Qwen 3.6 27B vs Gemma 3 27B Instruct
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Gemma 3 27B Instruct is more hardware-efficient — it needs 16.8 GB at Q4_K_M vs 16.9 GB for Qwen 3.6 27B, fitting on 61 GPUs natively.
VRAM at each quantization (8k context)
| Quant | Qwen 3.6 27B | Gemma 3 27B Instruct | Diff |
|---|---|---|---|
| FP16 | 62.3 GB | 62.2 GB | +0% |
| Q8 | 32.0 GB | 32.0 GB | +0% |
| Q6_K | 24.5 GB | 24.4 GB | +0% |
| Q5_K_M | 20.7 GB | 20.6 GB | +0% |
| Q4_K_M | 16.9 GB | 16.8 GB | +0% |
| Q3_K_M | 13.9 GB | 13.8 GB | +1% |
| Q2_K | 10.9 GB | 10.8 GB | +1% |
Diff is Qwen 3.6 27B relative to Gemma 3 27B Instruct. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Qwen 3.6 27B | Gemma 3 27B Instruct |
|---|---|---|
| Org | Alibaba | |
| Parameters | 27B | 27B |
| Architecture | Dense | Dense |
| Context | 256k tokens | 128k tokens |
| Modalities | text, vision | text, vision |
| License | Apache 2.0 | Gemma |
| Commercial | Yes | Yes |
| Released | 2026-04-01 | 2025-03-12 |
| GPUs (native) | 61 / 67 | 61 / 67 |
GPUs that run only Qwen 3.6 27B(0)
Every GPU that runs Qwen 3.6 27B also runs Gemma 3 27B Instruct.
GPUs that run only Gemma 3 27B Instruct(0)
Every GPU that runs Gemma 3 27B Instruct also runs Qwen 3.6 27B.
GPUs that run both natively(61)
- NVIDIA RTX 509032 GB
- NVIDIA RTX 409024 GB
- NVIDIA RTX 408016 GB
- NVIDIA RTX 4070 Ti12 GB
- NVIDIA RTX 407012 GB
- NVIDIA RTX 4060 Ti 16GB16 GB
- NVIDIA RTX 309024 GB
- NVIDIA RTX 3090 Ti24 GB
- NVIDIA RTX 3060 12GB12 GB
- NVIDIA H100 80GB80 GB
- NVIDIA A100 80GB80 GB
- NVIDIA A100 40GB40 GB
- +49 more GPUs run both
Which should you use?
Choose Qwen 3.6 27B if:
- • Long context matters — it supports 256k tokens vs 128k
- • You need chain-of-thought reasoning
Choose Gemma 3 27B Instruct if:
Frequently asked questions
- Which is better, Qwen 3.6 27B or Gemma 3 27B Instruct?
- Gemma 3 27B Instruct is more hardware-efficient, needing 16.8 GB at Q4_K_M vs 16.9 GB.
- How much VRAM does Qwen 3.6 27B need vs Gemma 3 27B Instruct?
- At Q4_K_M quantization with 8k context, Qwen 3.6 27B needs approximately 16.9 GB of VRAM, while Gemma 3 27B Instruct needs 16.8 GB. At FP16, Qwen 3.6 27B requires 62.3 GB vs 62.2 GB for Gemma 3 27B Instruct.
- Can you run Qwen 3.6 27B on the same GPUs as Gemma 3 27B Instruct?
- Yes, 61 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 4090, NVIDIA RTX 4080. However, no GPU can run Qwen 3.6 27B without also fitting Gemma 3 27B Instruct, and no GPU can run Gemma 3 27B Instruct without also fitting Qwen 3.6 27B.
- What is the difference between Qwen 3.6 27B and Gemma 3 27B Instruct?
- Qwen 3.6 27B has 27B parameters (dense) with a 256k context window. Gemma 3 27B Instruct has 27B parameters (dense) with a 128k context window. Licensing differs: Qwen 3.6 27B is Apache 2.0 while Gemma 3 27B Instruct is Gemma.
- Which model fits in 24 GB of VRAM, Qwen 3.6 27B or Gemma 3 27B Instruct?
- Both fit in 24 GB of VRAM at Q4_K_M — Qwen 3.6 27B needs 16.9 GB and Gemma 3 27B Instruct needs 16.8 GB.