Model comparison
Llama 3-8B vs Phi-4 Mini
Phi-4 Mini is the stronger model overall, scoring 30.9 to 25.5 on the Noometry Index.
Last verified . 0 shared benchmarks.
Meta
MicrosoftSummary
- The widest gap is in knowledge, where Phi-4 Mini leads 25.3 to 7.8.
Side by side
| Llama 3-8B | Phi-4 Mini | |
|---|---|---|
| Provider | Meta | Microsoft |
| Noometry Index | 25.5 | 30.9 |
| Released | 2024-04-18 | 2024-12-11 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.075 |
| Output $ / M tokens | — | $0.30 |
| Results tracked | 34 | 3 |
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Category by category
Coding Llama 3-8B leads
Llama 3-8B: 31.0 (#289), Phi-4 Mini: 28.1 (#317)
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| SciCode | — | 10.8% |
| BigCodeBench Instruct | 31.9% | — |
| LMArena Coding | 1152 | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Reasoning Phi-4 Mini leads
Llama 3-8B: 14.3 (#326), Phi-4 Mini: 22.4 (#195)
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| CritPt | — | 0% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1133 | — |
| DTBench | 43.9% | — |
| Adversarial NLI | 57.3% | — |
| Epoch Capabilities Index | 116.45 | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |
Math Not comparable
Llama 3-8B: 8.8 (#323), Phi-4 Mini: —
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |
Knowledge Phi-4 Mini leads
Llama 3-8B: 7.8 (#308), Phi-4 Mini: 25.3 (#262)
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| GPQA Diamond | 26.1% | — |
| Vectara Hallucination Rate | — | 23.5% |
| LMArena Expert | 1113 | — |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |
Multilingual Not comparable
Llama 3-8B: 30.8 (#261), Phi-4 Mini: —
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| LMArena Non-English | 1098 | — |
| LMArena Chinese | 1076 | — |
| LMArena French | 1159 | — |
| LMArena German | 1104 | — |
| LMArena Japanese | 967 | — |
| LMArena Korean | 1004 | — |
| LMArena Russian | 1109 | — |
| LMArena Spanish | 1173 | — |
Instruction Following Not comparable
Llama 3-8B: 58.4 (#260), Phi-4 Mini: —
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| LMArena Instruction Following | 1127 | — |
Long Context Not comparable
Llama 3-8B: 34.2 (#251), Phi-4 Mini: —
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| LMArena Longer Query | 1128 | — |
Writing & Preference Not comparable
Llama 3-8B: 37.5 (#256), Phi-4 Mini: —
| Benchmark | Llama 3-8B | Phi-4 Mini |
|---|---|---|
| LMArena Text | 1166 | — |
| LMArena Creative Writing | 1150 | — |
| LMArena Multi-Turn | 1152 | — |
Frequently asked questions
Is Llama 3-8B better than Phi-4 Mini?
Phi-4 Mini is the stronger model overall, scoring 30.9 to 25.5 on the Noometry Index.
Is Llama 3-8B or Phi-4 Mini better for coding?
Llama 3-8B scores higher on coding benchmarks: 31.0 versus 28.1 in the Noometry coding category.
How many benchmarks do Llama 3-8B and Phi-4 Mini share?
0 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Phi-4 Mini has 3.