# GPT-5.2 vs Llama 2-13B

> GPT-5.2 is the stronger model overall, scoring 54.1 to 29.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-2-vs-llama-2-13b
- Last updated: 2026-10-12
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. GPT-5.2 scores higher in 8 categories and Llama 2-13B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.2 leads 50.2 to 12.8.
- The biggest single-benchmark swing is Chess Puzzles: 49% for GPT-5.2 and 0% for Llama 2-13B.
- Llama 2-13B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.2 | Llama 2-13B |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 54.1 | 29.6 |
| Rank | 34 | 309 |
| Context | 400K | — |
| Input $/M | $1.75 | — |
| Output $/M | $14 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-5.2: 51.6 (#37)
- Llama 2-13B: 30.9 (#291)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1447 | 1062 |
| SWE-bench Verified | 73.8% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1416 | — |
| SWE-bench Multilingual | 66.7% | — |
| GSO | 27.4% | — |
| WeirdML | 72.2% | — |
| ALE-Bench | 1,294 | — |
| AlgoTune | 2.05 | — |

## Agentic & Tool Use

- GPT-5.2: 40.2 (#24)
- Llama 2-13B: —

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| Terminal-Bench | 64.9% | — |
| Berkeley Function Calling Leaderboard | 55.9% | — |
| GDPval | 49.7% | — |
| Remote Labor Index | 2.5% | — |
| τ²-bench Airline | 83% | — |
| τ²-bench Banking | 32.2% | — |
| τ²-bench Retail | 81.6% | — |
| τ²-bench Telecom | 89.7% | — |
| DeepResearch Bench | 41.1% | — |
| LMArena Search | 1207 | — |
| METR Time Horizons | 75.3% | — |
| Vending-Bench 2 | 3,591 | — |

## Reasoning

- GPT-5.2: 50.2 (#35)
- Llama 2-13B: 12.8 (#337)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| Chess Puzzles | 49% | 0% |
| LMArena Hard Prompts | 1445 | 1051 |
| DTBench | 90.9% | 42.2% |
| Epoch Capabilities Index | 153.45 | 106.17 |
| ARC-AGI-2 | 52.9% | — |
| SimpleBench | 45.8% | — |
| Kagi LLM Benchmark | 73.3% | — |
| NYT Connections (extended) | 83.6% | — |
| ARC-AGI-1 | 86.2% | — |
| EnigmaEval | 10.4% | — |
| EBR-Bench | 23% | — |
| Mystery Game Puzzles | 23% | — |
| LMCA | 43.9% | — |
| BIG-Bench Hard | — | 58.2% |
| ForecastBench | 60.1 | — |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |

## Math

- GPT-5.2: 60.0 (#38)
- Llama 2-13B: 31.1 (#229)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Math | 1440 | 1065 |
| FrontierMath (Tiers 1-3) | 67.4% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 72% | — |
| OTIS Mock AIME 2024-2025 | 96.1% | — |
| ProofBench | 15% | — |
| FrontierMath (Feb 2025 set) | 40.7% | — |
| FrontierMath Tier 4 (v1) | 18.8% | — |
| GSM8K | — | 36.9% |

## Knowledge

- GPT-5.2: 59.3 (#32)
- Llama 2-13B: 28.1 (#249)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1445 | 1030 |
| GPQA Diamond | 91.4% | — |
| Humanity's Last Exam | 27.8% | — |
| SimpleQA Verified | 37.1% | — |
| Vectara Hallucination Rate | 8.4% | — |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |

## Multimodal

- GPT-5.2: 51.3 (#7)
- Llama 2-13B: —

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Vision | 1268 | — |
| VPCT | 84% | — |
| Furniture Assembly | 38.3% | — |
| LMArena Document | 1405 | — |
| ScienceQA | — | 55.8% |

## Multilingual

- GPT-5.2: 53.4 (#67)
- Llama 2-13B: 26.5 (#279)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1425 | 1024 |
| LMArena Chinese | 1460 | 1001 |
| LMArena French | 1455 | 1044 |
| LMArena German | 1448 | 1009 |
| LMArena Japanese | 1420 | 894 |
| LMArena Korean | 1392 | 953 |
| LMArena Russian | 1440 | 1055 |
| LMArena Spanish | 1433 | 1087 |

## Instruction Following

- GPT-5.2: 74.7 (#89)
- Llama 2-13B: 53.3 (#287)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1417 | 1045 |

## Long Context

- GPT-5.2: 44.0 (#78)
- Llama 2-13B: 32.3 (#269)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1428 | 1064 |
| CL-bench | 18.2% | — |

## Writing & Preference

- GPT-5.2: 66.8 (#32)
- Llama 2-13B: 29.8 (#289)

| Benchmark | GPT-5.2 | Llama 2-13B |
|---|---|---|
| LMArena Text | 1439 | 1084 |
| LMArena Creative Writing | 1401 | 1047 |
| LMArena Multi-Turn | 1458 | 1050 |
| EQ-Bench Creative Writing | 1703 | — |

## FAQ

### Is GPT-5.2 better than Llama 2-13B?

GPT-5.2 is the stronger model overall, scoring 54.1 to 29.6 on the Noometry Index.

### Is GPT-5.2 or Llama 2-13B better for coding?

GPT-5.2 scores higher on coding benchmarks: 51.6 versus 30.9 in the Noometry coding category.

### How many benchmarks do GPT-5.2 and Llama 2-13B share?

20 benchmarks have published results for both models. GPT-5.2 has 67 scored results on Noometry and Llama 2-13B has 32.