# Kimi K2 (Jul 2025) vs Llama 3.2 3B

> Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 28.9 on the Noometry Index. Llama 3.2 3B costs 8.4× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/kimi-k2-vs-llama-3-2-3b
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. Kimi K2 (Jul 2025) scores higher in 9 categories and Llama 3.2 3B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Kimi K2 (Jul 2025) leads 62.3 to 24.7.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 59.1% for Kimi K2 (Jul 2025) and 21.9% for Llama 3.2 3B.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 131K.

## Snapshot

| | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| Provider | Moonshot AI | Meta |
| Noometry Index | 41.2 | 28.9 |
| Rank | 140 | 321 |
| Context | 262K | 131K |
| Input $/M | $0.57 | $0.05 |
| Output $/M | $2.30 | $0.33 |
| Weights | Open | Open |

## Coding

- Kimi K2 (Jul 2025): 42.4 (#102)
- Llama 3.2 3B: 27.6 (#319)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1399 | 1098 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |
| ALE-Bench | 597.5 | — |

## Agentic & Tool Use

- Kimi K2 (Jul 2025): 32.4 (#64)
- Llama 3.2 3B: 20.1 (#143)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 59.1% | 21.9% |
| Terminal-Bench | 35.7% | — |
| BALROG | — | 10.1% |
| METR Time Horizons | 59.2% | — |

## Reasoning

- Kimi K2 (Jul 2025): 23.3 (#179)
- Llama 3.2 3B: 21.0 (#228)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1384 | 1095 |
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| Epoch Capabilities Index | 146.01 | — |
| ForecastBench | 60.2 | — |

## Math

- Kimi K2 (Jul 2025): 42.7 (#83)
- Llama 3.2 3B: 32.4 (#214)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1397 | 1126 |
| Omni-MATH | 65.4% | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- Kimi K2 (Jul 2025): 37.3 (#157)
- Llama 3.2 3B: 29.7 (#235)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1365 | 1090 |
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |

## Multilingual

- Kimi K2 (Jul 2025): 49.6 (#130)
- Llama 3.2 3B: 26.2 (#281)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1372 | 1019 |
| LMArena Chinese | 1415 | 1017 |
| LMArena German | 1387 | 1056 |
| LMArena Russian | 1385 | 949 |
| LMArena French | 1379 | — |
| LMArena Japanese | 1349 | — |
| LMArena Korean | 1325 | — |
| LMArena Spanish | 1386 | — |

## Instruction Following

- Kimi K2 (Jul 2025): 71.1 (#156)
- Llama 3.2 3B: 56.0 (#275)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1348 | 1089 |
| IFEval | 85% | — |

## Long Context

- Kimi K2 (Jul 2025): 41.2 (#145)
- Llama 3.2 3B: 33.4 (#261)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1353 | 1100 |
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |

## Writing & Preference

- Kimi K2 (Jul 2025): 62.3 (#78)
- Llama 3.2 3B: 24.7 (#307)

| Benchmark | Kimi K2 (Jul 2025) | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1380 | 1110 |
| LMArena Creative Writing | 1350 | 1094 |
| EQ-Bench Creative Writing | 1666 | 595 |
| LMArena Multi-Turn | 1371 | 1105 |
| Short-Story Creative Writing | 85.6% | — |
| WildBench | 86.2% | — |

## FAQ

### Is Kimi K2 (Jul 2025) better than Llama 3.2 3B?

Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 28.9 on the Noometry Index. Llama 3.2 3B costs 8.4× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.

### Which is cheaper, Kimi K2 (Jul 2025) or Llama 3.2 3B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.

### Is Kimi K2 (Jul 2025) or Llama 3.2 3B better for coding?

Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 27.6 in the Noometry coding category.

### Which has the bigger context window?

Kimi K2 (Jul 2025) does, with 262K tokens against 131K.

### How many benchmarks do Kimi K2 (Jul 2025) and Llama 3.2 3B share?

15 benchmarks have published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Llama 3.2 3B has 18.