Gemma 4 E4B VRAM Requirements
Gemma 4 E4B needs about 5.7 GB of VRAM at Q4_K_M with an 8K context: 4.5 GB for weights, 0.1 GB for the KV cache and 1.0 GB of runtime overhead. At Q8_0 it needs 9.1 GB and at full FP16 precision 16.1 GB. The smallest GPU that runs it fully is the RTX 3050 8GB.
5.7 GB VRAM
Gemma 4 E4B at Q4_K_M with 8K context and the KV cache in FP16.
- Weights 4.5 GB
- KV cache 0.1 GB
- Runtime overhead 1.0 GB
Which GPUs can run it
- RTX 3060 12GBFits~46 tok/s
- RTX 4060 Ti 16GBFits~37 tok/s
- RTX 3090 24GBFits~117 tok/s
- Radeon RX 7900 XTX 24GBFits~102 tok/s
- RTX 4090 24GBFits~126 tok/s
- RTX 5090 32GBFits~215 tok/s
- RTX 6000 Ada 48GBFits~120 tok/s
- A100 80GBFits~241 tok/s
- H100 80GB SXMFits~372 tok/s
- Ryzen AI Max+ 395 128GBFits~31 tok/s
- Apple M4 Max 128GBFits~70 tok/s
- Apple M5 Max 128GBFits~78 tok/s
- RTX PRO 6000 Blackwell 96GBFits~215 tok/s
- NVIDIA DGX Spark 128GBFits~33 tok/s
- Apple M3 Ultra 512GBFits~103 tok/s
Gemma 4 E4B VRAM by quantization
Total memory with an FP16 KV cache. "Smallest tier" is the smallest standard VRAM size with a 6% safety margin at 8K.
| Quantization | Bits/weight | Weights | Total at 8K | Total at 32K | Smallest tier |
|---|---|---|---|---|---|
| Q4_K_M | 4.85 | 4.5 GB | 5.7 GB | 6.1 GB | 8 GB |
| Q5_K_M | 5.69 | 5.3 GB | 6.5 GB | 6.9 GB | 8 GB |
| Q6_K | 6.59 | 6.1 GB | 7.3 GB | 7.7 GB | 8 GB |
| Q8_0 | 8.50 | 7.9 GB | 9.1 GB | 9.5 GB | 10 GB |
| FP16 / BF16 | 16.00 | 14.9 GB | 16.1 GB | 16.5 GB | 20 GB |
| Q3_K_M | 3.91 | 3.6 GB | 4.8 GB | 5.2 GB | 6 GB |
| Q2_K | 3.00 | 2.8 GB | 4.0 GB | 4.4 GB | 6 GB |
VRAM by context length
At Q4_K_M. Only 24 of 42 layers have their own KV cache; the last 18 reuse caches from earlier layers. Of those 24, 20 use a 512-token sliding window and 4 keep the full context (2 KV heads, 512-dimension heads), so long contexts are very cheap.
| Context | KV cache (FP16) | KV cache (Q8_0) | Total, FP16 cache | Total, Q8_0 cache |
|---|---|---|---|---|
| 4K tokens | 84 MB | 45 MB | 5.6 GB | 5.6 GB |
| 8K tokens | 0.1 GB | 79 MB | 5.7 GB | 5.6 GB |
| 32K tokens | 0.5 GB | 0.3 GB | 6.1 GB | 5.8 GB |
| 128K tokens | 2.0 GB | 1.1 GB | 7.6 GB | 6.6 GB |
GPUs that can run Gemma 4 E4B
At Q4_K_M with 8K context. "Best quant" is the highest-quality format that fits fully; "max context" is at Q4_K_M.
| GPU | Usable memory | Status | Best quant | Max context | Speed |
|---|---|---|---|---|---|
| RTX 3050 8GB | 8.0 GB | Fits | Q6_K | 124K | ~29 tok/s |
| RTX 4060 8GB | 8.0 GB | Fits | Q6_K | 124K | ~35 tok/s |
| RTX 4060 Ti 8GB | 8.0 GB | Fits | Q6_K | 124K | ~37 tok/s |
| Radeon RX 7600 8GB | 8.0 GB | Fits | Q6_K | 124K | ~32 tok/s |
| RTX 3060 Ti 8GB | 8.0 GB | Fits | Q6_K | 124K | ~58 tok/s |
| RTX 3070 8GB | 8.0 GB | Fits | Q6_K | 124K | ~58 tok/s |
| RTX 5060 8GB | 8.0 GB | Fits | Q6_K | 124K | ~58 tok/s |
| RTX 5060 Ti 8GB | 8.0 GB | Fits | Q6_K | 124K | ~58 tok/s |
| RTX 3070 Ti 8GB | 8.0 GB | Fits | Q6_K | 124K | ~77 tok/s |
| Intel Arc B570 10GB | 10.0 GB | Fits | Q8_0 | 128K | ~38 tok/s |
| RTX 3080 10GB | 10.0 GB | Fits | Q8_0 | 128K | ~96 tok/s |
| Apple M4 16GB | 10.7 GB | Fits | Q8_0 | 128K | ~16 tok/s |
| RTX 2080 Ti 11GB | 11.0 GB | Fits | Q8_0 | 128K | ~78 tok/s |
| RTX 2060 12GB | 12.0 GB | Fits | Q8_0 | 128K | ~43 tok/s |
About Gemma 4 E4B
The larger on-device Gemma 4 with about 4.5B effective parameters (8B including per-layer embeddings). It handles text, images and audio, and a full 128K context costs only about 2 GB of cache. A strong pick for 8 GB GPUs and laptops.
| Spec | Value |
|---|---|
| Parameters | 8B |
| Layers | 42 |
| Hidden size | 2560 |
| Attention heads / KV heads | 8 / 2 (varies by layer) |
| Head dimension | 256 |
| Vocabulary | 262,144 |
| Max context (used here) | 128K tokens |
| Layers with a growing cache | 4 of 42 |
| KV cache per token (FP16) | 16 KB |
| Released | 2026-04 |
| License | Apache 2.0 |
Gemma 4 E4B VRAM: common questions
Can Gemma 4 E4B run on a 6GB GPU?
Yes at Q4_K_M. The full file is about 4.5 GB and the cache is very small; runtimes that keep per-layer embeddings in system RAM need even less VRAM.
How much VRAM does Gemma 4 E4B need?
About 5.7 GB at Q4_K_M with an 8K context, 9.1 GB at Q8_0 and 16.1 GB at FP16. Longer contexts add 0.02 GB per 1,000 tokens with an FP16 cache.
What is the cheapest GPU that can run Gemma 4 E4B?
The smallest listed device that fits it fully at Q4_K_M with 8K context is the RTX 3050 8GB (8.0 GB usable).