Gemma 4 E2B IT Uncensored — Hardware Requirements & GPU Compatibility
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Gemma 4 E2B IT Uncensored is a 5.1B-parameter open language model from TrevorJS in the Gemma family. It supports a context window of up to 131,072 tokens. At BF16 it needs about 10.60 GB of VRAM — see which GPUs and Macs can run it below.
1.6K downloads
20 likesSpecifications
- Publisher
- TrevorJS
- Family
- Gemma
- Parameters
- 5.1B
- Architecture
- Gemma4ForConditionalGeneration
- Context Length
- 131,072 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-04-05
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Gemma 4 E2B IT Uncensored Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 10.6 GB | 14.1 GB | 10.25 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Gemma 4 E2B IT Uncensored?
BF16 · 10.6 GBGemma 4 E2B IT Uncensored (BF16) requires 10.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 14+ GB is recommended. Using the full 131K context window can add up to 3.5 GB, bringing total usage to 14.1 GB. 27 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Gemma 4 E2B IT Uncensored?
BF16 · 10.6 GB27 devices with unified memory can run Gemma 4 E2B IT Uncensored, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Gemma 4 E2B IT Uncensored need?
Gemma 4 E2B IT Uncensored requires 10.6 GB of VRAM at BF16. Full 131K context adds up to 3.5 GB (14.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 5.1B × 16 bits ÷ 8 = 10.2 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 3.9 GB (at full 131K context)
VRAM usage by quantization
BF1610.6 GBBF16 + full context14.1 GB- Can I run Gemma 4 E2B IT Uncensored on a Mac?
Gemma 4 E2B IT Uncensored requires at least 10.6 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Gemma 4 E2B IT Uncensored locally?
Yes — Gemma 4 E2B IT Uncensored can run locally on consumer hardware. At BF16 quantization it needs 10.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma 4 E2B IT Uncensored?
At BF16, Gemma 4 E2B IT Uncensored can reach ~275 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~62 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 10.6 × 0.55 = ~275 tok/s
Estimated speed at BF16 (10.6 GB)
~275 tok/s~62 tok/s~206 tok/s~170 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Gemma 4 E2B IT Uncensored?
At BF16, the download is about 10.25 GB.
- Which GPUs can run Gemma 4 E2B IT Uncensored?
27 consumer GPUs can run Gemma 4 E2B IT Uncensored at BF16 (10.6 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 17 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Gemma 4 E2B IT Uncensored?
27 devices with unified memory can run Gemma 4 E2B IT Uncensored at BF16 (10.6 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.