# Grok 4.3 vs Llama 3.2 1B

> Grok 4.3 is the stronger model overall, scoring 43.6 to 19.9 on the Noometry Index. Llama 3.2 1B costs 22× less per token, which makes it the better buy when Grok 4.3's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/grok-4-3-vs-llama-3-2-1b
- Last updated: 2026-10-10
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. Grok 4.3 scores higher in 9 categories and Llama 3.2 1B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Grok 4.3 leads 52.5 to 7.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.3% for Grok 4.3 and 0.6% for Llama 3.2 1B.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $1.25 / $2.50 for Grok 4.3.
- Grok 4.3 accepts more context: 1M tokens versus 60K.
- Llama 3.2 1B has downloadable open weights; the other is API-only.

## Snapshot

| | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 43.6 | 19.9 |
| Rank | 80 | 349 |
| Context | 1M | 60K |
| Input $/M | $1.25 | $0.027 |
| Output $/M | $2.50 | $0.20 |
| Weights | Proprietary | Open |

## Coding

- Grok 4.3: 41.3 (#117)
- Llama 3.2 1B: 20.6 (#333)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| LMArena Coding | 1415 | 1071 |
| LMArena WebDev | 1357 | — |
| SciCode | 47.3% | — |
| WeirdML | 49.9% | — |
| BigCodeBench Instruct | — | 8.2% |
| BigCodeBench Complete | — | 11.3% |
| ALE-Bench | 944.17 | — |

## Agentic & Tool Use

- Grok 4.3: 27.6 (#93)
- Llama 3.2 1B: 14.5 (#142)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 10.8% |
| BALROG | — | 6.6% |
| GDP.pdf | 8% | — |
| LMArena Search | 1165 | — |
| Vending-Bench 2 | 35.26 | — |

## Reasoning

- Grok 4.3: 34.9 (#60)
- Llama 3.2 1B: 15.6 (#304)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| Chess Puzzles | 25% | 0% |
| LMArena Hard Prompts | 1397 | 1044 |
| Epoch Capabilities Index | 149.13 | 101.95 |
| NYT Connections (extended) | 55.2% | — |
| CritPt | 8% | — |
| DTBench | 90.7% | — |
| LMCA | 38.3% | — |
| ForecastBench | 60.3 | — |

## Math

- Grok 4.3: 45.8 (#60)
- Llama 3.2 1B: 9.7 (#308)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.3% | 0.6% |
| LMArena Math | 1388 | 1086 |
| FrontierMath (Tiers 1-3) | 42.8% | — |
| FrontierMath Tier 4 | 14.6% | — |
| ProofBench | 11% | — |

## Knowledge

- Grok 4.3: 52.5 (#57)
- Llama 3.2 1B: 7.2 (#307)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| GPQA Diamond | 88.8% | 23.9% |
| LMArena Expert | 1385 | 1007 |
| SimpleQA Verified | 33.2% | — |

## Multimodal

- Grok 4.3: 31.6 (#96)
- Llama 3.2 1B: —

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| LMArena Vision | 1231 | — |
| Blueprint-Bench 2 | 0% | — |

## Multilingual

- Grok 4.3: 50.7 (#114)
- Llama 3.2 1B: 23.9 (#287)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1385 | 973 |
| LMArena Chinese | 1423 | 958 |
| LMArena German | 1395 | 1014 |
| LMArena Russian | 1399 | 941 |
| LMArena French | 1412 | — |
| LMArena Japanese | 1379 | — |
| LMArena Korean | 1357 | — |
| LMArena Spanish | 1402 | — |

## Instruction Following

- Grok 4.3: 72.3 (#135)
- Llama 3.2 1B: 52.6 (#285)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1366 | 1031 |

## Long Context

- Grok 4.3: 42.5 (#118)
- Llama 3.2 1B: 31.9 (#269)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1393 | 1050 |

## Writing & Preference

- Grok 4.3: 58.6 (#112)
- Llama 3.2 1B: 21.4 (#305)

| Benchmark | Grok 4.3 | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1397 | 1055 |
| LMArena Creative Writing | 1380 | 1033 |
| LMArena Multi-Turn | 1406 | 1030 |
| EQ-Bench Creative Writing | — | 200 |
| EQ-Bench 4 | 1075 | — |

## FAQ

### Is Grok 4.3 better than Llama 3.2 1B?

Grok 4.3 is the stronger model overall, scoring 43.6 to 19.9 on the Noometry Index. Llama 3.2 1B costs 22× less per token, which makes it the better buy when Grok 4.3's lead doesn't matter for your workload.

### Which is cheaper, Grok 4.3 or Llama 3.2 1B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Grok 4.3 lists at $1.25 and $2.50.

### Is Grok 4.3 or Llama 3.2 1B better for coding?

Grok 4.3 scores higher on coding benchmarks: 41.3 versus 20.6 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.3 does, with 1M tokens against 60K.

### How many benchmarks do Grok 4.3 and Llama 3.2 1B share?

17 benchmarks have published results for both models. Grok 4.3 has 40 scored results on Noometry and Llama 3.2 1B has 22.