# Kimi K2.7 Code vs Llama 4 Scout

> Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 27.4 on the Noometry Index. Llama 4 Scout costs 11× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/kimi-k2-7-code-vs-llama-4-scout
- Last updated: 2026-10-10
- Shared benchmarks: 5

## Summary

- They share 5 benchmarks with published results for both. Kimi K2.7 Code scores higher in 4 categories and Llama 4 Scout in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.6 to 18.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Kimi K2.7 Code and 7.8% for Llama 4 Scout.
- Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 128K.

## Snapshot

| | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| Provider | Moonshot AI | Meta |
| Noometry Index | 43.0 | 27.4 |
| Rank | 90 | 323 |
| Context | 262K | 128K |
| Input $/M | $0.95 | $0.10 |
| Output $/M | $4 | $0.30 |
| Weights | Open | Open |

## Coding

- Kimi K2.7 Code: 42.4 (#92)
- Llama 4 Scout: 19.9 (#334)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| SciCode | 47.5% | 17% |
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| SWE-bench Verified (bash only) | — | 9.1% |
| LMArena WebDev | 1473 | — |
| WeirdML | 54.1% | — |
| LMArena Coding | — | 1286 |
| BigCodeBench Complete | — | 43.1% |
| ALE-Bench | 886.23 | — |

## Agentic & Tool Use

- Kimi K2.7 Code: 23.9 (#115)
- Llama 4 Scout: 24.4 (#109)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| APEX-Agents | 37.6% | — |
| Berkeley Function Calling Leaderboard | — | 28.1% |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |

## Reasoning

- Kimi K2.7 Code: 38.2 (#56)
- Llama 4 Scout: 9.2 (#339)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| CritPt | 10% | 0% |
| Epoch Capabilities Index | 150.01 | 129.64 |
| ARC-AGI-2 | — | 0% |
| SimpleBench | 57.9% | — |
| Kagi LLM Benchmark | — | 36.9% |
| ARC-AGI-1 | — | 0.5% |
| Chess Puzzles | 21% | — |
| LMArena Hard Prompts | — | 1266 |
| DTBench | — | 57.9% |
| LMCA | — | 12% |
| Surface Evolver Bench | 48.8% | — |
| ForecastBench | — | 57.5 |

## Math

- Kimi K2.7 Code: 52.6 (#39)
- Llama 4 Scout: 18.4 (#280)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 7.8% |
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |
| Omni-MATH | — | 37.3% |
| LMArena Math | — | 1286 |
| MATH Level 5 | — | 62.3% |
| FrontierMath (Feb 2025 set) | — | 0% |

## Knowledge

- Kimi K2.7 Code: 53.6 (#51)
- Llama 4 Scout: 31.8 (#208)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| GPQA Diamond | 87.9% | 51.8% |
| SimpleQA Verified | 36.5% | — |
| MMLU-Pro | — | 74.2% |
| Vectara Hallucination Rate | — | 7.7% |
| GPQA (HELM) | — | 50.7% |
| LMArena Expert | — | 1236 |

## Multimodal

- Kimi K2.7 Code: —
- Llama 4 Scout: 31.6 (#98)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| LMArena Vision | — | 1118 |
| SpatialViz-Bench | — | 34.2% |

## Multilingual

- Kimi K2.7 Code: —
- Llama 4 Scout: 41.3 (#207)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| LMArena Non-English | — | 1253 |
| LMArena Chinese | — | 1256 |
| LMArena French | — | 1283 |
| LMArena German | — | 1274 |
| LMArena Japanese | — | 1209 |
| LMArena Korean | — | 1207 |
| LMArena Russian | — | 1263 |
| LMArena Spanish | — | 1277 |

## Instruction Following

- Kimi K2.7 Code: —
- Llama 4 Scout: 66.0 (#212)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| IFEval | — | 81.8% |
| LMArena Instruction Following | — | 1248 |

## Long Context

- Kimi K2.7 Code: —
- Llama 4 Scout: 27.5 (#289)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| Fiction.LiveBench | — | 36% |
| LMArena Longer Query | — | 1265 |

## Writing & Preference

- Kimi K2.7 Code: —
- Llama 4 Scout: 37.1 (#256)

| Benchmark | Kimi K2.7 Code | Llama 4 Scout |
|---|---|---|
| LMArena Text | — | 1279 |
| LMArena Creative Writing | — | 1249 |
| EQ-Bench Creative Writing | — | 783 |
| WildBench | — | 78% |
| LMArena Multi-Turn | — | 1281 |

## FAQ

### Is Kimi K2.7 Code better than Llama 4 Scout?

Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 27.4 on the Noometry Index. Llama 4 Scout costs 11× less per token, which makes it the better buy when Kimi K2.7 Code's lead doesn't matter for your workload.

### Which is cheaper, Kimi K2.7 Code or Llama 4 Scout?

Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

### Is Kimi K2.7 Code or Llama 4 Scout better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.4 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

Kimi K2.7 Code does, with 262K tokens against 128K.

### How many benchmarks do Kimi K2.7 Code and Llama 4 Scout share?

5 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Llama 4 Scout has 43.