Model comparison
Llama 2-7B vs Qwen3.5 35B-A3B
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 29.1 on the Noometry Index.
Last verified . 17 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Llama 2-7B scores higher in 0 categories and Qwen3.5 35B-A3B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5 35B-A3B leads 57.9 to 28.0.
- The biggest single-benchmark swing is Chess Puzzles: 0% for Llama 2-7B and 10% for Qwen3.5 35B-A3B.
Side by side
| Llama 2-7B | Qwen3.5 35B-A3B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.1 | 42.0 |
| Released | 2023-07-18 | 2026-02-01 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.25 |
| Output $ / M tokens | — | $2 |
| Results tracked | 29 | 28 |
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Category by category
Coding Qwen3.5 35B-A3B leads
Llama 2-7B: 29.2 (#307), Qwen3.5 35B-A3B: 33.8 (#251)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Coding | 1002 | 1410 |
| LMArena WebDev | — | 1254 |
| SciCode | — | 29.3% |
Reasoning Qwen3.5 35B-A3B leads
Llama 2-7B: 15.7 (#312), Qwen3.5 35B-A3B: 24.6 (#161)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| Chess Puzzles | 0% | 10% |
| LMArena Hard Prompts | 1009 | 1400 |
| Epoch Capabilities Index | 99.06 | 142.52 |
| CritPt | — | 0.6% |
| DTBench | — | 80% |
| LMCA | — | 29.5% |
| BIG-Bench Hard | 39.2% | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Qwen3.5 35B-A3B leads
Llama 2-7B: 30.7 (#233), Qwen3.5 35B-A3B: 39.9 (#97)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Math | 1042 | 1404 |
| MathArena Final-Answer Competitions | — | 56% |
| OTIS Mock AIME 2024-2025 | — | 70% |
| GSM8K | 16.7% | — |
Knowledge Qwen3.5 35B-A3B leads
Llama 2-7B: 28.2 (#248), Qwen3.5 35B-A3B: 47.8 (#79)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Expert | 1036 | 1408 |
| GPQA Diamond | — | 83.5% |
| Vectara Hallucination Rate | — | 10.5% |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| MMLU | 45.8% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, Qwen3.5 35B-A3B: —
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| ScienceQA | 43.1% | — |
Multilingual Qwen3.5 35B-A3B leads
Llama 2-7B: 23.8 (#293), Qwen3.5 35B-A3B: 50.0 (#127)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Non-English | 973 | 1378 |
| LMArena Chinese | 973 | 1457 |
| LMArena French | 970 | 1412 |
| LMArena German | 978 | 1367 |
| LMArena Russian | 995 | 1376 |
| LMArena Spanish | 1007 | 1392 |
| LMArena Japanese | — | 1325 |
| LMArena Korean | — | 1356 |
Instruction Following Qwen3.5 35B-A3B leads
Llama 2-7B: 50.8 (#298), Qwen3.5 35B-A3B: 72.8 (#128)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Instruction Following | 1006 | 1379 |
Long Context Qwen3.5 35B-A3B leads
Llama 2-7B: 30.4 (#287), Qwen3.5 35B-A3B: 42.4 (#127)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Longer Query | 999 | 1389 |
Writing & Preference Qwen3.5 35B-A3B leads
Llama 2-7B: 28.0 (#298), Qwen3.5 35B-A3B: 57.9 (#124)
| Benchmark | Llama 2-7B | Qwen3.5 35B-A3B |
|---|---|---|
| LMArena Text | 1053 | 1395 |
| LMArena Creative Writing | 1033 | 1346 |
| LMArena Multi-Turn | 1029 | 1390 |
Frequently asked questions
Is Llama 2-7B better than Qwen3.5 35B-A3B?
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 29.1 on the Noometry Index.
Is Llama 2-7B or Qwen3.5 35B-A3B better for coding?
Qwen3.5 35B-A3B scores higher on coding benchmarks: 33.8 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Qwen3.5 35B-A3B share?
17 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Qwen3.5 35B-A3B has 28.