Model comparison
GPT-5-Codex vs Llama 3.1 Nemotron 70b Instruct
GPT-5-Codex and Llama 3.1 Nemotron 70b Instruct score almost the same on the Noometry Index (37.9 vs 37.6), so choose on price, context window or the category you care about most.
Last verified . 0 shared benchmarks.
NVIDIASummary
- The widest gap is in coding, where GPT-5-Codex leads 42.4 to 35.9.
- Llama 3.1 Nemotron 70b Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct | |
|---|---|---|
| Provider | OpenAI | NVIDIA |
| Noometry Index | 37.9 | 37.6 |
| Released | 2025-09-15 | 2024-12-18 |
| Weights | Proprietary | Open |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 3 | 14 |
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Category by category
Coding GPT-5-Codex leads
GPT-5-Codex: 42.4 (#103), Llama 3.1 Nemotron 70b Instruct: 35.9 (#216)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| WeirdML | 54.5% | — |
| BigCodeBench Instruct | — | 38.7% |
| LMArena Coding | — | 1272 |
| BigCodeBench Complete | — | 48.2% |
Agentic & Tool Use Not comparable
GPT-5-Codex: 31.0 (#72), Llama 3.1 Nemotron 70b Instruct: —
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| Terminal-Bench | 44.3% | — |
Reasoning GPT-5-Codex leads
GPT-5-Codex: 30.9 (#83), Llama 3.1 Nemotron 70b Instruct: 25.0 (#152)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| Kagi LLM Benchmark | 70.3% | — |
| LMArena Hard Prompts | — | 1266 |
Math Not comparable
GPT-5-Codex: —, Llama 3.1 Nemotron 70b Instruct: 35.5 (#182)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Math | — | 1271 |
Knowledge Not comparable
GPT-5-Codex: —, Llama 3.1 Nemotron 70b Instruct: 34.1 (#199)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Expert | — | 1242 |
Multilingual Not comparable
GPT-5-Codex: —, Llama 3.1 Nemotron 70b Instruct: 40.5 (#217)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Non-English | — | 1245 |
| LMArena Chinese | — | 1263 |
| LMArena Russian | — | 1227 |
Instruction Following Not comparable
GPT-5-Codex: —, Llama 3.1 Nemotron 70b Instruct: 65.9 (#213)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Instruction Following | — | 1252 |
Long Context Not comparable
GPT-5-Codex: —, Llama 3.1 Nemotron 70b Instruct: 37.6 (#215)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Longer Query | — | 1238 |
Writing & Preference Not comparable
GPT-5-Codex: —, Llama 3.1 Nemotron 70b Instruct: 48.4 (#203)
| Benchmark | GPT-5-Codex | Llama 3.1 Nemotron 70b Instruct |
|---|---|---|
| LMArena Text | — | 1283 |
| LMArena Creative Writing | — | 1269 |
| LMArena Multi-Turn | — | 1275 |
Frequently asked questions
Is GPT-5-Codex better than Llama 3.1 Nemotron 70b Instruct?
GPT-5-Codex and Llama 3.1 Nemotron 70b Instruct score almost the same on the Noometry Index (37.9 vs 37.6), so choose on price, context window or the category you care about most.
Is GPT-5-Codex or Llama 3.1 Nemotron 70b Instruct better for coding?
GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 35.9 in the Noometry coding category.
How many benchmarks do GPT-5-Codex and Llama 3.1 Nemotron 70b Instruct share?
0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Llama 3.1 Nemotron 70b Instruct has 14.