# GPT-6.1 Sol vs Llama 2-13B

> GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 29.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-6-1-sol-vs-llama-2-13b
- Last updated: 2026-10-12
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. GPT-6.1 Sol 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-6.1 Sol leads 81.9 to 12.8.
- The biggest single-benchmark swing is Chess Puzzles: 61% for GPT-6.1 Sol and 0% for Llama 2-13B.
- Llama 2-13B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 65.6 | 29.6 |
| Rank | 6 | 309 |
| Context | 1.05M | — |
| Input $/M | $2 | — |
| Output $/M | $10 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-6.1 Sol: 63.2 (#8)
- Llama 2-13B: 30.9 (#291)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1487 | 1062 |
| DeepSWE | 75.2% | — |
| FrontierCode | 50.2% | — |
| LMArena WebDev | 1755 | — |
| SciCode | 55.8% | — |

## Agentic & Tool Use

- GPT-6.1 Sol: 39.6 (#26)
- Llama 2-13B: —

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| APEX-Agents | 60% | — |
| GDP.pdf | 32% | — |

## Reasoning

- GPT-6.1 Sol: 81.9 (#2)
- Llama 2-13B: 12.8 (#337)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| Chess Puzzles | 61% | 0% |
| LMArena Hard Prompts | 1466 | 1051 |
| Epoch Capabilities Index | 166.09 | 106.17 |
| ARC-AGI-2 | 94.2% | — |
| NYT Connections (extended) | 95.5% | — |
| ARC-AGI-1 | 98.5% | — |
| CritPt | 31.7% | — |
| EBR-Bench | 54.3% | — |
| Mystery Game Puzzles | 80% | — |
| DTBench | — | 42.2% |
| BIG-Bench Hard | — | 58.2% |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |

## Math

- GPT-6.1 Sol: 93.7 (#1)
- Llama 2-13B: 31.1 (#229)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Math | 1464 | 1065 |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 100% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 99% | — |
| GSM8K | — | 36.9% |

## Knowledge

- GPT-6.1 Sol: 71.8 (#4)
- Llama 2-13B: 28.1 (#249)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1502 | 1030 |
| GPQA Diamond | 95.4% | — |
| SimpleQA Verified | 73.9% | — |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |

## Multimodal

- GPT-6.1 Sol: 52.7 (#5)
- Llama 2-13B: —

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Vision | 1288 | — |
| Furniture Assembly | 80% | — |
| ScienceQA | — | 55.8% |

## Multilingual

- GPT-6.1 Sol: 54.3 (#46)
- Llama 2-13B: 26.5 (#279)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1438 | 1024 |
| LMArena Chinese | 1477 | 1001 |
| LMArena Russian | 1455 | 1055 |
| LMArena French | — | 1044 |
| LMArena German | — | 1009 |
| LMArena Japanese | — | 894 |
| LMArena Korean | — | 953 |
| LMArena Spanish | — | 1087 |

## Instruction Following

- GPT-6.1 Sol: 77.0 (#29)
- Llama 2-13B: 53.3 (#287)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1468 | 1045 |

## Long Context

- GPT-6.1 Sol: 44.9 (#54)
- Llama 2-13B: 32.3 (#269)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1465 | 1064 |

## Writing & Preference

- GPT-6.1 Sol: 63.6 (#63)
- Llama 2-13B: 29.8 (#289)

| Benchmark | GPT-6.1 Sol | Llama 2-13B |
|---|---|---|
| LMArena Text | 1447 | 1084 |
| LMArena Creative Writing | 1432 | 1047 |
| LMArena Multi-Turn | 1449 | 1050 |

## FAQ

### Is GPT-6.1 Sol better than Llama 2-13B?

GPT-6.1 Sol is the stronger model overall, scoring 65.6 to 29.6 on the Noometry Index.

### Is GPT-6.1 Sol or Llama 2-13B better for coding?

GPT-6.1 Sol scores higher on coding benchmarks: 63.2 versus 30.9 in the Noometry coding category.

### How many benchmarks do GPT-6.1 Sol and Llama 2-13B share?

14 benchmarks have published results for both models. GPT-6.1 Sol has 34 scored results on Noometry and Llama 2-13B has 32.