Model comparison
Llama 2-7B vs Qwen3.5 27B
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 29.1 on the Noometry Index.
Last verified . 15 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 15 benchmarks with published results for both. Llama 2-7B scores higher in 0 categories and Qwen3.5 27B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.5 27B leads 59.3 to 28.0.
Side by side
| Llama 2-7B | Qwen3.5 27B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.1 | 41.9 |
| Released | 2023-07-18 | 2026-02-23 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.30 |
| Output $ / M tokens | — | $2.40 |
| Results tracked | 29 | 28 |
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Category by category
Coding Qwen3.5 27B leads
Llama 2-7B: 29.2 (#307), Qwen3.5 27B: 38.9 (#168)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Coding | 1002 | 1427 |
| LMArena WebDev | — | 1358 |
| WeirdML | — | 39.5% |
| ALE-Bench | — | 349.45 |
Agentic & Tool Use Not comparable
Llama 2-7B: —, Qwen3.5 27B: —
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| Vending-Bench 2 | — | 201.98 |
Reasoning Qwen3.5 27B leads
Llama 2-7B: 15.7 (#312), Qwen3.5 27B: 27.5 (#117)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1009 | 1414 |
| NYT Connections (extended) | — | 47.9% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 45.5% |
| DTBench | — | 82.4% |
| LMCA | — | 34% |
| BIG-Bench Hard | 39.2% | — |
| Epoch Capabilities Index | 99.06 | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Qwen3.5 27B leads
Llama 2-7B: 30.7 (#233), Qwen3.5 27B: 38.8 (#127)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1042 | 1429 |
| MathArena Final-Answer Competitions | — | 56.7% |
| GSM8K | 16.7% | — |
Knowledge Qwen3.5 27B leads
Llama 2-7B: 28.2 (#248), Qwen3.5 27B: 38.0 (#150)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Expert | 1036 | 1428 |
| Vectara Hallucination Rate | — | 12.1% |
| 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 27B: 39.4 (#59)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | — | 1241 |
| ScienceQA | 43.1% | — |
Multilingual Qwen3.5 27B leads
Llama 2-7B: 23.8 (#293), Qwen3.5 27B: 50.8 (#115)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 973 | 1390 |
| LMArena Chinese | 973 | 1478 |
| LMArena French | 970 | 1410 |
| LMArena German | 978 | 1393 |
| LMArena Russian | 995 | 1390 |
| LMArena Spanish | 1007 | 1407 |
| LMArena Japanese | — | 1345 |
| LMArena Korean | — | 1358 |
Instruction Following Qwen3.5 27B leads
Llama 2-7B: 50.8 (#298), Qwen3.5 27B: 73.5 (#119)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1006 | 1393 |
Long Context Qwen3.5 27B leads
Llama 2-7B: 30.4 (#287), Qwen3.5 27B: 43.1 (#106)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 999 | 1413 |
Writing & Preference Qwen3.5 27B leads
Llama 2-7B: 28.0 (#298), Qwen3.5 27B: 59.3 (#111)
| Benchmark | Llama 2-7B | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1053 | 1409 |
| LMArena Creative Writing | 1033 | 1362 |
| LMArena Multi-Turn | 1029 | 1410 |
Frequently asked questions
Is Llama 2-7B better than Qwen3.5 27B?
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 29.1 on the Noometry Index.
Is Llama 2-7B or Qwen3.5 27B better for coding?
Qwen3.5 27B scores higher on coding benchmarks: 38.9 versus 29.2 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Qwen3.5 27B share?
15 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Qwen3.5 27B has 28.