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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 19.0 GB at its Q4_K_M build vs 22.6 GB for Gemma 4 31B's Q4_K_M, fitting on 84 GPUs natively.

VRAM at each quantization (8k context)

FP32
Qwen 3.6 27B
121.6 GB
Gemma 4 31B
139.2 GB
BF16
Qwen 3.6 27B
61.1 GB
Gemma 4 31B
70.5 GB
FP16
Qwen 3.6 27B
61.1 GB
Gemma 4 31B
70.5 GB
Q8_0
Qwen 3.6 27B
32.8 GB
Gemma 4 31B
38.2 GB
Q6_K
Qwen 3.6 27B
25.4 GB
Gemma 4 31B
29.9 GB
Q5_K_M
Qwen 3.6 27B
22.1 GB
Gemma 4 31B
26.2 GB
Q4_K_M
Qwen 3.6 27B
19.0 GB
Gemma 4 31B
22.6 GB
Q3_K_M
Qwen 3.6 27B
15.2 GB
Gemma 4 31B
18.2 GB
Q2_K
Qwen 3.6 27B
12.1 GB
Gemma 4 31B
14.8 GB
NVFP4
Qwen 3.6 27B
15.7 GB
Gemma 4 31B
18.9 GB
QuantQwen 3.6 27BGemma 4 31BDiff
FP32121.6 GB139.2 GB-13%
BF1661.1 GB70.5 GB-13%
FP1661.1 GB70.5 GB-13%
Q8_032.8 GB38.2 GB-14%
Q6_K25.4 GB29.9 GB-15%
Q5_K_M22.1 GB26.2 GB-15%
Q4_K_M19.0 GB22.6 GB-16%
Q3_K_M15.2 GB18.2 GB-17%
Q2_K12.1 GB14.8 GB-18%
NVFP415.7 GB18.9 GB-17%

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
Parameters27B30.7B
ArchitectureDenseDense
Context256k tokens256k tokens
Modalitiestext, vision, videotext, vision
LicenseApache 2.0Apache 2.0
CommercialYesYes
Released2026-04-222026-04-02
GPUs (native)84 / 11984 / 119

Benchmark scores

BenchmarkQwen 3.6 27BGemma 4 31B
MMLU-Pro86.285.2
GPQA Diamond87.884.3
LiveCodeBench83.980.0
SWE-bench Verified77.2N/A
SWE-bench Pro53.5N/A

Green = higher score (better). N/A = not yet available. ~ = inherited from a base model, not independently reported for that release itself.

GPUs that run only Qwen 3.6 27B(0)

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

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(84)

Which should you use?

Choose Qwen 3.6 27B if:
  • • You have limited VRAM: it's a smaller model needing 19.0 GB vs 22.6 GB
  • • Benchmark quality matters: scores 86.2 vs 85.2 on MMLU-Pro
  • • It's the newer release (2026-04-22 vs 2026-04-02); check the benchmark table above for what actually improved
Choose Gemma 4 31B if:
  • • You want maximum capability and have a 23 GB+ GPU

Frequently asked questions

Which is better, Qwen 3.6 27B or Gemma 4 31B?
Qwen 3.6 27B has 27B parameters vs 30.7B for Gemma 4 31B, so Gemma 4 31B is the larger model. Qwen 3.6 27B is more hardware-efficient, needing 19.0 GB at its Q4_K_M build vs 22.6 GB for Gemma 4 31B's Q4_K_M. 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 8k context, Qwen 3.6 27B needs approximately 19.0 GB of VRAM at its Q4_K_M build, while Gemma 4 31B needs 22.6 GB at its Q4_K_M build. At the largest build each ships, Qwen 3.6 27B requires 61.1 GB (FP16) vs 70.5 GB (FP16) for Gemma 4 31B.
Can you run Qwen 3.6 27B on the same GPUs as Gemma 4 31B?
Yes, 84 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA RTX 5080, NVIDIA RTX 5070 Ti. However, no GPU can run Qwen 3.6 27B without also fitting 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 30.7B parameters (dense) with a 256k 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 their respective recommended builds: Qwen 3.6 27B (Q4_K_M) needs 19.0 GB and Gemma 4 31B (Q4_K_M) needs 22.6 GB.
Full Qwen 3.6 27B page →Full Gemma 4 31B page →Check your hardware →