# GPT-5.6 Sol vs Olmo 2 0325 32b Instruct

> GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 32.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-6-sol-vs-olmo-2-0325-32b-instruct
- Last updated: 2026-10-12
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. GPT-5.6 Sol scores higher in 8 categories and Olmo 2 0325 32b Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Sol leads 85.6 to 26.8.
- Olmo 2 0325 32b Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| Provider | OpenAI | Allen Institute for AI (Ai2) |
| Noometry Index | 65.0 | 32.7 |
| Rank | 7 | 254 |
| Context | 1.05M | — |
| Input $/M | $4 | — |
| Output $/M | $20 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-5.6 Sol: 65.1 (#7)
- Olmo 2 0325 32b Instruct: 35.2 (#227)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Coding | 1498 | 1210 |
| DeepSWE | 72.7% | — |
| FrontierCode | 47.5% | — |
| CursorBench | 41.7% | — |
| LMArena WebDev | 1618 | — |
| FrontierSWE | 32.2% | — |
| SciCode | 57.1% | — |
| GSO | 76.5% | — |
| WeirdML | 89.4% | — |
| MirrorCode | 20% | — |
| ALE-Bench | 2,177 | — |

## Agentic & Tool Use

- GPT-5.6 Sol: 50.3 (#7)
- Olmo 2 0325 32b Instruct: —

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| APEX-Agents | 51.4% | — |
| OSWorld 2.0 | 27.3% | — |
| τ²-bench Banking | 46.9% | — |
| PostTrainBench | 36.2% | — |
| BALROG | 60% | — |
| GBAEval | 52.6% | — |
| GDP.pdf | 30.7% | — |
| LMArena Search | 1257 | — |
| Vending-Bench 2 | 9,619 | — |

## Reasoning

- GPT-5.6 Sol: 74.8 (#8)
- Olmo 2 0325 32b Instruct: 23.6 (#175)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1484 | 1208 |
| ARC-AGI-2 | 92.5% | — |
| SimpleBench | 71.7% | — |
| Kagi LLM Benchmark | 67% | — |
| NYT Connections (extended) | 93.8% | — |
| ARC-AGI-1 | 97.5% | — |
| CritPt | 32.3% | — |
| Chess Puzzles | 64% | — |
| EnigmaEval | 37.1% | — |
| EBR-Bench | 44.8% | — |
| Mystery Game Puzzles | 58% | — |
| DTBench | 96% | — |
| LMCA | 59.2% | — |
| Surface Evolver Bench | 93.1% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 161.66 | — |

## Math

- GPT-5.6 Sol: 85.6 (#9)
- Olmo 2 0325 32b Instruct: 26.8 (#255)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Math | 1474 | 1208 |
| FrontierMath (Tiers 1-3) | 89.1% | — |
| FrontierMath Tier 4 | 82.9% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| Omni-MATH | — | 16.1% |
| FrontierMath Erdős | 0% | — |

## Knowledge

- GPT-5.6 Sol: 64.3 (#18)
- Olmo 2 0325 32b Instruct: 19.5 (#279)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| GPQA Diamond | 93.5% | — |
| SimpleQA Verified | 69.7% | — |
| MMLU-Pro | — | 41.4% |
| Vectara Hallucination Rate | 12.4% | — |
| GPQA (HELM) | — | 28.7% |
| LMArena Expert | 1516 | — |

## Multimodal

- GPT-5.6 Sol: 48.6 (#9)
- Olmo 2 0325 32b Instruct: —

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Vision | 1281 | — |
| Blueprint-Bench 2 | 33.6% | — |
| Furniture Assembly | 56.7% | — |
| LMArena Document | 1483 | — |

## Multilingual

- GPT-5.6 Sol: 55.3 (#32)
- Olmo 2 0325 32b Instruct: 34.8 (#248)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Non-English | 1452 | 1160 |
| LMArena Chinese | 1527 | 1192 |
| LMArena Russian | 1468 | 1187 |
| LMArena French | 1477 | — |
| LMArena German | 1476 | — |
| LMArena Japanese | 1471 | — |
| LMArena Korean | 1442 | — |
| LMArena Spanish | 1441 | — |

## Instruction Following

- GPT-5.6 Sol: 77.7 (#16)
- Olmo 2 0325 32b Instruct: 61.5 (#244)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Instruction Following | 1482 | 1186 |
| IFEval | — | 78% |

## Long Context

- GPT-5.6 Sol: 45.4 (#42)
- Olmo 2 0325 32b Instruct: 36.2 (#234)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Longer Query | 1480 | 1194 |

## Writing & Preference

- GPT-5.6 Sol: 73.3 (#12)
- Olmo 2 0325 32b Instruct: 42.1 (#236)

| Benchmark | GPT-5.6 Sol | Olmo 2 0325 32b Instruct |
|---|---|---|
| LMArena Text | 1457 | 1218 |
| LMArena Creative Writing | 1448 | 1199 |
| LMArena Multi-Turn | 1460 | 1221 |
| EQ-Bench Creative Writing | 1972 | — |
| WildBench | — | 73.4% |
| EQ-Bench 4 | 1250 | — |

## FAQ

### Is GPT-5.6 Sol better than Olmo 2 0325 32b Instruct?

GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 32.7 on the Noometry Index.

### Is GPT-5.6 Sol or Olmo 2 0325 32b Instruct better for coding?

GPT-5.6 Sol scores higher on coding benchmarks: 65.1 versus 35.2 in the Noometry coding category.

### How many benchmarks do GPT-5.6 Sol and Olmo 2 0325 32b Instruct share?

11 benchmarks have published results for both models. GPT-5.6 Sol has 65 scored results on Noometry and Olmo 2 0325 32b Instruct has 16.