Model comparison
Llama 2-7B vs Qwen3.8 27B
Qwen3.8 27B is the stronger model overall, scoring 45.3 to 28.6 on the Noometry Index.
Last verified . 16 shared benchmarks.
Summary
- They share 16 benchmarks with published results for both. Llama 2-7B scores higher in 0 categories and Qwen3.8 27B in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3.8 27B leads 65.9 to 28.1.
Side by side
| Llama 2-7B | Qwen3.8 27B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 28.6 | 45.3 |
| Released | 2023-07-18 | 2026-08-14 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 33K |
| Input $ / M tokens | — | $0.99 |
| Output $ / M tokens | — | $1.49 |
| Results tracked | 29 | 28 |
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Category by category
Coding Qwen3.8 27B leads
Llama 2-7B: 28.7 (#302), Qwen3.8 27B: 50.3 (#42)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Coding | 1002 | 1487 |
| LMArena WebDev | — | 1592 |
| SciCode | — | 46.6% |
Reasoning Qwen3.8 27B leads
Llama 2-7B: 15.1 (#309), Qwen3.8 27B: 31.5 (#71)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Hard Prompts | 1009 | 1459 |
| Epoch Capabilities Index | 98.54 | 149.38 |
| NYT Connections (extended) | — | 54.5% |
| CritPt | — | 5.4% |
| Chess Puzzles | 0% | — |
| DTBench | — | 88% |
| LMCA | — | 41.4% |
| Surface Evolver Bench | — | 45% |
| BIG-Bench Hard | 39.2% | — |
| HellaSwag | 77.2% | — |
| LAMBADA | 73.3% | — |
| PIQA | 78.8% | — |
| WinoGrande | 69.2% | — |
Math Qwen3.8 27B leads
Llama 2-7B: 28.2 (#231), Qwen3.8 27B: 35.7 (#139)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Math | 1042 | 1453 |
| ProofBench | — | 16% |
| GSM8K | 16.7% | — |
Knowledge Qwen3.8 27B leads
Llama 2-7B: 27.7 (#243), Qwen3.8 27B: 40.9 (#105)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Expert | 1036 | 1482 |
| ARC (AI2) Challenge | 45.9% | — |
| BoolQ | 77.9% | — |
| MMLU | 45.8% | — |
| OpenBookQA | 58.6% | — |
| TriviaQA | 73.7% | — |
Multimodal Not comparable
Llama 2-7B: —, Qwen3.8 27B: 40.5 (#36)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Vision | — | 1270 |
| ScienceQA | 43.1% | — |
Multilingual Qwen3.8 27B leads
Llama 2-7B: 23.9 (#288), Qwen3.8 27B: 54.0 (#54)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Non-English | 973 | 1431 |
| LMArena Chinese | 973 | 1504 |
| LMArena French | 969 | 1468 |
| LMArena German | 978 | 1435 |
| LMArena Russian | 995 | 1421 |
| LMArena Spanish | 1007 | 1444 |
| LMArena Japanese | — | 1392 |
| LMArena Korean | — | 1389 |
Instruction Following Qwen3.8 27B leads
Llama 2-7B: 51.0 (#293), Qwen3.8 27B: 75.8 (#54)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Instruction Following | 1006 | 1436 |
Long Context Qwen3.8 27B leads
Llama 2-7B: 30.4 (#282), Qwen3.8 27B: 44.3 (#66)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Longer Query | 999 | 1448 |
Writing & Preference Qwen3.8 27B leads
Llama 2-7B: 28.1 (#293), Qwen3.8 27B: 65.9 (#41)
| Benchmark | Llama 2-7B | Qwen3.8 27B |
|---|---|---|
| LMArena Text | 1053 | 1441 |
| LMArena Creative Writing | 1033 | 1382 |
| LMArena Multi-Turn | 1029 | 1443 |
| EQ-Bench Creative Writing | — | 1671 |
Frequently asked questions
Is Llama 2-7B better than Qwen3.8 27B?
Qwen3.8 27B is the stronger model overall, scoring 45.3 to 28.6 on the Noometry Index.
Is Llama 2-7B or Qwen3.8 27B better for coding?
Qwen3.8 27B scores higher on coding benchmarks: 50.3 versus 28.7 in the Noometry coding category.
How many benchmarks do Llama 2-7B and Qwen3.8 27B share?
16 benchmarks have published results for both models. Llama 2-7B has 29 scored results on Noometry and Qwen3.8 27B has 28.