Gemma 4 26B (MoE) vs Gemma 4 31B
Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.
Quick verdict
Gemma 4 26B (MoE) is more hardware-efficient: it needs 17.6 GB at its Q4_K_M build vs 22.6 GB for Gemma 4 31B's Q4_K_M, fitting on 91 GPUs natively. Gemma 4 26B (MoE) is a Mixture of Experts model: it has 25.2B total parameters but only 3.8B are active per token, making inference faster than its total size suggests.
VRAM at each quantization (8k context)
FP32
Gemma 4 26B (MoE)
113.3 GB
Gemma 4 31B
139.2 GB
BF16
Gemma 4 26B (MoE)
56.9 GB
Gemma 4 31B
70.5 GB
FP16
Gemma 4 26B (MoE)
56.9 GB
Gemma 4 31B
70.5 GB
Q8_0
Gemma 4 26B (MoE)
30.4 GB
Gemma 4 31B
38.2 GB
Q6_K
Gemma 4 26B (MoE)
23.6 GB
Gemma 4 31B
29.9 GB
Q5_K_M
Gemma 4 26B (MoE)
20.5 GB
Gemma 4 31B
26.2 GB
Q4_K_M
Gemma 4 26B (MoE)
17.6 GB
Gemma 4 31B
22.6 GB
Q3_K_M
Gemma 4 26B (MoE)
14.0 GB
Gemma 4 31B
18.2 GB
Q2_K
Gemma 4 26B (MoE)
11.2 GB
Gemma 4 31B
14.8 GB
NVFP4
Gemma 4 26B (MoE)
14.5 GB
Gemma 4 31B
18.9 GB
| Quant | Gemma 4 26B (MoE) | Gemma 4 31B | Diff |
|---|---|---|---|
| FP32 | 113.3 GB | 139.2 GB | -19% |
| BF16 | 56.9 GB | 70.5 GB | -19% |
| FP16 | 56.9 GB | 70.5 GB | -19% |
| Q8_0 | 30.4 GB | 38.2 GB | -20% |
| Q6_K | 23.6 GB | 29.9 GB | -21% |
| Q5_K_M | 20.5 GB | 26.2 GB | -22% |
| Q4_K_M | 17.6 GB | 22.6 GB | -22% |
| Q3_K_M | 14.0 GB | 18.2 GB | -23% |
| Q2_K | 11.2 GB | 14.8 GB | -24% |
| NVFP4 | 14.5 GB | 18.9 GB | -23% |
Diff is Gemma 4 26B (MoE) relative to Gemma 4 31B. Green = lower VRAM (fits more GPUs).
Model specifications
| Spec | Gemma 4 26B (MoE) | Gemma 4 31B |
|---|---|---|
| Org | ||
| Parameters | 25.2B | 30.7B |
| Architecture | MoE (3.8B active) | Dense |
| Context | 256k tokens | 256k tokens |
| Modalities | text, vision | text, vision |
| License | Apache 2.0 | Apache 2.0 |
| Commercial | Yes | Yes |
| Released | 2026-04-02 | 2026-04-02 |
| GPUs (native) | 91 / 119 | 84 / 119 |
Benchmark scores
| Benchmark | Gemma 4 26B (MoE) | Gemma 4 31B |
|---|---|---|
| MMLU-Pro | 82.6 | 85.2 |
| GPQA Diamond | 82.3 | 84.3 |
| LiveCodeBench | 77.1 | 80.0 |
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 Gemma 4 26B (MoE)(7)
- NVIDIA RTX 507012 GB
- NVIDIA RTX 4070 Ti12 GB
- NVIDIA RTX 4070 SUPER12 GB
- NVIDIA RTX 407012 GB
- NVIDIA RTX 3060 12GB12 GB
- Intel Arc B580 12GB12 GB
- Intel Arc Pro A60 12GB12 GB
GPUs that run only Gemma 4 31B(0)
Every GPU that runs Gemma 4 31B also runs Gemma 4 26B (MoE).
GPUs that run both natively(84)
- NVIDIA RTX 509032 GB
- NVIDIA RTX 508016 GB
- NVIDIA RTX 5070 Ti16 GB
- NVIDIA RTX 5060 Ti 16GB16 GB
- NVIDIA RTX 409024 GB
- NVIDIA RTX 408016 GB
- NVIDIA RTX 4070 Ti SUPER16 GB
- NVIDIA RTX 4060 Ti 16GB16 GB
- NVIDIA RTX 309024 GB
- NVIDIA RTX 3090 Ti24 GB
- NVIDIA B300 288GB288 GB
- NVIDIA B200 180GB180 GB
- +72 more GPUs run both
Which should you use?
Choose Gemma 4 26B (MoE) if:
- • You have limited VRAM: it's a smaller model needing 17.6 GB vs 22.6 GB
- • You want fast inference: MoE only activates 3.8B params per token
Choose Gemma 4 31B if:
- • You want maximum capability and have a 23 GB+ GPU
- • Benchmark quality matters: scores 85.2 vs 82.6 on MMLU-Pro
- • You're running coding tasks
- • You need chain-of-thought reasoning
Frequently asked questions
- Which is better, Gemma 4 26B (MoE) or Gemma 4 31B?
- Gemma 4 26B (MoE) has 25.2B parameters vs 30.7B for Gemma 4 31B, so Gemma 4 31B is the larger model. Gemma 4 26B (MoE) is more hardware-efficient, needing 17.6 GB at its Q4_K_M build vs 22.6 GB for Gemma 4 31B's Q4_K_M. Gemma 4 26B (MoE) runs on more GPUs natively (91 vs 84). On MMLU-Pro, Gemma 4 31B scores higher (85.2 vs 82.6).
- How much VRAM does Gemma 4 26B (MoE) need vs Gemma 4 31B?
- At 8k context, Gemma 4 26B (MoE) needs approximately 17.6 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, Gemma 4 26B (MoE) requires 56.9 GB (FP16) vs 70.5 GB (FP16) for Gemma 4 31B.
- Can you run Gemma 4 26B (MoE) 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, 7 GPUs can run Gemma 4 26B (MoE) but not Gemma 4 31B, and no GPU can run Gemma 4 31B without also fitting Gemma 4 26B (MoE).
- What is the difference between Gemma 4 26B (MoE) and Gemma 4 31B?
- Gemma 4 26B (MoE) has 25.2B parameters (3.8B active, MoE) 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, Gemma 4 26B (MoE) or Gemma 4 31B?
- Both fit in 24 GB of VRAM at their respective recommended builds: Gemma 4 26B (MoE) (Q4_K_M) needs 17.6 GB and Gemma 4 31B (Q4_K_M) needs 22.6 GB.