Kimi K2 0711 vs Llama 4 Scout
Kimi K2 0711 leads Llama 4 Scout on the Artificial Analysis Intelligence Index, 12.7 to 6.5, and Llama 4 Scout costs 4.6x less per output token ($0.50 vs $2.30 per million). Updated October 22, 2026; 30 benchmarks have a result for both.
Kimi K2 0711 or Llama 4 Scout: which to pick
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
- 30
- Kimi K2 0711 only
- 7
- Llama 4 Scout only
- 52
- 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
Kimi K2 0711
Kimi K2 0711 leads, 12.7 against 6.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Llama 4 Scout has a AA Agentic Index result, 0.5.
Directional only
Reasoning
GPQA Diamond
Kimi K2 0711
Kimi K2 0711 leads, 71.5% against 47.0%.
Same board, both measured
Math
AIME
Kimi K2 0711
Kimi K2 0711 leads, 62.7% against 19.0%.
Same board, both measured
Knowledge
MMLU Pro
Kimi K2 0711
Kimi K2 0711 leads, 79.4% against 69.6%.
Same board, both measured
Web design
Design Arena: websites
Kimi K2 0711
Kimi K2 0711 leads, 1050 against 750.
Same board, both measured
Long documents
Listed context window
Llama 4 Scout
Llama 4 Scout takes 1.31M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 4 Scout
Kimi K2 0711 $0.0017, Llama 4 Scout $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Llama 4 Scout has the number, $1.276.
Directional only
At a glance
- Coding index
- Kimi K2 0711 not benchmarked, Llama 4 Scout not benchmarked.
- Widest category
- Agentic work, 45.6 points apart on average over 1 shared benchmark.
- Widest single gap
- SWE-bench Verified: Kimi K2 0711 71.2% against Llama 4 Scout 9.1%, 62.1 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0711 $2.30 against Llama 4 Scout $0.50 per million output tokens, 4.6x apart.
- Context window
- Kimi K2 0711 takes 131K tokens, Llama 4 Scout 1.31M.
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 | Kimi K2 0711 | Bars | Llama 4 Scout | Ties |
|---|---|---|---|---|
| Coding | 4 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 4 | 0 | ||
| Math | 5 | 0 | ||
| Knowledge | 6 | 0 | ||
| Web design | 5 | 0 | ||
| General | 3 | 0 | ||
| All shared boards | 30 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| Aider polyglot | 59.1% | Not measured | Only Kimi K2 0711 measured |
| SWE-bench Verified | 71.2% | 9.1% | Kimi K2 0711 |
| AA Coding Index | Not measured | 8.2 | Only Llama 4 Scout measured |
| LiveCodeBench (Vals AI) | 70.5% | 38.5% | Kimi K2 0711 |
| LiveCodeBench (Artificial Analysis run) | 55.6% | 29.9% | Kimi K2 0711 |
| SciCode | Not measured | 21.3% | Only Llama 4 Scout measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | 1.5% | Kimi K2 0711 |
| Terminal-Bench | 27.8% | Not measured | Only Kimi K2 0711 measured |
| GSO-Bench | 4.9% | Not measured | Only Kimi K2 0711 measured |
| WeirdML | 39.4% | Not measured | Only Kimi K2 0711 measured |
| LMArena Text: coding | Not measured | 1286 | Only Llama 4 Scout measured |
| LMArena Text: software and IT | Not measured | 1286 | Only Llama 4 Scout measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | 6.5 | Kimi K2 0711 |
| Epoch Capabilities Index | 140.0 | 129.6 | Kimi K2 0711 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.5 | Only Llama 4 Scout measured |
| τ²-Bench Telecom | 61.1% | 15.5% | Kimi K2 0711 |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 28.1% | 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 index40
