# Kimi K2.7 Code vs Llama 3.1-70B

> Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 29.6 on the Noometry Index. Llama 3.1-70B costs 4.3× 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-3-1-70b
- Last updated: 2026-10-11
- Shared benchmarks: 4

## Summary

- They share 4 benchmarks with published results for both. Kimi K2.7 Code scores higher in 4 categories and Llama 3.1-70B in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2.7 Code leads 52.9 to 13.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 95.6% for Kimi K2.7 Code and 3.6% for Llama 3.1-70B.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 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 3.1-70B |
|---|---|---|
| Provider | Moonshot AI | Meta |
| Noometry Index | 43.3 | 29.6 |
| Rank | 94 | 308 |
| Context | 262K | 128K |
| Input $/M | $0.95 | $0.40 |
| Output $/M | $4 | $0.40 |
| Weights | Open | Open |

## Coding

- Kimi K2.7 Code: 42.9 (#95)
- Llama 3.1-70B: 30.3 (#296)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| WeirdML | 54.1% | 9% |
| DeepSWE | 30.5% | — |
| FrontierCode | 30.1% | — |
| LMArena WebDev | 1473 | — |
| SciCode | 47.5% | — |
| BigCodeBench Instruct | — | 46.1% |
| LMArena Coding | — | 1260 |
| BigCodeBench Complete | — | 54.8% |
| ALE-Bench | 886.23 | — |

## Agentic & Tool Use

- Kimi K2.7 Code: 24.0 (#122)
- Llama 3.1-70B: 25.1 (#112)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| APEX-Agents | 37.6% | — |
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |
| GBAEval | 0.9% | — |
| Vending-Bench 2 | 5,083 | — |

## Reasoning

- Kimi K2.7 Code: 39.0 (#61)
- Llama 3.1-70B: 21.6 (#220)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| Epoch Capabilities Index | 149.97 | 125.92 |
| SimpleBench | 57.9% | — |
| CritPt | 10% | — |
| Chess Puzzles | 21% | — |
| LMArena Hard Prompts | — | 1241 |
| DTBench | — | 60% |
| LMCA | — | 14.8% |
| Surface Evolver Bench | 48.8% | — |

## Math

- Kimi K2.7 Code: 52.9 (#48)
- Llama 3.1-70B: 13.5 (#304)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 95.6% | 3.6% |
| FrontierMath (Tiers 1-3) | 54% | — |
| FrontierMath Tier 4 | 12.2% | — |
| Omni-MATH | — | 21% |
| LMArena Math | — | 1252 |
| MATH Level 5 | — | 36.7% |

## Knowledge

- Kimi K2.7 Code: 53.5 (#57)
- Llama 3.1-70B: 24.2 (#269)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| GPQA Diamond | 87.9% | 44.2% |
| SimpleQA Verified | 36.5% | — |
| MMLU-Pro | — | 65.3% |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1209 |
| MMLU | — | 80.1% |

## Multilingual

- Kimi K2.7 Code: —
- Llama 3.1-70B: 38.8 (#225)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | — | 1219 |
| LMArena Chinese | — | 1215 |
| LMArena French | — | 1261 |
| LMArena German | — | 1222 |
| LMArena Japanese | — | 1132 |
| LMArena Korean | — | 1140 |
| LMArena Russian | — | 1234 |
| LMArena Spanish | — | 1253 |

## Instruction Following

- Kimi K2.7 Code: —
- Llama 3.1-70B: 65.3 (#223)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| IFEval | — | 82.1% |
| LMArena Instruction Following | — | 1231 |

## Long Context

- Kimi K2.7 Code: —
- Llama 3.1-70B: 37.6 (#214)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | — | 1241 |

## Writing & Preference

- Kimi K2.7 Code: —
- Llama 3.1-70B: 35.4 (#267)

| Benchmark | Kimi K2.7 Code | Llama 3.1-70B |
|---|---|---|
| LMArena Text | — | 1261 |
| LMArena Creative Writing | — | 1232 |
| EQ-Bench Creative Writing | — | 784 |
| WildBench | — | 75.8% |
| LMArena Multi-Turn | — | 1256 |

## FAQ

### Is Kimi K2.7 Code better than Llama 3.1-70B?

Kimi K2.7 Code is the stronger model overall, scoring 43.3 to 29.6 on the Noometry Index. Llama 3.1-70B costs 4.3× 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 3.1-70B?

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Kimi K2.7 Code lists at $0.95 and $4.

### Is Kimi K2.7 Code or Llama 3.1-70B better for coding?

Kimi K2.7 Code scores higher on coding benchmarks: 42.9 versus 30.3 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 3.1-70B share?

4 benchmarks have published results for both models. Kimi K2.7 Code has 19 scored results on Noometry and Llama 3.1-70B has 35.