Model comparison
Llama 3.1-8B vs Qwen2.5-Coder (1.5B)
Llama 3.1-8B has enough public results to be ranked (#347); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.
Last verified . 3 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 3 benchmarks with published results for both.
Side by side
| Llama 3.1-8B | Qwen2.5-Coder (1.5B) | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 22.8 | — |
| Released | 2024-07-23 | 2024-09-18 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.05 | — |
| Output $ / M tokens | $0.08 | — |
| Results tracked | 43 | 6 |
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Category by category
Coding Not comparable
Llama 3.1-8B: 19.9 (#335), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| SciCode | 13.2% | — |
| WeirdML | 1.7% | — |
| BigCodeBench Instruct | 32.8% | — |
| LMArena Coding | 1195 | — |
| BigCodeBench Complete | 40.5% | — |
| HumanEval+ | 62.8% | — |
| MBPP+ | 55.6% | — |
Agentic & Tool Use Not comparable
Llama 3.1-8B: 22.3 (#123), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| BALROG | 15.1% | — |
Reasoning Not comparable
Llama 3.1-8B: 14.5 (#316), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| Epoch Capabilities Index | 116.48 | 112.93 |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1175 | — |
| DTBench | 50.9% | — |
| LMCA | 5.4% | — |
| HellaSwag | — | 76.8% |
| PIQA | 81.2% | — |
| WinoGrande | — | 72.9% |
Math Not comparable
Llama 3.1-8B: 9.5 (#311), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| GSM8K | 82.4% | 86.7% |
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| Omni-MATH | 13.7% | — |
| LMArena Math | 1179 | — |
| MATH Level 5 | 22.9% | — |
Knowledge Not comparable
Llama 3.1-8B: 8.0 (#302), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| MMLU | 56.1% | 68% |
| GPQA Diamond | 27% | — |
| MMLU-Pro | 40.6% | — |
| GPQA (HELM) | 24.7% | — |
| LMArena Expert | 1144 | — |
| ARC (AI2) Challenge | — | 60.9% |
| BoolQ | 82.8% | — |
Multilingual Not comparable
Llama 3.1-8B: 34.2 (#244), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Non-English | 1148 | — |
| LMArena Chinese | 1151 | — |
| LMArena French | 1176 | — |
| LMArena German | 1144 | — |
| LMArena Japanese | 1061 | — |
| LMArena Korean | 1053 | — |
| LMArena Russian | 1158 | — |
| LMArena Spanish | 1169 | — |
Instruction Following Not comparable
Llama 3.1-8B: 59.1 (#253), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| IFEval | 74.3% | — |
| LMArena Instruction Following | 1159 | — |
Long Context Not comparable
Llama 3.1-8B: 35.8 (#233), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Longer Query | 1182 | — |
Writing & Preference Not comparable
Llama 3.1-8B: 29.9 (#285), Qwen2.5-Coder (1.5B): —
| Benchmark | Llama 3.1-8B | Qwen2.5-Coder (1.5B) |
|---|---|---|
| LMArena Text | 1187 | — |
| LMArena Creative Writing | 1154 | — |
| EQ-Bench Creative Writing | 713 | — |
| WildBench | 68.7% | — |
| LMArena Multi-Turn | 1172 | — |
Frequently asked questions
Is Llama 3.1-8B better than Qwen2.5-Coder (1.5B)?
Llama 3.1-8B has enough public results to be ranked (#347); Qwen2.5-Coder (1.5B) does not yet, so treat this comparison as directional.
How many benchmarks do Llama 3.1-8B and Qwen2.5-Coder (1.5B) share?
3 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Qwen2.5-Coder (1.5B) has 6.