Model comparison
Llama 2-70B vs Qwen1.5-14B
Qwen1.5-14B is the stronger model overall, scoring 32.7 to 24.4 on the Noometry Index.
Last verified . 17 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Llama 2-70B scores higher in 0 categories and Qwen1.5-14B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen1.5-14B leads 32.4 to 8.1.
Side by side
| Llama 2-70B | Qwen1.5-14B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 24.4 | 32.7 |
| Released | 2023-07-18 | 2024-02-04 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 35 | 17 |
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Category by category
Coding Qwen1.5-14B leads
Llama 2-70B: 31.4 (#286), Qwen1.5-14B: 33.1 (#263)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1079 | 1138 |
Reasoning Qwen1.5-14B leads
Llama 2-70B: 14.4 (#325), Qwen1.5-14B: 21.4 (#223)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1073 | 1113 |
| DTBench | 41.6% | — |
| BIG-Bench Hard | 64.9% | — |
| CommonsenseQA 2.0 | 50% | — |
| Epoch Capabilities Index | 113.79 | — |
| ForecastBench | 51.4 | — |
| HellaSwag | 85.3% | — |
| LAMBADA | 78.9% | — |
| PIQA | 82.8% | — |
| WinoGrande | 80.2% | — |
Math Qwen1.5-14B leads
Llama 2-70B: 8.1 (#326), Qwen1.5-14B: 32.4 (#215)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1091 | 1125 |
| OTIS Mock AIME 2024-2025 | 0% | — |
| MATH Level 5 | 3.3% | — |
| GSM8K | 69.6% | — |
Knowledge Qwen1.5-14B leads
Llama 2-70B: 7.4 (#310), Qwen1.5-14B: 29.8 (#232)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1039 | 1094 |
| MMLU | 69.9% | 68.6% |
| GPQA Diamond | 26.3% | — |
| ARC (AI2) Challenge | 78.3% | — |
| BoolQ | 88.6% | — |
| OpenBookQA | 60.2% | — |
| TriviaQA | 87.6% | — |
Multilingual Qwen1.5-14B leads
Llama 2-70B: 27.7 (#274), Qwen1.5-14B: 30.7 (#262)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1045 | 1095 |
| LMArena Chinese | 995 | 1147 |
| LMArena French | 1090 | 1116 |
| LMArena German | 1041 | 1043 |
| LMArena Japanese | 927 | 1019 |
| LMArena Russian | 1083 | 1046 |
| LMArena Spanish | 1143 | 1085 |
| LMArena Korean | 964 | — |
Instruction Following Qwen1.5-14B leads
Llama 2-70B: 54.9 (#278), Qwen1.5-14B: 56.8 (#271)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1071 | 1102 |
Long Context Qwen1.5-14B leads
Llama 2-70B: 32.3 (#270), Qwen1.5-14B: 33.7 (#257)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1062 | 1113 |
Writing & Preference Qwen1.5-14B leads
Llama 2-70B: 32.3 (#279), Qwen1.5-14B: 33.6 (#276)
| Benchmark | Llama 2-70B | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1115 | 1128 |
| LMArena Creative Writing | 1075 | 1091 |
| LMArena Multi-Turn | 1088 | 1110 |
Frequently asked questions
Is Llama 2-70B better than Qwen1.5-14B?
Qwen1.5-14B is the stronger model overall, scoring 32.7 to 24.4 on the Noometry Index.
Is Llama 2-70B or Qwen1.5-14B better for coding?
Qwen1.5-14B scores higher on coding benchmarks: 33.1 versus 31.4 in the Noometry coding category.
How many benchmarks do Llama 2-70B and Qwen1.5-14B share?
17 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Qwen1.5-14B has 17.