# GPT-5 Nano vs Llama 3-70B

> GPT-5 Nano is the stronger model overall, scoring 33.5 to 28.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-nano-vs-llama-3-70b
- Last updated: 2026-10-12
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. GPT-5 Nano scores higher in 5 categories and Llama 3-70B in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5 Nano leads 29.4 to 12.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 81.1% for GPT-5 Nano and 4.3% for Llama 3-70B.
- Llama 3-70B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 33.5 | 28.8 |
| Rank | 241 | 323 |
| Context | 400K | — |
| Input $/M | $0.05 | — |
| Output $/M | $0.40 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-5 Nano: 33.6 (#254)
- Llama 3-70B: 35.8 (#218)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| LMArena Coding | 1351 | 1206 |
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| BigCodeBench Instruct | — | 43.6% |
| BigCodeBench Complete | — | 54.5% |
| ALE-Bench | 718.67 | — |
| HumanEval+ | — | 72% |
| MBPP+ | — | 69% |

## Agentic & Tool Use

- GPT-5 Nano: 25.8 (#106)
- Llama 3-70B: 21.1 (#139)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
| Cybench | — | 5% |

## Reasoning

- GPT-5 Nano: 16.3 (#306)
- Llama 3-70B: 18.0 (#288)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| Kagi LLM Benchmark | 62.2% | 35.1% |
| LMArena Hard Prompts | 1328 | 1195 |
| DTBench | 62.7% | 54.2% |
| Epoch Capabilities Index | 139.38 | 122.93 |
| ForecastBench | 59.1 | 57.1 |
| ARC-AGI-2 | 2.6% | — |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| Mystery Game Puzzles | 9% | — |
| LMCA | 7.9% | — |
| WinoGrande | — | 83.5% |

## Math

- GPT-5 Nano: 29.4 (#241)
- Llama 3-70B: 12.8 (#305)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 81.1% | 4.3% |
| LMArena Math | 1317 | 1218 |
| MATH Level 5 | 95.2% | 22.6% |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GPT-5 Nano: 35.9 (#178)
- Llama 3-70B: 20.8 (#277)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| GPQA Diamond | 69.4% | 40.6% |
| LMArena Expert | 1321 | 1149 |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
| MMLU | — | 79.3% |

## Multimodal

- GPT-5 Nano: 31.3 (#108)
- Llama 3-70B: —

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |

## Multilingual

- GPT-5 Nano: 45.3 (#172)
- Llama 3-70B: 33.6 (#251)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| LMArena Non-English | 1313 | 1142 |
| LMArena Chinese | 1356 | 1114 |
| LMArena German | 1327 | 1169 |
| LMArena Japanese | 1226 | 1017 |
| LMArena Korean | 1269 | 1017 |
| LMArena Russian | 1296 | 1159 |
| LMArena Spanish | 1360 | 1241 |
| LMArena French | — | 1232 |

## Instruction Following

- GPT-5 Nano: 75.0 (#79)
- Llama 3-70B: 62.5 (#238)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| LMArena Instruction Following | 1306 | 1194 |
| IFEval | 93.2% | — |

## Long Context

- GPT-5 Nano: 31.3 (#281)
- Llama 3-70B: 35.6 (#240)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| LMArena Longer Query | 1312 | 1174 |
| Fiction.LiveBench | 44.4% | — |

## Writing & Preference

- GPT-5 Nano: 39.1 (#249)
- Llama 3-70B: 42.8 (#231)

| Benchmark | GPT-5 Nano | Llama 3-70B |
|---|---|---|
| LMArena Text | 1320 | 1221 |
| LMArena Creative Writing | 1249 | 1210 |
| LMArena Multi-Turn | 1311 | 1223 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |

## FAQ

### Is GPT-5 Nano better than Llama 3-70B?

GPT-5 Nano is the stronger model overall, scoring 33.5 to 28.8 on the Noometry Index.

### Is GPT-5 Nano or Llama 3-70B better for coding?

Llama 3-70B scores higher on coding benchmarks: 35.8 versus 33.6 in the Noometry coding category.

### How many benchmarks do GPT-5 Nano and Llama 3-70B share?

23 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Llama 3-70B has 31.