# GPT-5.5 vs Llama 13b

> GPT-5.5 is the stronger model overall, scoring 63.4 to 23.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-5-vs-llama-13b
- Last updated: 2026-10-10
- Shared benchmarks: 9

## Summary

- They share 9 benchmarks with published results for both. GPT-5.5 scores higher in 6 categories and Llama 13b in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.5 leads 72.7 to 13.4.
- Llama 13b has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.5 | Llama 13b |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 63.4 | 23.9 |
| Rank | 8 | 344 |
| Context | 1.05M | — |
| Input $/M | $5 | — |
| Output $/M | $30 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-5.5: 58.3 (#13)
- Llama 13b: 20.9 (#332)

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| LMArena Coding | 1494 | 683 |
| SWE-bench Verified | 80.6% | — |
| DeepSWE | 67% | — |
| FrontierCode | 43% | — |
| LMArena WebDev | 1512 | — |
| SciCode | 56.1% | — |
| GSO | 40.2% | — |
| WeirdML | 84.9% | — |
| MirrorCode | 10% | — |
| ALE-Bench | 1,943 | — |

## Agentic & Tool Use

- GPT-5.5: 50.7 (#6)
- Llama 13b: —

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| Terminal-Bench | 84.7% | — |
| APEX-Agents | 55.1% | — |
| OSWorld 2.0 | 13% | — |
| Remote Labor Index | 6.3% | — |
| τ²-bench Banking | 44.6% | — |
| DeepResearch Bench | 54% | — |
| PostTrainBench | 27.2% | — |
| ExploitBench | 47.4% | — |
| GBAEval | 53.2% | — |
| GDP.pdf | 26% | — |
| LMArena Search | 1242 | — |
| Vending-Bench 2 | 7,524 | — |

## Reasoning

- GPT-5.5: 72.7 (#8)
- Llama 13b: 13.4 (#327)

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| LMArena Hard Prompts | 1489 | 728 |
| Epoch Capabilities Index | 159.25 | 100.09 |
| ARC-AGI-2 | 85% | — |
| SimpleBench | 69% | — |
| Kagi LLM Benchmark | 88.8% | — |
| NYT Connections (extended) | 96.2% | — |
| ARC-AGI-1 | 95% | — |
| CritPt | 27.1% | — |
| Chess Puzzles | 54% | — |
| EBR-Bench | 34.3% | — |
| Mystery Game Puzzles | 56% | — |
| DTBench | 96% | — |
| LMCA | 54.3% | — |
| Surface Evolver Bench | 88.1% | — |
| Bench to the Future 3 | 0.14 | — |
| BIG-Bench Hard | — | 37.9% |
| ForecastBench | 60.6 | — |
| HellaSwag | — | 79.2% |
| LAMBADA | — | 75.2% |
| PIQA | — | 80.1% |
| WinoGrande | — | 73% |

## Math

- GPT-5.5: 81.5 (#9)
- Llama 13b: 24.4 (#259)

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| LMArena Math | 1486 | 838 |
| FrontierMath (Tiers 1-3) | 85.3% | — |
| FrontierMath Tier 4 | 72.5% | — |
| MathArena Final-Answer Competitions | 94.3% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 50% | — |
| FrontierMath (Feb 2025 set) | 51.7% | — |
| FrontierMath Erdős | 0% | — |
| FrontierMath Tier 4 (v1) | 35.4% | — |
| GSM8K | — | 20.6% |

## Knowledge

- GPT-5.5: 64.4 (#14)
- Llama 13b: —

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| GPQA Diamond | 94% | — |
| SimpleQA Verified | 63% | — |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1508 | — |
| ARC (AI2) Challenge | — | 52.7% |
| BoolQ | — | 78.7% |
| MMLU | — | 47.7% |
| OpenBookQA | — | 56.4% |
| TriviaQA | — | 77.9% |

## Multimodal

- GPT-5.5: 47.1 (#11)
- Llama 13b: —

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| LMArena Vision | 1297 | — |
| Blueprint-Bench 2 | 36.2% | — |
| Furniture Assembly | 44.2% | — |
| LMArena Document | 1486 | — |
| ScienceQA | — | 43.3% |

## Multilingual

- GPT-5.5: 56.5 (#19)
- Llama 13b: 16.8 (#292)

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| LMArena Non-English | 1467 | 819 |
| LMArena Chinese | 1535 | — |
| LMArena French | 1486 | — |
| LMArena German | 1478 | — |
| LMArena Japanese | 1498 | — |
| LMArena Korean | 1461 | — |
| LMArena Russian | 1473 | — |
| LMArena Spanish | 1469 | — |

## Instruction Following

- GPT-5.5: 77.7 (#18)
- Llama 13b: 36.9 (#300)

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| LMArena Instruction Following | 1479 | 781 |

## Long Context

- GPT-5.5: 48.3 (#12)
- Llama 13b: —

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| CL-bench Life | 22.2% | — |
| LMArena Longer Query | 1484 | — |

## Writing & Preference

- GPT-5.5: 72.8 (#13)
- Llama 13b: 13.9 (#307)

| Benchmark | GPT-5.5 | Llama 13b |
|---|---|---|
| LMArena Text | 1471 | 834 |
| LMArena Creative Writing | 1455 | 794 |
| LMArena Multi-Turn | 1477 | 753 |
| EQ-Bench Creative Writing | 1844 | — |
| EQ-Bench 4 | 1315 | — |

## FAQ

### Is GPT-5.5 better than Llama 13b?

GPT-5.5 is the stronger model overall, scoring 63.4 to 23.9 on the Noometry Index.

### Is GPT-5.5 or Llama 13b better for coding?

GPT-5.5 scores higher on coding benchmarks: 58.3 versus 20.9 in the Noometry coding category.

### How many benchmarks do GPT-5.5 and Llama 13b share?

9 benchmarks have published results for both models. GPT-5.5 has 71 scored results on Noometry and Llama 13b has 21.