# DeepSeek-V3 vs OLMo 2 Furious 13B

> DeepSeek-V3 is the stronger model overall, scoring 39.2 to 29.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-olmo-2-furious-13b
- Last updated: 2026-10-10
- Shared benchmarks: 12

## Summary

- They share 12 benchmarks with published results for both. DeepSeek-V3 scores higher in 6 categories and OLMo 2 Furious 13B in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3 leads 37.5 to 18.0.
- The biggest single-benchmark swing is LiveBench Coding: 70.9% for DeepSeek-V3 and 10.4% for OLMo 2 Furious 13B.

## Snapshot

| | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| Provider | DeepSeek | Allen Institute for AI (Ai2) |
| Noometry Index | 39.2 | 29.2 |
| Rank | 157 | 301 |
| Context | 164K | — |
| Input $/M | $0.24 | — |
| Output $/M | $0.90 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3: 41.9 (#99)
- OLMo 2 Furious 13B: 28.1 (#309)

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Coding | 70.9% | 10.4% |
| Aider Polyglot | 55.1% | — |
| SciCode | 35.8% | — |
| WeirdML | 36.1% | — |
| BigCodeBench Instruct | 50% | — |
| LMArena Coding | 1368 | — |
| BigCodeBench Complete | 62.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |

## Agentic & Tool Use

- DeepSeek-V3: —
- OLMo 2 Furious 13B: —

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| METR Time Horizons | 49.6% | — |

## Reasoning

- DeepSeek-V3: 20.0 (#226)
- OLMo 2 Furious 13B: 14.8 (#312)

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Reasoning | 65.8% | 16.3% |
| LiveBench Data Analysis | 60.9% | 20.6% |
| LiveBench | 66.9% | 22.1% |
| SimpleBench | 27.2% | — |
| Kagi LLM Benchmark | 52.3% | — |
| CritPt | 0% | — |
| LMArena Hard Prompts | 1365 | — |
| DTBench | 64.8% | — |
| LMCA | 15.5% | — |
| BIG-Bench Hard | 87.5% | — |
| Epoch Capabilities Index | 135.95 | — |
| ForecastBench | 59.1 | — |
| HellaSwag | 88.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |

## Math

- DeepSeek-V3: 30.4 (#208)
- OLMo 2 Furious 13B: 21.3 (#270)

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| Omni-MATH | 40.3% | 15.6% |
| LiveBench Math | 73.5% | 13.6% |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| LMArena Math | 1373 | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |

## Knowledge

- DeepSeek-V3: 37.5 (#147)
- OLMo 2 Furious 13B: 18.0 (#278)

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| MMLU-Pro | 72.3% | 31% |
| GPQA (HELM) | 53.8% | 31.6% |
| GPQA Diamond | 67.6% | — |
| Confabulations | 26.1% | — |
| Vectara Hallucination Rate | 6.1% | — |
| LMArena Expert | 1352 | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |

## Multilingual

- DeepSeek-V3: 48.8 (#138)
- OLMo 2 Furious 13B: —

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1358 | — |
| LMArena Chinese | 1390 | — |
| LMArena French | 1386 | — |
| LMArena German | 1374 | — |
| LMArena Japanese | 1333 | — |
| LMArena Korean | 1321 | — |
| LMArena Russian | 1372 | — |
| LMArena Spanish | 1358 | — |

## Instruction Following

- DeepSeek-V3: 73.0 (#125)
- OLMo 2 Furious 13B: 61.1 (#243)

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| LiveBench Instruction Following | 81.5% | 60.6% |
| IFEval | 83.2% | 73% |
| LMArena Instruction Following | 1345 | — |

## Long Context

- DeepSeek-V3: 34.0 (#248)
- OLMo 2 Furious 13B: —

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| Fiction.LiveBench | 50% | — |
| LMArena Longer Query | 1353 | — |

## Writing & Preference

- DeepSeek-V3: 57.6 (#124)
- OLMo 2 Furious 13B: 43.0 (#226)

| Benchmark | DeepSeek-V3 | OLMo 2 Furious 13B |
|---|---|---|
| WildBench | 83% | 68.9% |
| LiveBench Language | 49.1% | 11.2% |
| LMArena Text | 1375 | — |
| LMArena Creative Writing | 1364 | — |
| Short-Story Creative Writing | 77% | — |
| EQ-Bench Creative Writing | 1472 | — |
| LMArena Multi-Turn | 1389 | — |

## FAQ

### Is DeepSeek-V3 better than OLMo 2 Furious 13B?

DeepSeek-V3 is the stronger model overall, scoring 39.2 to 29.2 on the Noometry Index.

### Is DeepSeek-V3 or OLMo 2 Furious 13B better for coding?

DeepSeek-V3 scores higher on coding benchmarks: 41.9 versus 28.1 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3 and OLMo 2 Furious 13B share?

12 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and OLMo 2 Furious 13B has 12.