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Qwen 3.6 27B vs Gemma 4 31B

Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.

Quick verdict

Qwen 3.6 27B is more hardware-efficient — it needs 18.8 GB at Q4_K_M vs 23.2 GB for Gemma 4 31B, fitting on 85 GPUs natively.

VRAM at each quantization (8k context)

QuantQwen 3.6 27BGemma 4 31BDiff
FP32122.8 GB142.5 GB-14%
BF1662.3 GB73.0 GB-15%
FP1662.3 GB73.0 GB-15%
Q8_032.0 GB38.3 GB-16%
Q6_K26.6 GB32.1 GB-17%
Q5_K_M21.3 GB26.0 GB-18%
Q4_K_M18.8 GB23.2 GB-19%
Q3_K_M14.8 GB18.5 GB-20%
Q2_K11.8 GB15.0 GB-22%
NVFP416.9 GB21.0 GB-19%

Diff is Qwen 3.6 27B relative to Gemma 4 31B. Green = lower VRAM (fits more GPUs).

Model specifications

SpecQwen 3.6 27BGemma 4 31B
OrgAlibabaGoogle
Parameters27B31B
ArchitectureDenseDense
Context256k tokens250k tokens
Modalitiestext, visiontext, vision
LicenseApache 2.0Apache 2.0
CommercialYesYes
Released2026-04-012026-04-02
GPUs (native)85 / 10775 / 107

Benchmark scores

BenchmarkQwen 3.6 27BGemma 4 31B
MMLU-Pro86.285.2

Green = higher score (better). — = not yet available.

GPUs that run only Qwen 3.6 27B(10)

GPUs that run only Gemma 4 31B(0)

Every GPU that runs Gemma 4 31B also runs Qwen 3.6 27B.

GPUs that run both natively(75)

Which should you use?

Choose Qwen 3.6 27B if:
  • • You have limited VRAM — it's a smaller model needing 18.8 GB vs 23.2 GB
  • • Long context matters — it supports 256k tokens vs 250k
  • • Benchmark quality matters — scores 86.2 vs 85.2 on MMLU-Pro
  • • You need chain-of-thought reasoning
Choose Gemma 4 31B if:
  • • You want maximum capability and have a 24 GB+ GPU

Frequently asked questions

Which is better, Qwen 3.6 27B or Gemma 4 31B?
Qwen 3.6 27B has 27B parameters vs 31B for Gemma 4 31B, so Gemma 4 31B is the larger model. Qwen 3.6 27B is more hardware-efficient, needing 18.8 GB at Q4_K_M vs 23.2 GB. Qwen 3.6 27B runs on more GPUs natively (85 vs 75). On MMLU-Pro, Qwen 3.6 27B scores higher (86.2 vs 85.2).
How much VRAM does Qwen 3.6 27B need vs Gemma 4 31B?
At Q4_K_M quantization with 8k context, Qwen 3.6 27B needs approximately 18.8 GB of VRAM, while Gemma 4 31B needs 23.2 GB. At FP16, Qwen 3.6 27B requires 62.3 GB vs 73.0 GB for Gemma 4 31B.
Can you run Qwen 3.6 27B on the same GPUs as Gemma 4 31B?
Yes, 75 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 5080, NVIDIA RTX 5070 Ti. However, 10 GPUs can run Qwen 3.6 27B but not Gemma 4 31B, and no GPU can run Gemma 4 31B without also fitting Qwen 3.6 27B.
What is the difference between Qwen 3.6 27B and Gemma 4 31B?
Qwen 3.6 27B has 27B parameters (dense) with a 256k context window. Gemma 4 31B has 31B parameters (dense) with a 250k context window.
Which model fits in 24 GB of VRAM, Qwen 3.6 27B or Gemma 4 31B?
Both fit in 24 GB of VRAM at Q4_K_M — Qwen 3.6 27B needs 18.8 GB and Gemma 4 31B needs 23.2 GB.
Full Qwen 3.6 27B page →Full Gemma 4 31B page →Check your hardware →