Model comparison
Llama 4 Scout vs OLMo 2 Furious 13B
OLMo 2 Furious 13B is the stronger model overall, scoring 29.7 to 27.7 on the Noometry Index.
Last verified . 5 shared benchmarks.
Meta
Allen Institute for AI (Ai2)Summary
- They share 5 benchmarks with published results for both. Llama 4 Scout scores higher in 2 categories and OLMo 2 Furious 13B in 4 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama 4 Scout leads 31.9 to 18.3.
- The biggest single-benchmark swing is MMLU-Pro: 74.2% for Llama 4 Scout and 31% for OLMo 2 Furious 13B.
Side by side
| Llama 4 Scout | OLMo 2 Furious 13B | |
|---|---|---|
| Provider | Meta | Allen Institute for AI (Ai2) |
| Noometry Index | 27.7 | 29.7 |
| Released | 2025-04-05 | 2024-12-31 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.10 | — |
| Output $ / M tokens | $0.30 | — |
| Results tracked | 43 | 12 |
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Category by category
Coding OLMo 2 Furious 13B leads
Llama 4 Scout: 20.2 (#339), OLMo 2 Furious 13B: 28.6 (#313)
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| SWE-bench Verified (bash only) | 9.1% | — |
| SciCode | 17% | — |
| LiveBench Coding | — | 10.4% |
| LMArena Coding | 1286 | — |
| BigCodeBench Complete | 43.1% | — |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.6 (#119), OLMo 2 Furious 13B: —
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning OLMo 2 Furious 13B leads
Llama 4 Scout: 9.1 (#345), OLMo 2 Furious 13B: 15.5 (#314)
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 36.9% | — |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | — | 16.3% |
| LMArena Hard Prompts | 1266 | — |
| DTBench | 57.9% | — |
| LiveBench Data Analysis | — | 20.6% |
| LMCA | 12% | — |
| Epoch Capabilities Index | 129.64 | — |
| ForecastBench | 57.5 | — |
| LiveBench | — | 22.1% |
Math OLMo 2 Furious 13B leads
Llama 4 Scout: 19.6 (#286), OLMo 2 Furious 13B: 23.1 (#273)
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| Omni-MATH | 37.3% | 15.6% |
| OTIS Mock AIME 2024-2025 | 7.8% | — |
| LiveBench Math | — | 13.6% |
| LMArena Math | 1287 | — |
| MATH Level 5 | 62.3% | — |
| FrontierMath (Feb 2025 set) | 0% | — |
Knowledge Llama 4 Scout leads
Llama 4 Scout: 31.9 (#217), OLMo 2 Furious 13B: 18.3 (#283)
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| MMLU-Pro | 74.2% | 31% |
| GPQA (HELM) | 50.7% | 31.6% |
| GPQA Diamond | 51.8% | — |
| Vectara Hallucination Rate | 7.7% | — |
| LMArena Expert | 1235 | — |
Multimodal Not comparable
Llama 4 Scout: 32.2 (#102), OLMo 2 Furious 13B: —
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual Not comparable
Llama 4 Scout: 41.0 (#212), OLMo 2 Furious 13B: —
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| LMArena Non-English | 1252 | — |
| LMArena Chinese | 1255 | — |
| LMArena French | 1282 | — |
| LMArena German | 1272 | — |
| LMArena Japanese | 1206 | — |
| LMArena Korean | 1207 | — |
| LMArena Russian | 1263 | — |
| LMArena Spanish | 1278 | — |
Instruction Following Llama 4 Scout leads
Llama 4 Scout: 65.8 (#217), OLMo 2 Furious 13B: 60.9 (#248)
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| IFEval | 81.8% | 73% |
| LiveBench Instruction Following | — | 60.6% |
| LMArena Instruction Following | 1248 | — |
Long Context Not comparable
Llama 4 Scout: 27.5 (#294), OLMo 2 Furious 13B: —
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| Fiction.LiveBench | 36% | — |
| LMArena Longer Query | 1265 | — |
Writing & Preference OLMo 2 Furious 13B leads
Llama 4 Scout: 37.0 (#261), OLMo 2 Furious 13B: 42.9 (#230)
| Benchmark | Llama 4 Scout | OLMo 2 Furious 13B |
|---|---|---|
| WildBench | 78% | 68.9% |
| LMArena Text | 1279 | — |
| LMArena Creative Writing | 1249 | — |
| EQ-Bench Creative Writing | 783 | — |
| LMArena Multi-Turn | 1280 | — |
| LiveBench Language | — | 11.2% |
Frequently asked questions
Is Llama 4 Scout better than OLMo 2 Furious 13B?
OLMo 2 Furious 13B is the stronger model overall, scoring 29.7 to 27.7 on the Noometry Index.
Is Llama 4 Scout or OLMo 2 Furious 13B better for coding?
OLMo 2 Furious 13B scores higher on coding benchmarks: 28.6 versus 20.2 in the Noometry coding category.
How many benchmarks do Llama 4 Scout and OLMo 2 Furious 13B share?
5 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and OLMo 2 Furious 13B has 12.