Model comparison
GPT-5-Codex vs Llama 2-70B
GPT-5-Codex is the stronger model overall, scoring 37.9 to 24.4 on the Noometry Index.
Last verified . 0 shared benchmarks.
MetaSummary
- The widest gap is in reasoning, where GPT-5-Codex leads 30.9 to 14.4.
- Llama 2-70B has downloadable open weights; the other is API-only.
Side by side
| GPT-5-Codex | Llama 2-70B | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 37.9 | 24.4 |
| Released | 2025-09-15 | 2023-07-18 |
| Weights | Proprietary | Open |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 3 | 35 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5-Codex leads
GPT-5-Codex: 42.4 (#103), Llama 2-70B: 31.4 (#286)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| WeirdML | 54.5% | — |
| LMArena Coding | — | 1079 |
Agentic & Tool Use Not comparable
GPT-5-Codex: 31.0 (#72), Llama 2-70B: —
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| Terminal-Bench | 44.3% | — |
Reasoning GPT-5-Codex leads
GPT-5-Codex: 30.9 (#83), Llama 2-70B: 14.4 (#325)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | — |
| LMArena Hard Prompts | — | 1073 |
| DTBench | — | 41.6% |
| BIG-Bench Hard | — | 64.9% |
| CommonsenseQA 2.0 | — | 50% |
| Epoch Capabilities Index | — | 113.79 |
| ForecastBench | — | 51.4 |
| HellaSwag | — | 85.3% |
| LAMBADA | — | 78.9% |
| PIQA | — | 82.8% |
| WinoGrande | — | 80.2% |
Math Not comparable
GPT-5-Codex: —, Llama 2-70B: 8.1 (#326)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 0% |
| LMArena Math | — | 1091 |
| MATH Level 5 | — | 3.3% |
| GSM8K | — | 69.6% |
Knowledge Not comparable
GPT-5-Codex: —, Llama 2-70B: 7.4 (#310)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| GPQA Diamond | — | 26.3% |
| LMArena Expert | — | 1039 |
| ARC (AI2) Challenge | — | 78.3% |
| BoolQ | — | 88.6% |
| MMLU | — | 69.9% |
| OpenBookQA | — | 60.2% |
| TriviaQA | — | 87.6% |
Multilingual Not comparable
GPT-5-Codex: —, Llama 2-70B: 27.7 (#274)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| LMArena Non-English | — | 1045 |
| LMArena Chinese | — | 995 |
| LMArena French | — | 1090 |
| LMArena German | — | 1041 |
| LMArena Japanese | — | 927 |
| LMArena Korean | — | 964 |
| LMArena Russian | — | 1083 |
| LMArena Spanish | — | 1143 |
Instruction Following Not comparable
GPT-5-Codex: —, Llama 2-70B: 54.9 (#278)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| LMArena Instruction Following | — | 1071 |
Long Context Not comparable
GPT-5-Codex: —, Llama 2-70B: 32.3 (#270)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| LMArena Longer Query | — | 1062 |
Writing & Preference Not comparable
GPT-5-Codex: —, Llama 2-70B: 32.3 (#279)
| Benchmark | GPT-5-Codex | Llama 2-70B |
|---|---|---|
| LMArena Text | — | 1115 |
| LMArena Creative Writing | — | 1075 |
| LMArena Multi-Turn | — | 1088 |
Frequently asked questions
Is GPT-5-Codex better than Llama 2-70B?
GPT-5-Codex is the stronger model overall, scoring 37.9 to 24.4 on the Noometry Index.
Is GPT-5-Codex or Llama 2-70B better for coding?
GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 31.4 in the Noometry coding category.
How many benchmarks do GPT-5-Codex and Llama 2-70B share?
0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Llama 2-70B has 35.