# GPT-5 Nano vs Llama 2-7B

> GPT-5 Nano is the stronger model overall, scoring 33.4 to 28.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-nano-vs-llama-2-7b
- Last updated: 2026-10-10
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. GPT-5 Nano scores higher in 8 categories and Llama 2-7B in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where GPT-5 Nano leads 75.2 to 51.0.
- The biggest single-benchmark swing is Chess Puzzles: 27% for GPT-5 Nano and 0% for Llama 2-7B.
- Llama 2-7B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 33.4 | 28.6 |
| Rank | 234 | 315 |
| Context | 400K | — |
| Input $/M | $0.05 | — |
| Output $/M | $0.40 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-5 Nano: 33.3 (#248)
- Llama 2-7B: 28.7 (#302)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Coding | 1351 | 1002 |
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| ALE-Bench | 718.67 | — |

## Agentic & Tool Use

- GPT-5 Nano: 25.6 (#99)
- Llama 2-7B: —

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |

## Reasoning

- GPT-5 Nano: 16.4 (#291)
- Llama 2-7B: 15.1 (#309)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| Chess Puzzles | 27% | 0% |
| LMArena Hard Prompts | 1329 | 1009 |
| Epoch Capabilities Index | 139.39 | 98.54 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| ARC-AGI-1 | 20.7% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| BIG-Bench Hard | — | 39.2% |
| ForecastBench | 59.1 | — |
| HellaSwag | — | 77.2% |
| LAMBADA | — | 73.3% |
| PIQA | — | 78.8% |
| WinoGrande | — | 69.2% |

## Math

- GPT-5 Nano: 29.1 (#221)
- Llama 2-7B: 28.2 (#231)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Math | 1318 | 1042 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
| GSM8K | — | 16.7% |

## Knowledge

- GPT-5 Nano: 35.8 (#166)
- Llama 2-7B: 27.7 (#243)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Expert | 1321 | 1036 |
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
| ARC (AI2) Challenge | — | 45.9% |
| BoolQ | — | 77.9% |
| MMLU | — | 45.8% |
| OpenBookQA | — | 58.6% |
| TriviaQA | — | 73.7% |

## Multimodal

- GPT-5 Nano: 30.7 (#102)
- Llama 2-7B: —

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |
| ScienceQA | — | 43.1% |

## Multilingual

- GPT-5 Nano: 45.5 (#167)
- Llama 2-7B: 23.9 (#288)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Non-English | 1313 | 973 |
| LMArena Chinese | 1355 | 973 |
| LMArena German | 1329 | 978 |
| LMArena Russian | 1296 | 995 |
| LMArena Spanish | 1360 | 1007 |
| LMArena French | — | 969 |
| LMArena Korean | 1269 | — |

## Instruction Following

- GPT-5 Nano: 75.2 (#72)
- Llama 2-7B: 51.0 (#293)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Instruction Following | 1306 | 1006 |
| IFEval | 93.2% | — |

## Long Context

- GPT-5 Nano: 31.3 (#275)
- Llama 2-7B: 30.4 (#282)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Longer Query | 1313 | 999 |
| Fiction.LiveBench | 44.4% | — |

## Writing & Preference

- GPT-5 Nano: 39.4 (#244)
- Llama 2-7B: 28.1 (#293)

| Benchmark | GPT-5 Nano | Llama 2-7B |
|---|---|---|
| LMArena Text | 1320 | 1053 |
| LMArena Creative Writing | 1250 | 1033 |
| LMArena Multi-Turn | 1311 | 1029 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |

## FAQ

### Is GPT-5 Nano better than Llama 2-7B?

GPT-5 Nano is the stronger model overall, scoring 33.4 to 28.6 on the Noometry Index.

### Is GPT-5 Nano or Llama 2-7B better for coding?

GPT-5 Nano scores higher on coding benchmarks: 33.3 versus 28.7 in the Noometry coding category.

### How many benchmarks do GPT-5 Nano and Llama 2-7B share?

16 benchmarks have published results for both models. GPT-5 Nano has 48 scored results on Noometry and Llama 2-7B has 29.