Model comparison
Llama 2-7B vs Qwen3.5 397B-A17B
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 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 397B-A17B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5 397B-A17B leads 62.3 to 28.0.
- The biggest single-benchmark swing is Chess Puzzles: 0% for Llama 2-7B and 13% for Qwen3.5 397B-A17B.
Side by side
| Llama 2-7B | Qwen3.5 397B-A17B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.1 | 46.0 |
| Released | 2023-07-18 | 2026-02-01 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $3.60 |
| Results tracked | 29 | 36 |
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Category by category
Coding Qwen3.5 397B-A17B leads
Llama 2-7B: 29.2 (#307), Qwen3.5 397B-A17B: 42.0 (#114)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Coding | 1002 | 1465 |
| LMArena WebDev | — | 1400 |
Agentic & Tool Use Not comparable
Llama 2-7B: —, Qwen3.5 397B-A17B: 33.3 (#53)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| APEX-Agents | — | 24.9% |
| τ²-bench Airline | — | 81.5% |
| τ²-bench Banking | — | 9.8% |
| τ²-bench Retail | — | 84.4% |
| τ²-bench Telecom | — | 97.8% |
Reasoning Qwen3.5 397B-A17B leads
Llama 2-7B: 15.7 (#312), Qwen3.5 397B-A17B: 34.5 (#70)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| Chess Puzzles | 0% | 13% |
| LMArena Hard Prompts | 1009 | 1448 |
| Epoch Capabilities Index | 99.06 | 146.65 |
| Kagi LLM Benchmark | — | 73.7% |
| NYT Connections (extended) | — | 58.9% |
| Thematic Generalization | — | 65.1% |
| Mystery Game Puzzles | — | 18% |
| DTBench | — | 87.5% |
| LMCA | — | 37.9% |
| BIG-Bench Hard | 39.2% | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Qwen3.5 397B-A17B leads
Llama 2-7B: 30.7 (#233), Qwen3.5 397B-A17B: 46.1 (#73)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Math | 1042 | 1454 |
| FrontierMath (Tiers 1-3) | — | 31.2% |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| GSM8K | 16.7% | — |
Knowledge Qwen3.5 397B-A17B leads
Llama 2-7B: 28.2 (#248), Qwen3.5 397B-A17B: 53.3 (#58)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Expert | 1036 | 1462 |
| GPQA Diamond | — | 86.4% |
| 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 397B-A17B: 40.7 (#44)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Vision | — | 1263 |
| ScienceQA | 43.1% | — |
Multilingual Qwen3.5 397B-A17B leads
Llama 2-7B: 23.8 (#293), Qwen3.5 397B-A17B: 53.7 (#59)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Non-English | 973 | 1430 |
| LMArena Chinese | 973 | 1500 |
| LMArena French | 970 | 1461 |
| LMArena German | 978 | 1447 |
| LMArena Russian | 995 | 1429 |
| LMArena Spanish | 1007 | 1441 |
| LMArena Japanese | — | 1426 |
| LMArena Korean | — | 1384 |
Instruction Following Qwen3.5 397B-A17B leads
Llama 2-7B: 50.8 (#298), Qwen3.5 397B-A17B: 75.0 (#77)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Instruction Following | 1006 | 1424 |
Long Context Qwen3.5 397B-A17B leads
Llama 2-7B: 30.4 (#287), Qwen3.5 397B-A17B: 44.1 (#74)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Longer Query | 999 | 1442 |
Writing & Preference Qwen3.5 397B-A17B leads
Llama 2-7B: 28.0 (#298), Qwen3.5 397B-A17B: 62.3 (#79)
| Benchmark | Llama 2-7B | Qwen3.5 397B-A17B |
|---|---|---|
| LMArena Text | 1053 | 1438 |
| LMArena Creative Writing | 1033 | 1401 |
| LMArena Multi-Turn | 1029 | 1446 |
| EQ-Bench Creative Writing | — | 1478 |
Frequently asked questions
Is Llama 2-7B better than Qwen3.5 397B-A17B?
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 29.1 on the Noometry Index.
Is Llama 2-7B or Qwen3.5 397B-A17B better for coding?
Qwen3.5 397B-A17B scores higher on coding benchmarks: 42.0 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Qwen3.5 397B-A17B share?
17 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Qwen3.5 397B-A17B has 36.