Model comparison
Llama 4 Scout vs phi-3-medium 14B
phi-3-medium 14B is the stronger model overall, scoring 29.7 to 27.7 on the Noometry Index.
Last verified . 4 shared benchmarks.
Summary
- They share 4 benchmarks with published results for both. Llama 4 Scout scores higher in 1 category and phi-3-medium 14B in 2 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama 4 Scout leads 31.9 to 9.1.
- The biggest single-benchmark swing is MATH Level 5: 62.3% for Llama 4 Scout and 17.6% for phi-3-medium 14B.
Side by side
| Llama 4 Scout | phi-3-medium 14B | |
|---|---|---|
| Provider | Meta | Microsoft |
| Noometry Index | 27.7 | 29.7 |
| Released | 2025-04-05 | 2024-04-23 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.10 | — |
| Output $ / M tokens | $0.30 | — |
| Results tracked | 43 | 13 |
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Category by category
Coding phi-3-medium 14B leads
Llama 4 Scout: 20.2 (#339), phi-3-medium 14B: 36.8 (#201)
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| BigCodeBench Complete | 43.1% | 48.7% |
| SWE-bench Verified (bash only) | 9.1% | — |
| SciCode | 17% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1286 | — |
Agentic & Tool Use Not comparable
Llama 4 Scout: 24.6 (#119), phi-3-medium 14B: —
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 28.1% | — |
Reasoning Not comparable
Llama 4 Scout: 9.1 (#345), phi-3-medium 14B: —
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| Epoch Capabilities Index | 129.64 | 121.23 |
| ARC-AGI-2 | 0% | — |
| Kagi LLM Benchmark | 36.9% | — |
| ARC-AGI-1 | 0.5% | — |
| CritPt | 0% | — |
| LMArena Hard Prompts | 1266 | — |
| DTBench | 57.9% | — |
| LMCA | 12% | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| ForecastBench | 57.5 | — |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |
Math phi-3-medium 14B leads
Llama 4 Scout: 19.6 (#286), phi-3-medium 14B: 27.3 (#250)
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| MATH Level 5 | 62.3% | 17.6% |
| OTIS Mock AIME 2024-2025 | 7.8% | — |
| Omni-MATH | 37.3% | — |
| LMArena Math | 1287 | — |
| FrontierMath (Feb 2025 set) | 0% | — |
Knowledge Llama 4 Scout leads
Llama 4 Scout: 31.9 (#217), phi-3-medium 14B: 9.1 (#306)
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | 51.8% | 27.6% |
| MMLU-Pro | 74.2% | — |
| Vectara Hallucination Rate | 7.7% | — |
| GPQA (HELM) | 50.7% | — |
| LMArena Expert | 1235 | — |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |
Multimodal Not comparable
Llama 4 Scout: 32.2 (#102), phi-3-medium 14B: —
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| LMArena Vision | 1118 | — |
| SpatialViz-Bench | 34.2% | — |
Multilingual Not comparable
Llama 4 Scout: 41.0 (#212), phi-3-medium 14B: —
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| 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 Not comparable
Llama 4 Scout: 65.8 (#217), phi-3-medium 14B: —
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| IFEval | 81.8% | — |
| LMArena Instruction Following | 1248 | — |
Long Context Not comparable
Llama 4 Scout: 27.5 (#294), phi-3-medium 14B: —
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| Fiction.LiveBench | 36% | — |
| LMArena Longer Query | 1265 | — |
Writing & Preference Not comparable
Llama 4 Scout: 37.0 (#261), phi-3-medium 14B: —
| Benchmark | Llama 4 Scout | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1279 | — |
| LMArena Creative Writing | 1249 | — |
| EQ-Bench Creative Writing | 783 | — |
| WildBench | 78% | — |
| LMArena Multi-Turn | 1280 | — |
Frequently asked questions
Is Llama 4 Scout better than phi-3-medium 14B?
phi-3-medium 14B is the stronger model overall, scoring 29.7 to 27.7 on the Noometry Index.
Is Llama 4 Scout or phi-3-medium 14B better for coding?
phi-3-medium 14B scores higher on coding benchmarks: 36.8 versus 20.2 in the Noometry coding category.
How many benchmarks do Llama 4 Scout and phi-3-medium 14B share?
4 benchmarks have published results for both models. Llama 4 Scout has 43 scored results on Noometry and phi-3-medium 14B has 13.