How much VRAM does Gemma 3 4B need?

Gemma 3 4B requires approximately 0.0 GB VRAM at Q4_K_M quantization with 1K context and 10% overhead. At Q8_0 it needs ~0.0 GB, and at FP16 ~0.0 GB. Use the PCPARTGUIDE VRAM Calculator for exact requirements at any context length and overhead setting.

Can I run Gemma 3 4B on a consumer GPU?

Yes, Gemma 3 4B can run on consumer GPUs. At Q4_K_M quantization with moderate context length, it fits on a 12 GB GPU. For best performance, use a 12 GB or larger GPU with at least 8 GB VRAM for reasonable context lengths.

What is Gemma 3 4B's context window?

Gemma 3 4B supports a maximum context window of 32,768 tokens. The default context is 8,192 tokens. Larger contexts require proportionally more VRAM for the KV cache — use the VRAM Calculator to estimate exact requirements at your target context length.

What quantization level should I use for Gemma 3 4B?

For Gemma 3 4B, Q4_K_M is the recommended quantization — it provides an excellent quality-to-VRAM ratio at ~0.0 GB. Q8_0 offers slightly better quality at ~2× the VRAM. Q4_K_M is the sweet spot for most users.

How does Gemma 3 4B compare to similar models?

Gemma 3 4B is a 4.0B Dense model from the Gemma family. Browse other Gemma models on the PCPARTGUIDE directory for comparable alternatives with different parameter counts and VRAM requirements. Use the Model Transparency scores to assess documentation quality and reproducibility.

GemmaDenseGemma License

Gemma 3 4B

Gemma 3 4B is a dense transformer language model from the Gemma family, containing 4B parameters across 34 layers. It supports up to 33K tokens of context with a hidden dimension of 2560 and 4 KV heads for efficient grouped-query attention …

4.0B

Parameters

32K

Max Context

Dense

Architecture

—

Released

Text

Modality

About Gemma 3 4B

General PurposeChat

Technical Specifications

Total Parameters4.0B

ArchitectureDense

Attention TypeGQA (Grouped Query Attention)

Hidden Dimensiond = 2,560

Transformer Layers34

Attention Heads16

KV Headsn_kv = 4

Head Dimensiond_head = 160

Activation FunctionSwiGLU

NormalizationRMSNorm

Position EmbeddingRoPE

System Requirements

Estimated VRAM at 10% overhead for different quantization methods and context sizes.

Quantization	1K ctx	32K ctx
Q4_K_M0.50 B/W ~97% of FP16	2.15Consumer GPU	4.72Consumer GPU
Q8_01.00 B/W ~100% of FP16	4.22Consumer GPU	6.79Consumer GPU
F162.00 B/W Reference	8.35Consumer GPU	10.93Consumer GPU

Params

25.2B

Layers

Context

256K

3.8B active

Find the right GPU for Gemma 3 4B

Use the interactive VRAM Calculator to see exactly how much memory you need at any quantization level, context length, and overhead setting.

Open VRAM Calculator Best GPU Guide VRAM Guide