# Kimi K2.7 Code vs Llama 3-8B

> Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 25.3 on the Noometry Index. Llama 3-8B costs 12× 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-3-8b
- Last updated: 2026-10-10
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. Kimi K2.7 Code scores higher in 4 categories and Llama 3-8B in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Kimi K2.7 Code leads 53.6 to 7.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Kimi K2.7 Code and 1.9% for Llama 3-8B.
- Llama 3-8B is cheaper at $0.14 / $0.14 per million input/output tokens, against $0.95 / $4 for Kimi K2.7 Code.
- Kimi K2.7 Code accepts more context: 262K tokens versus 8K.

## Snapshot

| | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| Provider | Moonshot AI | Meta |
| Noometry Index | 43.0 | 25.3 |
| Rank | 90 | 338 |
| Context | 262K | 8K |
| Input $/M | $0.95 | $0.14 |
| Output $/M | $4 | $0.14 |
| Weights | Open | Open |

## Coding

- Kimi K2.7 Code: 42.4 (#92)
- Llama 3-8B: 30.5 (#285)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| LMArena WebDev | 1473 | — |
| SciCode | 47.5% | — |
| WeirdML | 54.1% | — |
| BigCodeBench Instruct | — | 31.9% |
| LMArena Coding | — | 1152 |
| BigCodeBench Complete | — | 36.9% |
| ALE-Bench | 886.23 | — |
| HumanEval+ | — | 56.7% |
| MBPP+ | — | 54.8% |

## Agentic & Tool Use

- Kimi K2.7 Code: 23.9 (#115)
- Llama 3-8B: —

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| APEX-Agents | 37.6% | — |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |

## Reasoning

- Kimi K2.7 Code: 38.2 (#56)
- Llama 3-8B: 13.8 (#321)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| Chess Puzzles | 21% | 0% |
| Epoch Capabilities Index | 150.01 | 116.33 |
| SimpleBench | 57.9% | — |
| CritPt | 10% | — |
| LMArena Hard Prompts | — | 1133 |
| DTBench | — | 43.9% |
| Surface Evolver Bench | 48.8% | — |
| Adversarial NLI | — | 57.3% |
| ForecastBench | — | 58.6 |
| WinoGrande | — | 75.7% |

## Math

- Kimi K2.7 Code: 52.6 (#39)
- Llama 3-8B: 8.3 (#317)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 1.9% |
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |
| LMArena Math | — | 1151 |
| MATH Level 5 | — | 6.1% |

## Knowledge

- Kimi K2.7 Code: 53.6 (#51)
- Llama 3-8B: 7.8 (#303)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| GPQA Diamond | 87.9% | 26.1% |
| SimpleQA Verified | 36.5% | — |
| LMArena Expert | — | 1113 |
| ARC (AI2) Challenge | — | 82.8% |
| MMLU | — | 68.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |

## Multilingual

- Kimi K2.7 Code: —
- Llama 3-8B: 31.0 (#256)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| LMArena Non-English | — | 1098 |
| LMArena Chinese | — | 1076 |
| LMArena French | — | 1158 |
| LMArena German | — | 1104 |
| LMArena Japanese | — | 967 |
| LMArena Korean | — | 1003 |
| LMArena Russian | — | 1109 |
| LMArena Spanish | — | 1172 |

## Instruction Following

- Kimi K2.7 Code: —
- Llama 3-8B: 58.7 (#255)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | — | 1127 |

## Long Context

- Kimi K2.7 Code: —
- Llama 3-8B: 34.2 (#246)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | — | 1128 |

## Writing & Preference

- Kimi K2.7 Code: —
- Llama 3-8B: 37.7 (#251)

| Benchmark | Kimi K2.7 Code | Llama 3-8B |
|---|---|---|
| LMArena Text | — | 1166 |
| LMArena Creative Writing | — | 1150 |
| LMArena Multi-Turn | — | 1152 |

## FAQ

### Is Kimi K2.7 Code better than Llama 3-8B?

Kimi K2.7 Code is the stronger model overall, scoring 43.0 to 25.3 on the Noometry Index. Llama 3-8B costs 12× 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 3-8B?

Llama 3-8B is cheaper. It lists at $0.14 per million input tokens and $0.14 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

### Is Kimi K2.7 Code or Llama 3-8B better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.4 versus 30.5 in the Noometry coding category.

### Which has the bigger context window?

Kimi K2.7 Code does, with 262K tokens against 8K.

### How many benchmarks do Kimi K2.7 Code and Llama 3-8B share?

4 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Llama 3-8B has 34.