Model comparison
Llama 3.1-405B vs Qwen1.5-14B
Qwen1.5-14B is the stronger model overall, scoring 32.7 to 30.7 on the Noometry Index.
Last verified . 17 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Llama 3.1-405B scores higher in 6 categories and Qwen1.5-14B in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen1.5-14B leads 32.4 to 18.4.
Side by side
| Llama 3.1-405B | Qwen1.5-14B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.7 | 32.7 |
| Released | 2024-07-23 | 2024-02-04 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 42 | 17 |
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Category by category
Coding Too close to call
Llama 3.1-405B: 33.1 (#262), Qwen1.5-14B: 33.1 (#263)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1291 | 1138 |
| WeirdML | 21.4% | — |
Agentic & Tool Use Not comparable
Llama 3.1-405B: 21.0 (#140), Qwen1.5-14B: —
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| TheAgentCompany | 7.4% | — |
| Cybench | 7.5% | — |
Reasoning Qwen1.5-14B leads
Llama 3.1-405B: 16.8 (#300), Qwen1.5-14B: 21.4 (#223)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1269 | 1113 |
| SimpleBench | 23% | — |
| Kagi LLM Benchmark | 45% | — |
| DTBench | 61.4% | — |
| BIG-Bench Hard | 82.9% | — |
| Epoch Capabilities Index | 128.75 | — |
| ForecastBench | 59.9 | — |
| HellaSwag | 89.2% | — |
| PIQA | 85.9% | — |
| WinoGrande | 89.2% | — |
Math Qwen1.5-14B leads
Llama 3.1-405B: 18.4 (#290), Qwen1.5-14B: 32.4 (#215)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1281 | 1125 |
| OTIS Mock AIME 2024-2025 | 9.7% | — |
| Omni-MATH | 24.9% | — |
| MATH Level 5 | 49.8% | — |
Knowledge Too close to call
Llama 3.1-405B: 30.4 (#227), Qwen1.5-14B: 29.8 (#232)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1243 | 1094 |
| MMLU | 84.5% | 68.6% |
| GPQA Diamond | 50.9% | — |
| MMLU-Pro | 72.3% | — |
| Confabulations | 17.6% | — |
| GPQA (HELM) | 52.2% | — |
| ARC (AI2) Challenge | 95.3% | — |
| TriviaQA | 82.7% | — |
Multilingual Llama 3.1-405B leads
Llama 3.1-405B: 40.7 (#214), Qwen1.5-14B: 30.7 (#262)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1248 | 1095 |
| LMArena Chinese | 1242 | 1147 |
| LMArena French | 1279 | 1116 |
| LMArena German | 1252 | 1043 |
| LMArena Japanese | 1208 | 1019 |
| LMArena Russian | 1265 | 1046 |
| LMArena Spanish | 1260 | 1085 |
| LMArena Korean | 1184 | — |
Instruction Following Llama 3.1-405B leads
Llama 3.1-405B: 65.9 (#214), Qwen1.5-14B: 56.8 (#271)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1259 | 1102 |
| IFEval | 81.1% | — |
Long Context Llama 3.1-405B leads
Llama 3.1-405B: 38.4 (#197), Qwen1.5-14B: 33.7 (#257)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1266 | 1113 |
Writing & Preference Llama 3.1-405B leads
Llama 3.1-405B: 38.9 (#251), Qwen1.5-14B: 33.6 (#276)
| Benchmark | Llama 3.1-405B | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1284 | 1128 |
| LMArena Creative Writing | 1262 | 1091 |
| LMArena Multi-Turn | 1297 | 1110 |
| EQ-Bench Creative Writing | 870 | — |
| WildBench | 78.3% | — |
Frequently asked questions
Is Llama 3.1-405B better than Qwen1.5-14B?
Qwen1.5-14B is the stronger model overall, scoring 32.7 to 30.7 on the Noometry Index.
Is Llama 3.1-405B or Qwen1.5-14B better for coding?
They score almost the same on coding (33.1 vs 33.1); test both on your own repository before choosing.
How many benchmarks do Llama 3.1-405B and Qwen1.5-14B share?
17 benchmarks have published results for both models. Llama 3.1-405B has 42 scored results on Noometry and Qwen1.5-14B has 17.