Model comparison
Llama 3-8B vs Qwen3.6 27B
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 25.5 on the Noometry Index.
Last verified . 5 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 5 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and Qwen3.6 27B in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.6 27B leads 52.4 to 7.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.9% for Llama 3-8B and 91.1% for Qwen3.6 27B.
Side by side
| Llama 3-8B | Qwen3.6 27B | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 25.5 | 42.2 |
| Released | 2024-04-18 | 2026-04-22 |
| Weights | Open | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $3.60 |
| Results tracked | 34 | 11 |
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Category by category
Coding Qwen3.6 27B leads
Llama 3-8B: 31.0 (#289), Qwen3.6 27B: 39.1 (#163)
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| SciCode | — | 37.3% |
| BigCodeBench Instruct | 31.9% | — |
| LMArena Coding | 1152 | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Reasoning Qwen3.6 27B leads
Llama 3-8B: 14.3 (#326), Qwen3.6 27B: 25.0 (#153)
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| Chess Puzzles | 0% | 22% |
| DTBench | 43.9% | 78.1% |
| Epoch Capabilities Index | 116.45 | 146.5 |
| CritPt | — | 0.9% |
| LMArena Hard Prompts | 1133 | — |
| Mystery Game Puzzles | — | 7% |
| LMCA | — | 34.5% |
| Adversarial NLI | 57.3% | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |
Math Qwen3.6 27B leads
Llama 3-8B: 8.8 (#323), Qwen3.6 27B: 48.5 (#62)
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | 91.1% |
| FrontierMath (Tiers 1-3) | — | 35.1% |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |
Knowledge Qwen3.6 27B leads
Llama 3-8B: 7.8 (#308), Qwen3.6 27B: 52.4 (#63)
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| GPQA Diamond | 26.1% | 85.9% |
| LMArena Expert | 1113 | — |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |
Multilingual Not comparable
Llama 3-8B: 30.8 (#261), Qwen3.6 27B: —
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| LMArena Non-English | 1098 | — |
| LMArena Chinese | 1076 | — |
| LMArena French | 1159 | — |
| LMArena German | 1104 | — |
| LMArena Japanese | 967 | — |
| LMArena Korean | 1004 | — |
| LMArena Russian | 1109 | — |
| LMArena Spanish | 1173 | — |
Instruction Following Not comparable
Llama 3-8B: 58.4 (#260), Qwen3.6 27B: —
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| LMArena Instruction Following | 1127 | — |
Long Context Not comparable
Llama 3-8B: 34.2 (#251), Qwen3.6 27B: —
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| LMArena Longer Query | 1128 | — |
Writing & Preference Qwen3.6 27B leads
Llama 3-8B: 37.5 (#256), Qwen3.6 27B: 50.3 (#181)
| Benchmark | Llama 3-8B | Qwen3.6 27B |
|---|---|---|
| LMArena Text | 1166 | — |
| LMArena Creative Writing | 1150 | — |
| EQ-Bench 4 | — | 1026 |
| LMArena Multi-Turn | 1152 | — |
Frequently asked questions
Is Llama 3-8B better than Qwen3.6 27B?
Qwen3.6 27B is the stronger model overall, scoring 42.2 to 25.5 on the Noometry Index.
Is Llama 3-8B or Qwen3.6 27B better for coding?
Qwen3.6 27B scores higher on coding benchmarks: 39.1 versus 31.0 in the Noometry coding category.
How many benchmarks do Llama 3-8B and Qwen3.6 27B share?
5 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Qwen3.6 27B has 11.