Gemma 4 26B A4B IT Uncensored — Hardware Requirements & GPU Compatibility
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Gemma 4 26B A4B IT Uncensored is a 25.8B-parameter open language model from TrevorJS in the Gemma family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 16.13 GB of VRAM — see which GPUs and Macs can run it below.
243.0K downloads
39 likesSpecifications
- Publisher
- TrevorJS
- Family
- Gemma
- Parameters
- 25.8B
- Architecture
- Gemma4ForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-04-05
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Gemma 4 26B A4B IT Uncensored Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q4_K_M | 4.80 | 16.1 GB | 60.1 GB | 15.48 GB | 4-bit medium quantization — most popular sweet spot |
| Q8_0 | 8.00 | 26.4 GB | 70.4 GB | 25.81 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Gemma 4 26B A4B IT Uncensored?
Q4_K_M · 16.1 GBGemma 4 26B A4B IT Uncensored (Q4_K_M) requires 16.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 21+ GB is recommended. Using the full 262K context window can add up to 44.0 GB, bringing total usage to 60.1 GB. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroom
Which Devices Can Run Gemma 4 26B A4B IT Uncensored?
Q4_K_M · 16.1 GB21 devices with unified memory can run Gemma 4 26B A4B IT Uncensored, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomRelated Models
Derivatives (1)
Frequently Asked Questions
- How much VRAM does Gemma 4 26B A4B IT Uncensored need?
Gemma 4 26B A4B IT Uncensored requires 16.1 GB of VRAM at Q4_K_M, or 26.4 GB at Q8_0. Full 262K context adds up to 44.0 GB (60.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 25.8B × 4.8 bits ÷ 8 = 15.5 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 44.6 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M16.1 GBQ4_K_M + full context60.1 GB- Can NVIDIA GeForce RTX 4090 run Gemma 4 26B A4B IT Uncensored?
Yes, at Q4_K_M (16.1 GB) or lower. Higher quantizations like Q8_0 (26.4 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Gemma 4 26B A4B IT Uncensored?
For Gemma 4 26B A4B IT Uncensored, Q4_K_M (16.1 GB) offers the best balance of quality and VRAM usage. Q8_0 (26.4 GB) provides better quality if you have the VRAM.
VRAM requirement by quantization
Q4_K_M ★16.1 GBQ8_026.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Gemma 4 26B A4B IT Uncensored on a Mac?
Gemma 4 26B A4B IT Uncensored requires at least 16.1 GB at Q4_K_M, 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 26B A4B IT Uncensored locally?
Yes — Gemma 4 26B A4B IT Uncensored can run locally on consumer hardware. At Q4_K_M quantization it needs 16.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma 4 26B A4B IT Uncensored?
At Q4_K_M, Gemma 4 26B A4B IT Uncensored can reach ~181 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~41 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 ÷ 16.1 × 0.55 = ~181 tok/s
Estimated speed at Q4_K_M (16.1 GB)
~181 tok/s~41 tok/s~135 tok/s~112 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 26B A4B IT Uncensored?
At Q4_K_M, the download is about 15.48 GB. The full-precision Q8_0 version is 25.81 GB.
- Which GPUs can run Gemma 4 26B A4B IT Uncensored?
6 consumer GPUs can run Gemma 4 26B A4B IT Uncensored at Q4_K_M (16.1 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.
- Which devices can run Gemma 4 26B A4B IT Uncensored?
21 devices with unified memory can run Gemma 4 26B A4B IT Uncensored at Q4_K_M (16.1 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.