# GPT-5.2 Codex vs Llama 3.1-70B

> GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 29.4 on the Noometry Index. Llama 3.1-70B costs 12× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-2-codex-vs-llama-3-1-70b
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in agentic & tool use, where GPT-5.2 Codex leads 40.7 to 24.9.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- GPT-5.2 Codex accepts more context: 400K tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 42.2 | 29.4 |
| Rank | 107 | 299 |
| Context | 400K | 128K |
| Input $/M | $1.75 | $0.40 |
| Output $/M | $14 | $0.40 |
| Weights | Proprietary | Open |

## Coding

- GPT-5.2 Codex: 45.4 (#66)
- Llama 3.1-70B: 29.8 (#292)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| WeirdML | — | 9% |
| BigCodeBench Instruct | — | 46.1% |
| LMArena Coding | — | 1260 |
| BigCodeBench Complete | — | 54.8% |
| ALE-Bench | 1,300 | — |

## Agentic & Tool Use

- GPT-5.2 Codex: 40.7 (#20)
- Llama 3.1-70B: 24.9 (#104)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| Terminal-Bench | 66.5% | — |
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |

## Reasoning

- GPT-5.2 Codex: —
- Llama 3.1-70B: 20.8 (#215)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| LMArena Hard Prompts | — | 1241 |
| DTBench | — | 60% |
| LMCA | — | 14.8% |
| Epoch Capabilities Index | — | 125.91 |

## Math

- GPT-5.2 Codex: —
- Llama 3.1-70B: 12.7 (#298)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 3.6% |
| Omni-MATH | — | 21% |
| LMArena Math | — | 1252 |
| MATH Level 5 | — | 36.7% |

## Knowledge

- GPT-5.2 Codex: —
- Llama 3.1-70B: 24.1 (#264)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| GPQA Diamond | — | 44.2% |
| MMLU-Pro | — | 65.3% |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1209 |
| MMLU | — | 80.1% |

## Multilingual

- GPT-5.2 Codex: —
- Llama 3.1-70B: 38.9 (#220)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | — | 1219 |
| LMArena Chinese | — | 1215 |
| LMArena French | — | 1260 |
| LMArena German | — | 1222 |
| LMArena Japanese | — | 1132 |
| LMArena Korean | — | 1140 |
| LMArena Russian | — | 1234 |
| LMArena Spanish | — | 1253 |

## Instruction Following

- GPT-5.2 Codex: —
- Llama 3.1-70B: 65.5 (#218)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| IFEval | — | 82.1% |
| LMArena Instruction Following | — | 1231 |

## Long Context

- GPT-5.2 Codex: —
- Llama 3.1-70B: 37.6 (#208)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | — | 1241 |

## Writing & Preference

- GPT-5.2 Codex: —
- Llama 3.1-70B: 35.6 (#262)

| Benchmark | GPT-5.2 Codex | Llama 3.1-70B |
|---|---|---|
| LMArena Text | — | 1261 |
| LMArena Creative Writing | — | 1232 |
| EQ-Bench Creative Writing | — | 784 |
| WildBench | — | 75.8% |
| LMArena Multi-Turn | — | 1256 |

## FAQ

### Is GPT-5.2 Codex better than Llama 3.1-70B?

GPT-5.2 Codex is the stronger model overall, scoring 42.2 to 29.4 on the Noometry Index. Llama 3.1-70B costs 12× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.

### Which is cheaper, GPT-5.2 Codex or Llama 3.1-70B?

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.

### Is GPT-5.2 Codex or Llama 3.1-70B better for coding?

GPT-5.2 Codex scores higher on coding benchmarks: 45.4 versus 29.8 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.2 Codex does, with 400K tokens against 128K.

### How many benchmarks do GPT-5.2 Codex and Llama 3.1-70B share?

0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Llama 3.1-70B has 35.