# GPT-4 vs Llama 3.2 1B

> GPT-4 is the stronger model overall, scoring 28.9 to 19.9 on the Noometry Index. Llama 3.2 1B costs 532× less per token, which makes it the better buy when GPT-4's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-4-vs-llama-3-2-1b
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. GPT-4 scores higher in 8 categories and Llama 3.2 1B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GPT-4 leads 40.8 to 23.9.
- The biggest single-benchmark swing is BigCodeBench Complete: 57.2% for GPT-4 and 11.3% for Llama 3.2 1B.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $30 / $60 for GPT-4.
- Llama 3.2 1B accepts more context: 60K tokens versus 8K.
- Llama 3.2 1B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-4 | Llama 3.2 1B |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 28.9 | 19.9 |
| Rank | 308 | 349 |
| Context | 8K | 60K |
| Input $/M | $30 | $0.027 |
| Output $/M | $60 | $0.20 |
| Weights | Proprietary | Open |

## Coding

- GPT-4: 31.2 (#277)
- Llama 3.2 1B: 20.6 (#333)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| BigCodeBench Instruct | 46% | 8.2% |
| LMArena Coding | 1254 | 1071 |
| BigCodeBench Complete | 57.2% | 11.3% |
| WeirdML | 12.4% | — |
| HumanEval+ | 79.3% | — |

## Agentic & Tool Use

- GPT-4: —
- Llama 3.2 1B: 14.5 (#142)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 10.8% |
| BALROG | — | 6.6% |
| METR Time Horizons | 36.1% | — |

## Reasoning

- GPT-4: 17.3 (#285)
- Llama 3.2 1B: 15.6 (#304)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| Chess Puzzles | 4% | 0% |
| LMArena Hard Prompts | 1241 | 1044 |
| Epoch Capabilities Index | 125.88 | 101.95 |
| Mystery Game Puzzles | 12% | — |
| DTBench | 62.7% | — |
| LMCA | 17.1% | — |
| BIG-Bench Hard | 75.1% | — |
| ForecastBench | 57.8 | — |
| HellaSwag | 95.3% | — |
| WinoGrande | 87.5% | — |

## Math

- GPT-4: 10.1 (#304)
- Llama 3.2 1B: 9.7 (#308)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.1% | 0.6% |
| LMArena Math | 1269 | 1086 |
| MATH Level 5 | 23% | — |
| GSM8K | 92% | — |

## Knowledge

- GPT-4: 18.4 (#277)
- Llama 3.2 1B: 7.2 (#307)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| GPQA Diamond | 35.7% | 23.9% |
| LMArena Expert | 1211 | 1007 |
| MMLU | 86.4% | — |
| TriviaQA | 84.8% | — |

## Multilingual

- GPT-4: 40.8 (#210)
- Llama 3.2 1B: 23.9 (#287)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1246 | 973 |
| LMArena Chinese | 1242 | 958 |
| LMArena German | 1251 | 1014 |
| LMArena Russian | 1251 | 941 |
| LMArena French | 1282 | — |
| LMArena Japanese | 1209 | — |
| LMArena Korean | 1184 | — |
| LMArena Spanish | 1261 | — |

## Instruction Following

- GPT-4: 65.5 (#217)
- Llama 3.2 1B: 52.6 (#285)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1241 | 1031 |

## Long Context

- GPT-4: 37.7 (#207)
- Llama 3.2 1B: 31.9 (#269)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1244 | 1050 |

## Writing & Preference

- GPT-4: 35.0 (#263)
- Llama 3.2 1B: 21.4 (#305)

| Benchmark | GPT-4 | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1263 | 1055 |
| LMArena Creative Writing | 1244 | 1033 |
| EQ-Bench Creative Writing | 752 | 200 |
| LMArena Multi-Turn | 1257 | 1030 |

## FAQ

### Is GPT-4 better than Llama 3.2 1B?

GPT-4 is the stronger model overall, scoring 28.9 to 19.9 on the Noometry Index. Llama 3.2 1B costs 532× less per token, which makes it the better buy when GPT-4's lead doesn't matter for your workload.

### Which is cheaper, GPT-4 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; GPT-4 lists at $30 and $60.

### Is GPT-4 or Llama 3.2 1B better for coding?

GPT-4 scores higher on coding benchmarks: 31.2 versus 20.6 in the Noometry coding category.

### Which has the bigger context window?

Llama 3.2 1B does, with 60K tokens against 8K.

### How many benchmarks do GPT-4 and Llama 3.2 1B share?

20 benchmarks have published results for both models. GPT-4 has 38 scored results on Noometry and Llama 3.2 1B has 22.