Model comparison
Llama 2-70B vs Qwen2.5-VL 72B Instruct
Qwen2.5-VL 72B Instruct is the stronger model overall, scoring 29.9 to 24.4 on the Noometry Index.
Last verified . 0 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where Qwen2.5-VL 72B Instruct leads 20.7 to 14.4.
Side by side
| Llama 2-70B | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 24.4 | 29.9 |
| Released | 2023-07-18 | 2024-09 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $2.80 |
| Output $ / M tokens | — | $8.40 |
| Results tracked | 35 | 6 |
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Category by category
Coding Not comparable
Llama 2-70B: 31.4 (#286), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Coding | 1079 | — |
Agentic & Tool Use Not comparable
Llama 2-70B: —, Qwen2.5-VL 72B Instruct: 18.6 (#144)
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OSWorld | — | 5% |
Reasoning Qwen2.5-VL 72B Instruct leads
Llama 2-70B: 14.4 (#325), Qwen2.5-VL 72B Instruct: 20.7 (#233)
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 36% |
| LMArena Hard Prompts | 1073 | — |
| 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 Not comparable
Llama 2-70B: 8.1 (#326), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0% | — |
| LMArena Math | 1091 | — |
| MATH Level 5 | 3.3% | — |
| GSM8K | 69.6% | — |
Knowledge Not comparable
Llama 2-70B: 7.4 (#310), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 26.3% | — |
| LMArena Expert | 1039 | — |
| ARC (AI2) Challenge | 78.3% | — |
| BoolQ | 88.6% | — |
| MMLU | 69.9% | — |
| OpenBookQA | 60.2% | — |
| TriviaQA | 87.6% | — |
Multimodal Not comparable
Llama 2-70B: —, Qwen2.5-VL 72B Instruct: 33.5 (#97)
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | — | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
Llama 2-70B: 27.7 (#274), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1045 | — |
| LMArena Chinese | 995 | — |
| LMArena French | 1090 | — |
| LMArena German | 1041 | — |
| LMArena Japanese | 927 | — |
| LMArena Korean | 964 | — |
| LMArena Russian | 1083 | — |
| LMArena Spanish | 1143 | — |
Instruction Following Not comparable
Llama 2-70B: 54.9 (#278), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1071 | — |
Long Context Not comparable
Llama 2-70B: 32.3 (#270), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1062 | — |
Writing & Preference Not comparable
Llama 2-70B: 32.3 (#279), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 2-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1115 | — |
| LMArena Creative Writing | 1075 | — |
| LMArena Multi-Turn | 1088 | — |
Frequently asked questions
Is Llama 2-70B better than Qwen2.5-VL 72B Instruct?
Qwen2.5-VL 72B Instruct is the stronger model overall, scoring 29.9 to 24.4 on the Noometry Index.
How many benchmarks do Llama 2-70B and Qwen2.5-VL 72B Instruct share?
0 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.