# Kimi K2.7 Code vs Llama 3.1-8B

> Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 23.0 on the Noometry Index. Llama 3.1-8B costs 30× 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-3-1-8b
- Last updated: 2026-10-11
- Shared benchmarks: 7

## Summary

- They share 7 benchmarks with published results for both. Kimi K2.7 Code scores higher in 5 categories and Llama 3.1-8B in 0 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Kimi K2.7 Code leads 53.5 to 8.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Kimi K2.7 Code and 1.7% for Llama 3.1-8B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 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 3.1-8B |
|---|---|---|
| Provider | Moonshot AI | Meta |
| Noometry Index | 43.3 | 23.0 |
| Rank | 94 | 352 |
| Context | 262K | 128K |
| Input $/M | $0.95 | $0.05 |
| Output $/M | $4 | $0.08 |
| Weights | Open | Open |

## Coding

- Kimi K2.7 Code: 42.9 (#95)
- Llama 3.1-8B: 20.2 (#340)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| SciCode | 47.5% | 13.2% |
| WeirdML | 54.1% | 1.7% |
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| LMArena WebDev | 1473 | — |
| BigCodeBench Instruct | — | 32.8% |
| LMArena Coding | — | 1195 |
| BigCodeBench Complete | — | 40.5% |
| ALE-Bench | 886.23 | — |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |

## Agentic & Tool Use

- Kimi K2.7 Code: 24.0 (#122)
- Llama 3.1-8B: 22.5 (#131)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| APEX-Agents | 37.6% | — |
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |

## Reasoning

- Kimi K2.7 Code: 39.0 (#61)
- Llama 3.1-8B: 14.9 (#321)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| CritPt | 10% | 0% |
| Chess Puzzles | 21% | 0% |
| Epoch Capabilities Index | 149.97 | 116.57 |
| SimpleBench | 57.9% | — |
| LMArena Hard Prompts | — | 1175 |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Surface Evolver Bench | 48.8% | — |
| PIQA | — | 81.2% |

## Math

- Kimi K2.7 Code: 52.9 (#48)
- Llama 3.1-8B: 10.2 (#317)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 1.7% |
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |
| Omni-MATH | — | 13.7% |
| LMArena Math | — | 1179 |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |

## Knowledge

- Kimi K2.7 Code: 53.5 (#57)
- Llama 3.1-8B: 8.0 (#307)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| GPQA Diamond | 87.9% | 27% |
| SimpleQA Verified | 36.5% | — |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| LMArena Expert | — | 1144 |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |

## Multilingual

- Kimi K2.7 Code: —
- Llama 3.1-8B: 34.0 (#249)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | — | 1148 |
| LMArena Chinese | — | 1151 |
| LMArena French | — | 1177 |
| LMArena German | — | 1144 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1053 |
| LMArena Russian | — | 1158 |
| LMArena Spanish | — | 1169 |

## Instruction Following

- Kimi K2.7 Code: —
- Llama 3.1-8B: 58.9 (#258)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| IFEval | — | 74.3% |
| LMArena Instruction Following | — | 1159 |

## Long Context

- Kimi K2.7 Code: —
- Llama 3.1-8B: 35.8 (#238)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | — | 1182 |

## Writing & Preference

- Kimi K2.7 Code: —
- Llama 3.1-8B: 29.7 (#290)

| Benchmark | Kimi K2.7 Code | Llama 3.1-8B |
|---|---|---|
| LMArena Text | — | 1187 |
| LMArena Creative Writing | — | 1154 |
| EQ-Bench Creative Writing | — | 713 |
| WildBench | — | 68.7% |
| LMArena Multi-Turn | — | 1172 |

## FAQ

### Is Kimi K2.7 Code better than Llama 3.1-8B?

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 23.0 on the Noometry Index. Llama 3.1-8B costs 30× 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 3.1-8B?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

### Is Kimi K2.7 Code or Llama 3.1-8B better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 20.2 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 3.1-8B share?

7 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Llama 3.1-8B has 43.