Model comparison
Llama 3-8B vs Phi 3 Small 8k Instruct
Phi 3 Small 8k Instruct is the stronger model overall, scoring 29.3 to 25.5 on the Noometry Index.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. Llama 3-8B scores higher in 5 categories and Phi 3 Small 8k Instruct in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Phi 3 Small 8k Instruct leads 29.1 to 7.8.
Side by side
| Llama 3-8B | Phi 3 Small 8k Instruct | |
|---|---|---|
| Provider | Meta | Microsoft |
| Noometry Index | 25.5 | 29.3 |
| Released | 2024-04-18 | 2024-04-23 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 34 | 32 |
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Category by category
Coding Llama 3-8B leads
Llama 3-8B: 31.0 (#289), Phi 3 Small 8k Instruct: 27.9 (#318)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Coding | 1152 | 1101 |
| BigCodeBench Instruct | 31.9% | — |
| LiveBench Coding | — | 20.3% |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Reasoning Too close to call
Llama 3-8B: 14.3 (#326), Phi 3 Small 8k Instruct: 14.8 (#323)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Hard Prompts | 1133 | 1100 |
| Adversarial NLI | 57.3% | 58.1% |
| WinoGrande | 75.7% | 81.5% |
| Chess Puzzles | 0% | — |
| LiveBench Reasoning | — | 15.9% |
| DTBench | 43.9% | — |
| LiveBench Data Analysis | — | 30.3% |
| BIG-Bench Hard | — | 79.1% |
| Epoch Capabilities Index | 116.45 | — |
| ForecastBench | 58.6 | — |
| HellaSwag | — | 77% |
| LiveBench | — | 24% |
Math Phi 3 Small 8k Instruct leads
Llama 3-8B: 8.8 (#323), Phi 3 Small 8k Instruct: 27.6 (#248)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Math | 1151 | 1151 |
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LiveBench Math | — | 17.6% |
| MATH Level 5 | 6.1% | — |
Knowledge Phi 3 Small 8k Instruct leads
Llama 3-8B: 7.8 (#308), Phi 3 Small 8k Instruct: 29.1 (#240)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Expert | 1113 | 1067 |
| ARC (AI2) Challenge | 82.8% | 90.7% |
| MMLU | 68.8% | 75.7% |
| OpenBookQA | 82.6% | 88% |
| TriviaQA | 67.7% | 58.1% |
| GPQA Diamond | 26.1% | — |
Multilingual Llama 3-8B leads
Llama 3-8B: 30.8 (#261), Phi 3 Small 8k Instruct: 28.5 (#272)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Non-English | 1098 | 1058 |
| LMArena Chinese | 1076 | 1061 |
| LMArena French | 1159 | 1135 |
| LMArena German | 1104 | 1080 |
| LMArena Japanese | 967 | 966 |
| LMArena Korean | 1004 | 894 |
| LMArena Russian | 1109 | 1111 |
| LMArena Spanish | 1173 | 1111 |
Instruction Following Llama 3-8B leads
Llama 3-8B: 58.4 (#260), Phi 3 Small 8k Instruct: 51.9 (#292)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Instruction Following | 1127 | 1087 |
| LiveBench Instruction Following | — | 47.2% |
Long Context Llama 3-8B leads
Llama 3-8B: 34.2 (#251), Phi 3 Small 8k Instruct: 33.0 (#267)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Longer Query | 1128 | 1088 |
Writing & Preference Llama 3-8B leads
Llama 3-8B: 37.5 (#256), Phi 3 Small 8k Instruct: 31.1 (#284)
| Benchmark | Llama 3-8B | Phi 3 Small 8k Instruct |
|---|---|---|
| LMArena Text | 1166 | 1110 |
| LMArena Creative Writing | 1150 | 1083 |
| LMArena Multi-Turn | 1152 | 1068 |
| LiveBench Language | — | 12.9% |
Frequently asked questions
Is Llama 3-8B better than Phi 3 Small 8k Instruct?
Phi 3 Small 8k Instruct is the stronger model overall, scoring 29.3 to 25.5 on the Noometry Index.
Is Llama 3-8B or Phi 3 Small 8k Instruct better for coding?
Llama 3-8B scores higher on coding benchmarks: 31.0 versus 27.9 in the Noometry coding category.
How many benchmarks do Llama 3-8B and Phi 3 Small 8k Instruct share?
23 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Phi 3 Small 8k Instruct has 32.