Model comparison
Llama 3-8B vs Qwen2.5-Coder (1.5B)
Llama 3-8B has enough public results to be ranked (#344); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.
Last verified . 4 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 4 benchmarks with published results for both.
Side by side
| Llama 3-8B | Qwen2.5-Coder (1.5B) | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 25.5 | — |
| Released | 2024-04-18 | 2024-09-18 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 34 | 6 |
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Category by category
Coding Not comparable
Llama 3-8B: 31.0 (#289), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| BigCodeBench Instruct | 31.9% | — |
| LMArena Coding | 1152 | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Reasoning Not comparable
Llama 3-8B: 14.3 (#326), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| Epoch Capabilities Index | 116.45 | 113.14 |
| WinoGrande | 75.7% | 72.9% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1133 | — |
| DTBench | 43.9% | — |
| Adversarial NLI | 57.3% | — |
| ForecastBench | 58.6 | — |
| HellaSwag | — | 76.8% |
Math Not comparable
Llama 3-8B: 8.8 (#323), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |
| GSM8K | — | 86.7% |
Knowledge Not comparable
Llama 3-8B: 7.8 (#308), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| ARC (AI2) Challenge | 82.8% | 60.9% |
| MMLU | 68.8% | 68% |
| GPQA Diamond | 26.1% | — |
| LMArena Expert | 1113 | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |
Multilingual Not comparable
Llama 3-8B: 30.8 (#261), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| 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), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Instruction Following | 1127 | — |
Long Context Not comparable
Llama 3-8B: 34.2 (#251), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Longer Query | 1128 | — |
Writing & Preference Not comparable
Llama 3-8B: 37.5 (#256), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Text | 1166 | — |
| LMArena Creative Writing | 1150 | — |
| LMArena Multi-Turn | 1152 | — |
Frequently asked questions
Is Llama 3-8B better than Qwen2.5-Coder (1.5B)?
Llama 3-8B has enough public results to be ranked (#344); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.
How many benchmarks do Llama 3-8B and Qwen2.5-Coder (1.5B) share?
4 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Qwen2.5-Coder (1.5B) has 6.