# GPT-5.3 Codex vs Llama 3.1-8B

> GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 22.8 on the Noometry Index. Llama 3.1-8B costs 84× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-3-codex-vs-llama-3-1-8b
- Last updated: 2026-10-10
- Shared benchmarks: 2

## Summary

- They share 2 benchmarks with published results for both. GPT-5.3 Codex scores higher in 2 categories and Llama 3.1-8B in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.3 Codex leads 48.5 to 19.9.
- The biggest single-benchmark swing is WeirdML: 79.3% for GPT-5.3 Codex and 1.7% for Llama 3.1-8B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.3 Codex accepts more context: 400K tokens versus 128K.
- Llama 3.1-8B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 45.5 | 22.8 |
| Rank | 61 | 347 |
| Context | 400K | 128K |
| Input $/M | $1.75 | $0.05 |
| Output $/M | $14 | $0.08 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.3 Codex: 48.5 (#51)
- Llama 3.1-8B: 19.9 (#335)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| WeirdML | 79.3% | 1.7% |
| SWE-bench Verified | 74.8% | — |
| LMArena WebDev | 1408 | — |
| SciCode | — | 13.2% |
| BigCodeBench Instruct | — | 32.8% |
| LMArena Coding | — | 1195 |
| BigCodeBench Complete | — | 40.5% |
| ALE-Bench | 1,655 | — |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |

## Agentic & Tool Use

- GPT-5.3 Codex: 47.8 (#9)
- Llama 3.1-8B: 22.3 (#123)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| Terminal-Bench | 78.4% | — |
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |
| METR Time Horizons | 74.5% | — |
| Vending-Bench 2 | 5,940 | — |

## Reasoning

- GPT-5.3 Codex: —
- Llama 3.1-8B: 14.5 (#316)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| Epoch Capabilities Index | 156.84 | 116.48 |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1175 |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| PIQA | — | 81.2% |

## Math

- GPT-5.3 Codex: —
- Llama 3.1-8B: 9.5 (#311)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| Omni-MATH | — | 13.7% |
| LMArena Math | — | 1179 |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |

## Knowledge

- GPT-5.3 Codex: —
- Llama 3.1-8B: 8.0 (#302)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| LMArena Expert | — | 1144 |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |

## Multilingual

- GPT-5.3 Codex: —
- Llama 3.1-8B: 34.2 (#244)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | — | 1148 |
| LMArena Chinese | — | 1151 |
| LMArena French | — | 1176 |
| LMArena German | — | 1144 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1053 |
| LMArena Russian | — | 1158 |
| LMArena Spanish | — | 1169 |

## Instruction Following

- GPT-5.3 Codex: —
- Llama 3.1-8B: 59.1 (#253)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| IFEval | — | 74.3% |
| LMArena Instruction Following | — | 1159 |

## Long Context

- GPT-5.3 Codex: —
- Llama 3.1-8B: 35.8 (#233)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | — | 1182 |

## Writing & Preference

- GPT-5.3 Codex: —
- Llama 3.1-8B: 29.9 (#285)

| Benchmark | GPT-5.3 Codex | Llama 3.1-8B |
|---|---|---|
| LMArena Text | — | 1187 |
| LMArena Creative Writing | — | 1154 |
| EQ-Bench Creative Writing | — | 713 |
| WildBench | — | 68.7% |
| LMArena Multi-Turn | — | 1172 |

## FAQ

### Is GPT-5.3 Codex better than Llama 3.1-8B?

GPT-5.3 Codex is the stronger model overall, scoring 45.5 to 22.8 on the Noometry Index. Llama 3.1-8B costs 84× less per token, which makes it the better buy when GPT-5.3 Codex's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.3 Codex or Llama 3.1-8B?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; GPT-5.3 Codex lists at $1.75 and $14.

### Is GPT-5.3 Codex or Llama 3.1-8B better for coding?

GPT-5.3 Codex scores higher on coding benchmarks: 48.5 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.3 Codex does, with 400K tokens against 128K.

### How many benchmarks do GPT-5.3 Codex and Llama 3.1-8B share?

2 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and Llama 3.1-8B has 43.