Model comparison
Llama 2-70B vs Qwen2.5-Max
Qwen2.5-Max is the stronger model overall, scoring 40.7 to 24.4 on the Noometry Index.
Last verified . 18 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. Llama 2-70B scores higher in 0 categories and Qwen2.5-Max in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen2.5-Max leads 36.9 to 8.1.
- Llama 2-70B has downloadable open weights; the other is API-only.
Side by side
| Llama 2-70B | Qwen2.5-Max | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 24.4 | 40.7 |
| Released | 2023-07-18 | 2025-01-25 |
| Weights | Open | Proprietary |
| Context window | — | — |
| Max output | — | — |
| Input $ / M tokens | — | — |
| Output $ / M tokens | — | — |
| Results tracked | 35 | 27 |
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Category by category
Coding Qwen2.5-Max leads
Llama 2-70B: 31.4 (#286), Qwen2.5-Max: 41.8 (#117)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Coding | 1079 | 1359 |
| LiveBench Coding | — | 64.4% |
Reasoning Qwen2.5-Max leads
Llama 2-70B: 14.4 (#325), Qwen2.5-Max: 25.6 (#147)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Hard Prompts | 1073 | 1360 |
| Epoch Capabilities Index | 113.79 | 132.53 |
| LiveBench Reasoning | — | 51.4% |
| DTBench | 41.6% | — |
| LiveBench Data Analysis | — | 67.9% |
| BIG-Bench Hard | 64.9% | — |
| CommonsenseQA 2.0 | 50% | — |
| ForecastBench | 51.4 | — |
| HellaSwag | 85.3% | — |
| LAMBADA | 78.9% | — |
| LiveBench | — | 62.3% |
| PIQA | 82.8% | — |
| WinoGrande | 80.2% | — |
Math Qwen2.5-Max leads
Llama 2-70B: 8.1 (#326), Qwen2.5-Max: 36.9 (#162)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Math | 1091 | 1369 |
| OTIS Mock AIME 2024-2025 | 0% | — |
| LiveBench Math | — | 58.4% |
| MATH Level 5 | 3.3% | — |
| GSM8K | 69.6% | — |
Knowledge Qwen2.5-Max leads
Llama 2-70B: 7.4 (#310), Qwen2.5-Max: 35.3 (#186)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Expert | 1039 | 1337 |
| GPQA Diamond | 26.3% | — |
| Confabulations | — | 21.8% |
| ARC (AI2) Challenge | 78.3% | — |
| BoolQ | 88.6% | — |
| MMLU | 69.9% | — |
| OpenBookQA | 60.2% | — |
| TriviaQA | 87.6% | — |
Multilingual Qwen2.5-Max leads
Llama 2-70B: 27.7 (#274), Qwen2.5-Max: 48.1 (#146)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Non-English | 1045 | 1352 |
| LMArena Chinese | 995 | 1382 |
| LMArena French | 1090 | 1396 |
| LMArena German | 1041 | 1350 |
| LMArena Japanese | 927 | 1300 |
| LMArena Korean | 964 | 1304 |
| LMArena Russian | 1083 | 1353 |
| LMArena Spanish | 1143 | 1377 |
Instruction Following Qwen2.5-Max leads
Llama 2-70B: 54.9 (#278), Qwen2.5-Max: 71.3 (#152)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Instruction Following | 1071 | 1335 |
| LiveBench Instruction Following | — | 75.3% |
Long Context Qwen2.5-Max leads
Llama 2-70B: 32.3 (#270), Qwen2.5-Max: 41.4 (#142)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Longer Query | 1062 | 1358 |
Writing & Preference Qwen2.5-Max leads
Llama 2-70B: 32.3 (#279), Qwen2.5-Max: 55.4 (#146)
| Benchmark | Llama 2-70B | Qwen2.5-Max |
|---|---|---|
| LMArena Text | 1115 | 1367 |
| LMArena Creative Writing | 1075 | 1339 |
| LMArena Multi-Turn | 1088 | 1364 |
| Short-Story Creative Writing | — | 72.9% |
| LiveBench Language | — | 56.3% |
Frequently asked questions
Is Llama 2-70B better than Qwen2.5-Max?
Qwen2.5-Max is the stronger model overall, scoring 40.7 to 24.4 on the Noometry Index.
Is Llama 2-70B or Qwen2.5-Max better for coding?
Qwen2.5-Max scores higher on coding benchmarks: 41.8 versus 31.4 in the Noometry coding category.
How many benchmarks do Llama 2-70B and Qwen2.5-Max share?
18 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Qwen2.5-Max has 27.