input + 10K output tokens
Llama 4 Scout 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 | Meta Llama 4 Scout | Mistral Large 3 2512 |
|---|---|---|
| Maker | Meta Llama | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | April 5, 2025 | December 1, 2025 |
| Context window | 1.31M | 262K |
| Input $/Mtok | $0.175 | $0.50 |
| Output $/Mtok | $0.50 | $1.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | $1.276 | $0.77 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 4 Scout better than Mistral Large 3 2512 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 4 Scout for output tokens 3.0x cheaper ($0.50 vs $1.50 per million) and a larger context window (1.31M against 262K tokens).
Which is cheaper, Llama 4 Scout or Mistral Large 3 2512?
Llama 4 Scout costs $0.175 per million input tokens and $0.50 per million output tokens; Mistral Large 3 2512 costs $0.50 and $1.50. Per solved SWE-bench Verified task, Llama 4 Scout costs $1.276 and Mistral Large 3 2512 $0.77.
Which has the bigger context window, Llama 4 Scout or Mistral Large 3 2512?
Llama 4 Scout, with 1.31M tokens against 262K.
How many benchmarks is the Llama 4 Scout vs Mistral Large 3 2512 comparison based on?
22 benchmarks have a result for both models as of October 21, 2026. Llama 4 Scout's coding index rests on 0 independent benchmarks and Mistral Large 3 2512's on 1. Where only one model has a result, the page says so instead of naming a winner.