# Llama-3.3-70B-Instruct vs Qwen2.5 32B Instruct

> Llama-3.3-70B-Instruct and Qwen2.5 32B Instruct score almost the same on the Noometry Index (30.6 vs 30.1), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/llama-3-3-70b-instruct-vs-qwen2-5-32b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 6

## Summary

- They share 6 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 1 category and Qwen2.5 32B Instruct in 3 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in coding, where Qwen2.5 32B Instruct leads 38.7 to 31.0.
- The biggest single-benchmark swing is MATH Level 5: 41.6% for Llama-3.3-70B-Instruct and 56.1% for Qwen2.5 32B Instruct.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.70 / $2.80 for Qwen2.5 32B Instruct.
- Qwen2.5 32B Instruct accepts more context: 131K tokens versus 128K.

## Snapshot

| | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.6 | 30.1 |
| Rank | 291 | 297 |
| Context | 128K | 131K |
| Input $/M | $0.10 | $0.70 |
| Output $/M | $0.32 | $2.80 |
| Weights | Open | Open |

## Coding

- Llama-3.3-70B-Instruct: 31.0 (#290)
- Qwen2.5 32B Instruct: 38.7 (#169)

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| BigCodeBench Instruct | 46.9% | 45% |
| BigCodeBench Complete | 57.5% | 52.3% |
| SciCode | 26% | — |
| WeirdML | 14.4% | — |
| LiveBench Coding | 36.6% | — |
| LMArena Coding | 1268 | — |

## Agentic & Tool Use

- Llama-3.3-70B-Instruct: 25.8 (#105)
- Qwen2.5 32B Instruct: —

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| BALROG | 23% | — |

## Reasoning

- Llama-3.3-70B-Instruct: 14.1 (#327)
- Qwen2.5 32B Instruct: 19.2 (#266)

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| Epoch Capabilities Index | 127.33 | 128.52 |
| SimpleBench | 19.9% | — |
| CritPt | 0% | — |
| Chess Puzzles | — | 0% |
| LiveBench Reasoning | 50.8% | — |
| LMArena Hard Prompts | 1257 | — |
| DTBench | 59.5% | — |
| LiveBench Data Analysis | 49.5% | — |
| LMCA | 17.5% | — |
| ForecastBench | 58.6 | — |
| LiveBench | 50.2% | — |

## Math

- Llama-3.3-70B-Instruct: 15.3 (#298)
- Qwen2.5 32B Instruct: 16.2 (#296)

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | 7.4% |
| MATH Level 5 | 41.6% | 56.1% |
| LiveBench Math | 42.2% | — |
| LMArena Math | 1267 | — |

## Knowledge

- Llama-3.3-70B-Instruct: 30.6 (#226)
- Qwen2.5 32B Instruct: 24.9 (#266)

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| GPQA Diamond | 47.4% | 46.1% |
| Confabulations | 22.8% | — |
| Vectara Hallucination Rate | 4.1% | — |
| LMArena Expert | 1225 | — |
| MMLU | 86.3% | — |

## Multilingual

- Llama-3.3-70B-Instruct: 39.9 (#220)
- Qwen2.5 32B Instruct: —

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Non-English | 1236 | — |
| LMArena Chinese | 1217 | — |
| LMArena French | 1281 | — |
| LMArena German | 1251 | — |
| LMArena Japanese | 1150 | — |
| LMArena Korean | 1143 | — |
| LMArena Russian | 1252 | — |
| LMArena Spanish | 1270 | — |

## Instruction Following

- Llama-3.3-70B-Instruct: 71.1 (#157)
- Qwen2.5 32B Instruct: —

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| LiveBench Instruction Following | 82.7% | — |
| LMArena Instruction Following | 1242 | — |

## Long Context

- Llama-3.3-70B-Instruct: 26.4 (#295)
- Qwen2.5 32B Instruct: —

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| Fiction.LiveBench | 33.3% | — |
| LMArena Longer Query | 1256 | — |

## Writing & Preference

- Llama-3.3-70B-Instruct: 47.6 (#207)
- Qwen2.5 32B Instruct: —

| Benchmark | Llama-3.3-70B-Instruct | Qwen2.5 32B Instruct |
|---|---|---|
| LMArena Text | 1274 | — |
| LMArena Creative Writing | 1250 | — |
| LMArena Multi-Turn | 1280 | — |
| LiveBench Language | 39.2% | — |

## FAQ

### Is Llama-3.3-70B-Instruct better than Qwen2.5 32B Instruct?

Llama-3.3-70B-Instruct and Qwen2.5 32B Instruct score almost the same on the Noometry Index (30.6 vs 30.1), so choose on price, context window or the category you care about most.

### Which is cheaper, Llama-3.3-70B-Instruct or Qwen2.5 32B Instruct?

Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Qwen2.5 32B Instruct lists at $0.70 and $2.80.

### Is Llama-3.3-70B-Instruct or Qwen2.5 32B Instruct better for coding?

Qwen2.5 32B Instruct scores higher on coding benchmarks: 38.7 versus 31.0 in the Noometry coding category.

### Which has the bigger context window?

Qwen2.5 32B Instruct does, with 131K tokens against 128K.

### How many benchmarks do Llama-3.3-70B-Instruct and Qwen2.5 32B Instruct share?

6 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Qwen2.5 32B Instruct has 7.