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| GPQA Diamond | 71.5% | 47.0% | Kimi K2 0711 |
| MMMU Pro (Vals AI) | Not measured | 58.8% | Only Llama 4 Scout measured |
| GPQA Diamond (Artificial Analysis run) | 76.6% | 58.7% | Kimi K2 0711 |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | 3.8% | Kimi K2 0711 |
| GPQA Diamond (Epoch AI run) | Not measured | 51.8% | Only Llama 4 Scout measured |
| ARC-AGI | Not measured | 0.5% | Only Llama 4 Scout measured |
| ARC-AGI-2 | Not measured | 0.0% | Only Llama 4 Scout measured |
| SimpleBench | 26.3% | Not measured | Only Kimi K2 0711 measured |
| LMArena Text: hard prompts | Not measured | 1266 | Only Llama 4 Scout measured |
| LMArena Text: expert | Not measured | 1235 | Only Llama 4 Scout measured |
| LMArena Text: hard prompts in English | Not measured | 1293 | Only Llama 4 Scout measured |
| LMArena Vision: diagrams | Not measured | 1125 | Only Llama 4 Scout measured |
| LMArena Vision: homework | Not measured | 1148 | Only Llama 4 Scout measured |
| Kagi LLM Benchmark | 64.4% | 36.9% | Kimi K2 0711 |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| AIME | 62.7% | 19.0% | Kimi K2 0711 |
| MATH 500 (Vals AI) | 94.2% | 79.2% | Kimi K2 0711 |
| MGSM (Vals AI) | 91.0% | 88.0% | Kimi K2 0711 |
| AA Math Index | 57.0 | 14.0 | Kimi K2 0711 |
| AIME 2025 (Artificial Analysis run) | 57.0% | 14.0% | Kimi K2 0711 |
| OTIS Mock AIME | Not measured | 7.8% | Only Llama 4 Scout measured |
| MATH level 5 | Not measured | 62.3% | Only Llama 4 Scout measured |
| LMArena Text: math | Not measured | 1287 | Only Llama 4 Scout measured |
| LMArena Text: mathematical work | Not measured | 1286 | 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 index60
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| MMLU Pro | 79.4% | 69.6% | Kimi K2 0711 |
| LegalBench (Vals AI) | 81.5% | 72.0% | Kimi K2 0711 |
| CorpFin (Vals AI) | 50.4% | 46.8% | Kimi K2 0711 |
| TaxEval (Vals AI) | 70.2% | 55.2% | Kimi K2 0711 |
| MortgageTax (Vals AI) | Not measured | 57.8% | Only Llama 4 Scout measured |
| MedQA (Vals AI) | 84.0% | 50.9% | Kimi K2 0711 |
| MedCode (Vals AI) | Not measured | 23.3% | Only Llama 4 Scout measured |
| MMLU Pro (Artificial Analysis run) | 82.4% | 75.2% | Kimi K2 0711 |
| LMArena Text: science | Not measured | 1278 | Only Llama 4 Scout measured |
| LMArena Text: medicine and healthcare | Not measured | 1275 | Only Llama 4 Scout measured |
| LMArena Text: legal and government | Not measured | 1285 | Only Llama 4 Scout measured |
| LMArena Text: business and finance | Not measured | 1257 | Only Llama 4 Scout measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| Design Arena: websites | 1050 | 750 | Kimi K2 0711 |
| Design Arena: UI components | 1027 | 765 | Kimi K2 0711 |
| Design Arena: game dev | 973 | 772 | Kimi K2 0711 |
| Design Arena: data viz | 1018 | 896 | Kimi K2 0711 |
| Design Arena: all code categories | 1033 | 789 | Kimi K2 0711 |
| Neither model has a result on the other 4 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Kimi K2 0711 | Llama 4 Scout | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 34.8% | Only Llama 4 Scout measured |
| MedScribe (Vals AI) | Not measured | 50.6% | Only Llama 4 Scout measured |
| IFBench | 41.5% | 39.5% | Kimi K2 0711 |
| Long context reasoning (AA-LCR) | 53.0% | 27.7% | Kimi K2 0711 |
| DTBench | Not measured | 57.9% | Only Llama 4 Scout measured |
