# Llama-3.3-70B-Instruct vs Pixtral Large

> Pixtral Large is the stronger model overall, scoring 32.2 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 19× less per token, which makes it the better buy when Pixtral Large's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-3-3-70b-instruct-vs-pixtral-large
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- The widest gap is in writing & preference, where Llama-3.3-70B-Instruct leads 47.6 to 32.9.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $2 / $6 for Pixtral Large.

## Snapshot

| | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 30.6 | 32.2 |
| Rank | 291 | 259 |
| Context | 128K | 128K |
| Input $/M | $0.10 | $2 |
| Output $/M | $0.32 | $6 |
| Weights | Open | Open |

## Coding

- Llama-3.3-70B-Instruct: 31.0 (#290)
- Pixtral Large: —

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| SciCode | 26% | — |
| WeirdML | 14.4% | — |
| BigCodeBench Instruct | 46.9% | — |
| LiveBench Coding | 36.6% | — |
| LMArena Coding | 1268 | — |
| BigCodeBench Complete | 57.5% | — |

## Agentic & Tool Use

- Llama-3.3-70B-Instruct: 25.8 (#105)
- Pixtral Large: —

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| BALROG | 23% | — |

## Reasoning

- Llama-3.3-70B-Instruct: 14.1 (#327)
- Pixtral Large: 21.7 (#218)

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| SimpleBench | 19.9% | — |
| CritPt | 0% | — |
| EnigmaEval | — | 0.8% |
| LiveBench Reasoning | 50.8% | — |
| LMArena Hard Prompts | 1257 | — |
| DTBench | 59.5% | — |
| LiveBench Data Analysis | 49.5% | — |
| LMCA | 17.5% | — |
| Epoch Capabilities Index | 127.33 | — |
| ForecastBench | 58.6 | — |
| LiveBench | 50.2% | — |

## Math

- Llama-3.3-70B-Instruct: 15.3 (#298)
- Pixtral Large: —

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | — |
| LiveBench Math | 42.2% | — |
| LMArena Math | 1267 | — |
| MATH Level 5 | 41.6% | — |

## Knowledge

- Llama-3.3-70B-Instruct: 30.6 (#226)
- Pixtral Large: —

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| GPQA Diamond | 47.4% | — |
| Confabulations | 22.8% | — |
| Vectara Hallucination Rate | 4.1% | — |
| LMArena Expert | 1225 | — |
| MMLU | 86.3% | — |

## Multimodal

- Llama-3.3-70B-Instruct: —
- Pixtral Large: 30.6 (#111)

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| LMArena Vision | — | 1089 |

## Multilingual

- Llama-3.3-70B-Instruct: 39.9 (#220)
- Pixtral Large: —

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| 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)
- Pixtral Large: —

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| LiveBench Instruction Following | 82.7% | — |
| LMArena Instruction Following | 1242 | — |

## Long Context

- Llama-3.3-70B-Instruct: 26.4 (#295)
- Pixtral Large: —

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| Fiction.LiveBench | 33.3% | — |
| LMArena Longer Query | 1256 | — |

## Writing & Preference

- Llama-3.3-70B-Instruct: 47.6 (#207)
- Pixtral Large: 32.9 (#278)

| Benchmark | Llama-3.3-70B-Instruct | Pixtral Large |
|---|---|---|
| LMArena Text | 1274 | — |
| LMArena Creative Writing | 1250 | — |
| EQ-Bench Creative Writing | — | 988 |
| LMArena Multi-Turn | 1280 | — |
| LiveBench Language | 39.2% | — |

## FAQ

### Is Llama-3.3-70B-Instruct better than Pixtral Large?

Pixtral Large is the stronger model overall, scoring 32.2 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 19× less per token, which makes it the better buy when Pixtral Large's lead doesn't matter for your workload.

### Which is cheaper, Llama-3.3-70B-Instruct or Pixtral Large?

Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Pixtral Large lists at $2 and $6.

### Which has the bigger context window?

Both accept 128K tokens.

### How many benchmarks do Llama-3.3-70B-Instruct and Pixtral Large share?

0 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Pixtral Large has 3.