# Grok 4.6 vs Llama 3.2 3B

> Grok 4.6 is the stronger model overall, scoring 56.9 to 28.9 on the Noometry Index. Llama 3.2 3B costs 25× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/grok-4-6-vs-llama-3-2-3b
- Last updated: 2026-10-12
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Grok 4.6 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 reasoning, where Grok 4.6 leads 61.4 to 21.0.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $2 / $6 for Grok 4.6.
- Grok 4.6 accepts more context: 500K tokens versus 131K.
- Llama 3.2 3B has downloadable open weights; the other is API-only.

## Snapshot

| | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 56.9 | 28.9 |
| Rank | 21 | 321 |
| Context | 500K | 131K |
| Input $/M | $2 | $0.05 |
| Output $/M | $6 | $0.33 |
| Weights | Proprietary | Open |

## Coding

- Grok 4.6: 58.5 (#16)
- Llama 3.2 3B: 27.6 (#319)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1465 | 1098 |
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| CursorBench | 41.4% | — |
| LMArena WebDev | 1617 | — |
| FrontierSWE | 25.3% | — |
| SciCode | 56.5% | — |
| WeirdML | 67.3% | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |
| ALE-Bench | 1,508 | — |

## Agentic & Tool Use

- Grok 4.6: 39.4 (#27)
- Llama 3.2 3B: 20.1 (#143)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| APEX-Agents | 65.3% | — |
| Berkeley Function Calling Leaderboard | — | 21.9% |
| BALROG | — | 10.1% |
| GDP.pdf | 17.2% | — |
| Vending-Bench 2 | 9,047 | — |

## Reasoning

- Grok 4.6: 61.4 (#20)
- Llama 3.2 3B: 21.0 (#228)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1447 | 1095 |
| ARC-AGI-2 | 67.1% | — |
| SimpleBench | 75.9% | — |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| CritPt | 19.7% | — |
| Chess Puzzles | 40% | — |
| EBR-Bench | 30.5% | — |
| Mystery Game Puzzles | 34% | — |
| DTBench | 97.3% | — |
| LMCA | 48.5% | — |
| Epoch Capabilities Index | 156.44 | — |

## Math

- Grok 4.6: 67.0 (#24)
- Llama 3.2 3B: 32.4 (#214)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1423 | 1126 |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 31.7% | — |
| OTIS Mock AIME 2024-2025 | 99.2% | — |
| ProofBench | 51% | — |

## Knowledge

- Grok 4.6: 63.3 (#20)
- Llama 3.2 3B: 29.7 (#235)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1467 | 1090 |
| GPQA Diamond | 94% | — |
| SimpleQA Verified | 49.3% | — |

## Multimodal

- Grok 4.6: 43.6 (#23)
- Llama 3.2 3B: —

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |

## Multilingual

- Grok 4.6: 53.0 (#74)
- Llama 3.2 3B: 26.2 (#281)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1420 | 1019 |
| LMArena Chinese | 1480 | 1017 |
| LMArena German | 1431 | 1056 |
| LMArena Russian | 1422 | 949 |
| LMArena French | 1461 | — |
| LMArena Japanese | 1376 | — |
| LMArena Korean | 1397 | — |
| LMArena Spanish | 1404 | — |

## Instruction Following

- Grok 4.6: 75.4 (#63)
- Llama 3.2 3B: 56.0 (#275)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1431 | 1089 |

## Long Context

- Grok 4.6: 44.5 (#66)
- Llama 3.2 3B: 33.4 (#261)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1454 | 1100 |

## Writing & Preference

- Grok 4.6: 62.3 (#80)
- Llama 3.2 3B: 24.7 (#307)

| Benchmark | Grok 4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1428 | 1110 |
| LMArena Creative Writing | 1428 | 1094 |
| LMArena Multi-Turn | 1425 | 1105 |
| EQ-Bench Creative Writing | — | 595 |

## FAQ

### Is Grok 4.6 better than Llama 3.2 3B?

Grok 4.6 is the stronger model overall, scoring 56.9 to 28.9 on the Noometry Index. Llama 3.2 3B costs 25× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.

### Which is cheaper, Grok 4.6 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; Grok 4.6 lists at $2 and $6.

### Is Grok 4.6 or Llama 3.2 3B better for coding?

Grok 4.6 scores higher on coding benchmarks: 58.5 versus 27.6 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.6 does, with 500K tokens against 131K.

### How many benchmarks do Grok 4.6 and Llama 3.2 3B share?

13 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Llama 3.2 3B has 18.