Compare / Qwen3.6 27B vs Gemma 3 27B
Qwen3.6 27B vs Gemma 3 27B
Updated November 2026
Verdict
Qwen3.6 27B scores higher on the Small LM Index: 74.0 vs 32.7. On the 3 benchmarks both labs report, Qwen3.6 27B wins 3 and Gemma 3 27B wins 0. Both need about 18.8 GB of memory at 4-bit quantization. Gemma 3 27B is cheaper through an API: $0.10 per million tokens against $0.90.
Pick Qwen3.6 27B if…
- you want the strongest model overall
- you mostly write code
- you work with long documents
- you need a permissive license (Apache-2.0)
- you want the more widely used model (more quantized builds and community support)
Pick Gemma 3 27B if…
- API cost matters most
Specifications
| Qwen3.6 27B | Gemma 3 27B | |
|---|---|---|
| Small LM Index | 74.0 (likely 73–75) | 32.7 (likely 26–41) |
| Lab | Alibaba (Qwen) · China | Google · United States |
| Released | 2026-04-22 | 2025-03-12 |
| Parameters | 27B (dense) | 27.4B (dense) |
| Memory at 4-bit | ~17.9 GB | ~18.8 GB |
| Context window | 262K tokens | 128K tokens |
| Input | text, image, video | text, image |
| Reasoning | Hybrid (thinking on/off) | No thinking |
| License | Apache-2.0 | Gemma |
| API price / 1M tokens | $0.90 ($0.20 in, $3.00 out) | $0.10 ($0.080 in, $0.16 out) |
| Hugging Face downloads (30 days) | 2.3M | 359.4K |
Benchmarks
Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.
| Benchmark | Qwen3.6 27B | Gemma 3 27B |
|---|---|---|
| MMLU-Pro Knowledge | 86.2 | 67.5 |
| GPQA Diamond Knowledge | 87.8 | 42.4 |
| Humanity's Last Exam Reasoning | 24.0 | ≈ 3 |
| AIME Math | 94.1 | ≈ 39 |
| LiveCodeBench Coding | 83.9 | 29.7 |
| SWE-bench Verified Coding | 77.2 | ≈ 14 |
| Terminal-Bench Agentic | 59.3 | — |
Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.
Questions
Which is better, Qwen3.6 27B or Gemma 3 27B?
Qwen3.6 27B scores higher on the Small LM Index: 74.0 vs 32.7. On the 3 benchmarks both labs report, Qwen3.6 27B wins 3 and Gemma 3 27B wins 0.
Which is cheaper to run?
Gemma 3 27B is cheaper through an API: $0.10 per million tokens against $0.90. Both need about 18.8 GB of memory at 4-bit quantization.
Which has the longer context window?
Qwen3.6 27B has the longer context window: 262K tokens against 128K.
Can I use Qwen3.6 27B and Gemma 3 27B commercially?
Qwen3.6 27B is released under Apache-2.0 and Gemma 3 27B under Gemma. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.