Gemma 4 E2B
40 consumer GPUs can run Gemma 4 E2B at Q4 natively. Precise VRAM thresholds and benchmarks below.
llama.cpp 0.2.x · CUDA 12 · ROCm 6 · Updated monthly · methodology →
Execution Context
This model requires a Entry GPU (8 GB VRAM)
Cómo ejecutar este modelo
CPU vs GPU for Gemma 4 E2B →
VRAM Calculator — instant compatibility check
RTX 5090
32 GB · Runs Q4 natively · Check availability
*Prices and availability may change. Some links are affiliate links.
System Requirements
VRAM by Quantization
| Quantization | VRAM needed | Disk space | Quality |
|---|---|---|---|
| FP16 (max quality) | 4.4 GB | 4 GB | Maximum |
| Q8 (high quality) | 2.2 GB | 2 GB | Near-lossless |
| Q4 (recommended) Best balance | 1.1 GB | 1 GB | Recommended |
| Q2 (minimum) | 0.6 GB | 0.5 GB | Quality loss |
Model Details
| Developer | |
| Parameters | 2B |
| Context window | 128,000 tokens |
| License | Apache 2.0 |
| Use cases | chat, vision, reasoning |
| Released | 2026-04 |
Install with Ollama
ollama run gemma4:e2b Hugging Face
google/gemma-4-E2B Can your GPU run Gemma 4 E2B?
Gemma 4 E2B requires 1.1 GB VRAM at Q4. 40 consumer GPUs meet this threshold. Below 8 GB or -0.8999999999999999 GB you'll hit significant offload latency.
Hardware Performance Matrix
40 Q4 native · 0 offload · 0 unsupported
| GPU Unit | VRAM | Compatibility | Est. Speed | Action |
|---|---|---|---|---|
| RTX 5090 | 32GB | Optimal | 300 tok/s | Calculate → |
| RTX 4090 | 24GB | Optimal | 300 tok/s | Calculate → |
| M4 Ultra | 128GB | Optimal | 300 tok/s | Calculate → |
| RTX 5080 | 16GB | Optimal | 300 tok/s | Calculate → |
| M3 Ultra | 192GB | Optimal | 284 tok/s | Calculate → |
| RTX 4080 Super | 16GB | Optimal | 271 tok/s | Calculate → |
| RTX 5070 Ti | 16GB | Optimal | 294 tok/s | Calculate → |
| RTX 3090 | 24GB | Optimal | 299 tok/s | Calculate → |
| M4 Max 48GB | 48GB | Optimal | 201 tok/s | Calculate → |
| RX 7900 XTX | 24GB | Optimal | 300 tok/s | Calculate → |
| M4 Max 36GB | 36GB | Optimal | 201 tok/s | Calculate → |
| RTX 4070 Ti Super | 16GB | Optimal | 247 tok/s | Calculate → |
| RTX 3080 Ti | 12GB | Optimal | 291 tok/s | Calculate → |
| RX 7900 XT | 20GB | Optimal | 284 tok/s | Calculate → |
| RTX 5070 | 12GB | Optimal | 247 tok/s | Calculate → |
| RTX 3080 | 10GB | Optimal | 280 tok/s | Calculate → |
| M4 Pro | 24GB | Optimal | 100 tok/s | Calculate → |
| RX 7800 XT | 16GB | Optimal | 230 tok/s | Calculate → |
| RX 6800 XT | 16GB | Optimal | 189 tok/s | Calculate → |
| RTX 4070 | 12GB | Optimal | 186 tok/s | Calculate → |
| RTX 4060 Ti 16GB | 16GB | Optimal | 106 tok/s | Calculate → |
| RX 7700 XT | 12GB | Optimal | 159 tok/s | Calculate → |
| RTX 3070 Ti | 8GB | Optimal | 224 tok/s | Calculate → |
| RTX 4060 Ti | 8GB | Optimal | 106 tok/s | Calculate → |
| RTX 3070 | 8GB | Optimal | 165 tok/s | Calculate → |
| RX 6700 XT | 12GB | Optimal | 142 tok/s | Calculate → |
| M3 Pro | 18GB | Optimal | 56 tok/s | Calculate → |
| RTX 3060 Ti | 8GB | Optimal | 165 tok/s | Calculate → |
| RTX 2080 Ti | 11GB | Optimal | 165 tok/s | Calculate → |
| RTX 3060 | 12GB | Optimal | 133 tok/s | Calculate → |
| M2 Pro | 16GB | Optimal | 74 tok/s | Calculate → |
| RTX 4060 | 8GB | Optimal | 100 tok/s | Calculate → |
| Arc A770 16GB | 16GB | Optimal | 83 tok/s | Calculate → |
| M1 Pro | 16GB | Optimal | 74 tok/s | Calculate → |
| RX 7600 | 8GB | Optimal | 107 tok/s | Calculate → |
| RX 6600 XT | 8GB | Optimal | 100 tok/s | Calculate → |
| Arc A750 8GB | 8GB | Optimal | 75 tok/s | Calculate → |
| RX 6600 | 8GB | Optimal | 91 tok/s | Calculate → |
| RTX 3050 8GB | 8GB | Optimal | 83 tok/s | Calculate → |
| GTX 1660 Super | 6GB | Optimal | 123 tok/s | Calculate → |
Recommended GPUs for Gemma 4 E2B
Best picks by compatibility, VRAM headroom, and value — prices and availability may change.
RTX 5090
32 GB VRAM
Check availability →
RTX 4090
24 GB VRAM
Check availability →
M4 Ultra
128 GB VRAM
Check availability →
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Gemma 4 E2B — Compatibility guide
Gemma 4 E2B can run on CPU without a dedicated GPU — unusual for a 2B model. On an i7-13700K with llama.cpp Q4 it reaches 25 tok/s (comfortable for daily use). With a GPU you get 4–6× more speed — check the VRAM calculator for specifics.
Compare GPUs for Gemma 4 E2B
Which GPU is worth it? Real specs and benchmarks side by side.
Compatible Hardware
GPUs that run Gemma 4 E2B at Q4 — sorted by AI performance score.
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More Practical Alternatives
Similar models in the vision category with comparable VRAM footprints.
Not sure which GPU you need for Gemma 4 E2B?
The VRAM Calculator tells you exactly which quantization your hardware can handle.