Model comparison
Llama 13b vs Qwen2.5-VL 72B Instruct
Qwen2.5-VL 72B Instruct is the stronger model overall, scoring 29.4 to 23.9 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 20.0 to 13.4.
Side by side
| Llama 13b | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 23.9 | 29.4 |
| Released | 2023-02-24 | 2024-09 |
| Weights | Open | Open |
| Context window | — | 131K |
| Max output | — | 8K |
| Input $ / M tokens | — | $2.80 |
| Output $ / M tokens | — | $8.40 |
| Results tracked | 21 | 6 |
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Category by category
Coding Not comparable
Llama 13b: 20.9 (#332), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Coding | 683 | — |
Agentic & Tool Use Not comparable
Llama 13b: —, Qwen2.5-VL 72B Instruct: 18.4 (#136)
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OSWorld | — | 5% |
Reasoning Qwen2.5-VL 72B Instruct leads
Llama 13b: 13.4 (#327), Qwen2.5-VL 72B Instruct: 20.0 (#228)
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 36% |
| LMArena Hard Prompts | 728 | — |
| BIG-Bench Hard | 37.9% | — |
| Epoch Capabilities Index | 100.09 | — |
| HellaSwag | 79.2% | — |
| LAMBADA | 75.2% | — |
| PIQA | 80.1% | — |
| WinoGrande | 73% | — |
Math Not comparable
Llama 13b: 24.4 (#259), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Math | 838 | — |
| GSM8K | 20.6% | — |
Knowledge Not comparable
Llama 13b: —, Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| ARC (AI2) Challenge | 52.7% | — |
| BoolQ | 78.7% | — |
| MMLU | 47.7% | — |
| OpenBookQA | 56.4% | — |
| TriviaQA | 77.9% | — |
Multimodal Not comparable
Llama 13b: —, Qwen2.5-VL 72B Instruct: 32.9 (#92)
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | — | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| ScienceQA | 43.3% | — |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
Llama 13b: 16.8 (#292), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 819 | — |
Instruction Following Not comparable
Llama 13b: 36.9 (#300), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 781 | — |
Writing & Preference Not comparable
Llama 13b: 13.9 (#307), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 13b | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 834 | — |
| LMArena Creative Writing | 794 | — |
| LMArena Multi-Turn | 753 | — |
Frequently asked questions
Is Llama 13b better than Qwen2.5-VL 72B Instruct?
Qwen2.5-VL 72B Instruct is the stronger model overall, scoring 29.4 to 23.9 on the Noometry Index.
How many benchmarks do Llama 13b and Qwen2.5-VL 72B Instruct share?
0 benchmarks have published results for both models. Llama 13b has 21 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.