Model comparison
Llama 2-7B vs Qwen1.5-7B
Qwen1.5-7B is the stronger model overall, scoring 31.4 to 29.1 on the Noometry Index.
Last verified . 13 shared benchmarks.
Summary
- They share 13 benchmarks with published results for both. Llama 2-7B scores higher in 0 categories and Qwen1.5-7B in 8 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Qwen1.5-7B leads 28.5 to 23.8.
Side by side
| Llama 2-7B | Qwen1.5-7B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.1 | 31.4 |
| Released | 2023-07-18 | 2024-02-04 |
| Weights | Open | Open |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 29 | 13 |
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Category by category
Coding Qwen1.5-7B leads
Llama 2-7B: 29.2 (#307), Qwen1.5-7B: 32.2 (#276)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Coding | 1002 | 1107 |
Reasoning Qwen1.5-7B leads
Llama 2-7B: 15.7 (#312), Qwen1.5-7B: 20.4 (#240)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Hard Prompts | 1009 | 1065 |
| Chess Puzzles | 0% | — |
| BIG-Bench Hard | 39.2% | — |
| Epoch Capabilities Index | 99.06 | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Too close to call
Llama 2-7B: 30.7 (#233), Qwen1.5-7B: 31.4 (#224)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Math | 1042 | 1080 |
| GSM8K | 16.7% | — |
Knowledge Too close to call
Llama 2-7B: 28.2 (#248), Qwen1.5-7B: 28.7 (#243)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Expert | 1036 | 1055 |
| MMLU | 45.8% | 62.6% |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, Qwen1.5-7B: —
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| ScienceQA | 43.1% | — |
Multilingual Qwen1.5-7B leads
Llama 2-7B: 23.8 (#293), Qwen1.5-7B: 28.5 (#271)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Non-English | 973 | 1058 |
| LMArena Chinese | 973 | 1141 |
| LMArena Russian | 995 | 1006 |
| LMArena French | 970 | — |
| LMArena German | 978 | — |
| LMArena Spanish | 1007 | — |
Instruction Following Qwen1.5-7B leads
Llama 2-7B: 50.8 (#298), Qwen1.5-7B: 54.1 (#281)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Instruction Following | 1006 | 1058 |
Long Context Qwen1.5-7B leads
Llama 2-7B: 30.4 (#287), Qwen1.5-7B: 33.1 (#266)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Longer Query | 999 | 1090 |
Writing & Preference Qwen1.5-7B leads
Llama 2-7B: 28.0 (#298), Qwen1.5-7B: 29.6 (#293)
| Benchmark | Llama 2-7B | Qwen1.5-7B |
|---|---|---|
| LMArena Text | 1053 | 1083 |
| LMArena Creative Writing | 1033 | 1035 |
| LMArena Multi-Turn | 1029 | 1062 |
Frequently asked questions
Is Llama 2-7B better than Qwen1.5-7B?
Qwen1.5-7B is the stronger model overall, scoring 31.4 to 29.1 on the Noometry Index.
Is Llama 2-7B or Qwen1.5-7B better for coding?
Qwen1.5-7B scores higher on coding benchmarks: 32.2 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Qwen1.5-7B share?
13 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Qwen1.5-7B has 13.