Model comparison
Llama 2-13B vs Phi-4
Phi-4 is the stronger model overall, scoring 30.9 to 29.1 on the Noometry Index.
Last verified . 20 shared benchmarks.
Meta
MicrosoftSummary
- They share 20 benchmarks with published results for both. Llama 2-13B scores higher in 1 category and Phi-4 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Phi-4 leads 37.4 to 26.7.
Side by side
| Llama 2-13B | Phi-4 | |
|---|---|---|
| Provider | Meta | Microsoft |
| Noometry Index | 29.1 | 30.9 |
| Released | 2023-07-18 | 2024-12-11 |
| Weights | Open | Open |
| Context window | — | 128K |
| Max output | — | 4K |
| Input $ / M tokens | — | $0.07 |
| Output $ / M tokens | — | $0.14 |
| Results tracked | 32 | 37 |
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Category by category
Coding Phi-4 leads
Llama 2-13B: 30.4 (#287), Phi-4: 33.8 (#237)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| LMArena Coding | 1062 | 1231 |
| BigCodeBench Instruct | — | 45.5% |
| LiveBench Coding | — | 30.7% |
| BigCodeBench Complete | — | 55.4% |
Agentic & Tool Use Not comparable
Llama 2-13B: —, Phi-4: 22.6 (#120)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 28.8% |
| BALROG | — | 11.6% |
Reasoning Phi-4 leads
Llama 2-13B: 12.3 (#333), Phi-4: 17.0 (#287)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| Chess Puzzles | 0% | 1% |
| LMArena Hard Prompts | 1051 | 1220 |
| Epoch Capabilities Index | 105.8 | 130.43 |
| LiveBench Reasoning | — | 47.8% |
| DTBench | 42.2% | — |
| LiveBench Data Analysis | — | 45.2% |
| BIG-Bench Hard | 58.2% | — |
| HellaSwag | 80.7% | — |
| LAMBADA | 76.5% | — |
| LiveBench | — | 41.6% |
| PIQA | 80.8% | — |
| WinoGrande | 72.8% | — |
Math Llama 2-13B leads
Llama 2-13B: 28.7 (#226), Phi-4: 19.6 (#279)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| LMArena Math | 1065 | 1246 |
| OTIS Mock AIME 2024-2025 | — | 13.8% |
| LiveBench Math | — | 42% |
| MATH Level 5 | — | 64.9% |
| GSM8K | 36.9% | — |
Knowledge Phi-4 leads
Llama 2-13B: 27.5 (#244), Phi-4: 32.5 (#204)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| LMArena Expert | 1030 | 1203 |
| MMLU | 55.6% | 84.8% |
| GPQA Diamond | — | 56.1% |
| Confabulations | — | 29.4% |
| Vectara Hallucination Rate | — | 3.7% |
| ARC (AI2) Challenge | 60.3% | — |
| BoolQ | 82.4% | — |
| OpenBookQA | 57% | — |
| TriviaQA | 79.6% | — |
Multimodal Not comparable
Llama 2-13B: —, Phi-4: —
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| ScienceQA | 55.8% | — |
Multilingual Phi-4 leads
Llama 2-13B: 26.7 (#274), Phi-4: 37.4 (#232)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| LMArena Non-English | 1024 | 1197 |
| LMArena Chinese | 1001 | 1211 |
| LMArena French | 1043 | 1223 |
| LMArena German | 1009 | 1222 |
| LMArena Japanese | 894 | 1158 |
| LMArena Korean | 953 | 1151 |
| LMArena Russian | 1055 | 1209 |
| LMArena Spanish | 1086 | 1234 |
Instruction Following Phi-4 leads
Llama 2-13B: 53.5 (#282), Phi-4: 60.6 (#246)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| LMArena Instruction Following | 1046 | 1201 |
| LiveBench Instruction Following | — | 58.4% |
Long Context Phi-4 leads
Llama 2-13B: 32.3 (#264), Phi-4: 36.9 (#221)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| LMArena Longer Query | 1064 | 1217 |
Writing & Preference Phi-4 leads
Llama 2-13B: 30.0 (#284), Phi-4: 40.7 (#239)
| Benchmark | Llama 2-13B | Phi-4 |
|---|---|---|
| LMArena Text | 1085 | 1217 |
| LMArena Creative Writing | 1047 | 1182 |
| LMArena Multi-Turn | 1050 | 1206 |
| Short-Story Creative Writing | — | 62.6% |
| LiveBench Language | — | 25.6% |
Frequently asked questions
Is Llama 2-13B better than Phi-4?
Phi-4 is the stronger model overall, scoring 30.9 to 29.1 on the Noometry Index.
Is Llama 2-13B or Phi-4 better for coding?
Phi-4 scores higher on coding benchmarks: 33.8 versus 30.4 in the Noometry coding category.
How many benchmarks do Llama 2-13B and Phi-4 share?
20 benchmarks have published results for both models. Llama 2-13B has 32 scored results on Noometry and Phi-4 has 37.