| LMCA | Not measured | 12.0% | Only Llama 4 Scout measured |
| Fiction.LiveBench | 61.1% | 36.0% | Kimi K2 0711 |
| Creative writing (Lech Mazur) | 85.6% | Not measured | Only Kimi K2 0711 measured |
| CL-bench | 11.9% | Not measured | Only Kimi K2 0711 measured |
| LMArena Text | Not measured | 1279 | Only Llama 4 Scout measured |
| LMArena Text: instruction following | Not measured | 1248 | Only Llama 4 Scout measured |
| LMArena Text: creative writing | Not measured | 1249 | Only Llama 4 Scout measured |
| LMArena Vision | Not measured | 1118 | Only Llama 4 Scout measured |
| LMArena Text: English | Not measured | 1304 | Only Llama 4 Scout measured |
| LMArena Text: non-English | Not measured | 1252 | Only Llama 4 Scout measured |
| LMArena Text: Chinese | Not measured | 1255 | Only Llama 4 Scout measured |
| LMArena Text: German | Not measured | 1273 | Only Llama 4 Scout measured |
| LMArena Text: Japanese | Not measured | 1206 | Only Llama 4 Scout measured |
| LMArena Text: Korean | Not measured | 1207 | Only Llama 4 Scout measured |
| LMArena Text: French | Not measured | 1283 | Only Llama 4 Scout measured |
| LMArena Text: Spanish | Not measured | 1278 | Only Llama 4 Scout measured |
| LMArena Text: Russian | Not measured | 1263 | Only Llama 4 Scout measured |
| LMArena Text: Polish | Not measured | 1265 | Only Llama 4 Scout measured |
| LMArena Text: multi-turn | Not measured | 1280 | Only Llama 4 Scout measured |
| LMArena Text: longer queries | Not measured | 1265 | Only Llama 4 Scout measured |
| LMArena Text: writing and language | Not measured | 1269 | Only Llama 4 Scout measured |
| LMArena Text: entertainment and media | Not measured | 1242 | Only Llama 4 Scout measured |
| LMArena Vision: English | Not measured | 1143 | Only Llama 4 Scout measured |
| LMArena Vision: Chinese | Not measured | 1106 | Only Llama 4 Scout measured |
| LMArena Vision: reading text | Not measured | 1117 | Only Llama 4 Scout measured |
| LMArena Vision: humor | Not measured | 1102 | Only Llama 4 Scout measured |
| LMArena Vision: creative writing | Not measured | 1126 | Only Llama 4 Scout measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2 0711 | Llama 4 Scout | 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 | MoonshotAI Kimi K2 0711 | Meta Llama 4 Scout |
|---|---|---|
| Maker | Moonshot AI | Meta Llama |
| Weights | Open weights | Open weights |
| Released | July 11, 2025 | April 5, 2025 |
| Context window | 131K | 1.31M |
| Input $/Mtok | $0.57 | $0.175 |
| Output $/Mtok | $2.30 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | $1.276 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2 0711 better than Llama 4 Scout 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, Kimi K2 0711 or Llama 4 Scout?
Kimi K2 0711 costs $0.57 per million input tokens and $2.30 per million output tokens; Llama 4 Scout costs $0.175 and $0.50. Cost per solved task is known for Llama 4 Scout only.
Which has the bigger context window, Kimi K2 0711 or Llama 4 Scout?
Llama 4 Scout, with 1.31M tokens against 131K.
How many benchmarks is the Kimi K2 0711 vs Llama 4 Scout comparison based on?
30 benchmarks have a result for both models as of October 22, 2026. Kimi K2 0711's coding index rests on 0 independent benchmarks and Llama 4 Scout's on 0. Where only one model has a result, the page says so instead of naming a winner.