# Hy3 vs Llama 3.2 3B

> Hy3 is the stronger model overall, scoring 44.2 to 28.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/hy3-vs-llama-3-2-3b
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Hy3 scores higher in 8 categories and Llama 3.2 3B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Hy3 leads 62.2 to 24.7.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.0825 / $0.33 for Hy3.
- Hy3 accepts more context: 262K tokens versus 131K.

## Snapshot

| | Hy3 | Llama 3.2 3B |
|---|---|---|
| Provider | Tencent | Meta |
| Noometry Index | 44.2 | 28.9 |
| Rank | 79 | 321 |
| Context | 262K | 131K |
| Input $/M | $0.0825 | $0.05 |
| Output $/M | $0.33 | $0.33 |
| Weights | Open | Open |

## Coding

- Hy3: 46.8 (#63)
- Llama 3.2 3B: 27.6 (#319)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1464 | 1098 |
| LMArena WebDev | 1508 | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |

## Agentic & Tool Use

- Hy3: —
- Llama 3.2 3B: 20.1 (#143)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 21.9% |
| BALROG | — | 10.1% |

## Reasoning

- Hy3: 26.1 (#136)
- Llama 3.2 3B: 21.0 (#228)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1447 | 1095 |
| NYT Connections (extended) | 41.2% | — |

## Math

- Hy3: 40.1 (#93)
- Llama 3.2 3B: 32.4 (#214)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1475 | 1126 |

## Knowledge

- Hy3: 40.8 (#114)
- Llama 3.2 3B: 29.7 (#235)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1460 | 1090 |

## Multilingual

- Hy3: 53.5 (#65)
- Llama 3.2 3B: 26.2 (#281)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1426 | 1019 |
| LMArena Chinese | 1493 | 1017 |
| LMArena German | 1439 | 1056 |
| LMArena Russian | 1432 | 949 |
| LMArena French | 1461 | — |
| LMArena Japanese | 1392 | — |
| LMArena Korean | 1395 | — |
| LMArena Spanish | 1456 | — |

## Instruction Following

- Hy3: 75.1 (#70)
- Llama 3.2 3B: 56.0 (#275)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1426 | 1089 |

## Long Context

- Hy3: 44.1 (#75)
- Llama 3.2 3B: 33.4 (#261)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1442 | 1100 |

## Writing & Preference

- Hy3: 62.2 (#81)
- Llama 3.2 3B: 24.7 (#307)

| Benchmark | Hy3 | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1439 | 1110 |
| LMArena Creative Writing | 1402 | 1094 |
| LMArena Multi-Turn | 1436 | 1105 |
| EQ-Bench Creative Writing | — | 595 |

## FAQ

### Is Hy3 better than Llama 3.2 3B?

Hy3 is the stronger model overall, scoring 44.2 to 28.9 on the Noometry Index.

### Which is cheaper, Hy3 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; Hy3 lists at $0.0825 and $0.33.

### Is Hy3 or Llama 3.2 3B better for coding?

Hy3 scores higher on coding benchmarks: 46.8 versus 27.6 in the Noometry coding category.

### Which has the bigger context window?

Hy3 does, with 262K tokens against 131K.

### How many benchmarks do Hy3 and Llama 3.2 3B share?

13 benchmarks have published results for both models. Hy3 has 19 scored results on Noometry and Llama 3.2 3B has 18.