Humanizer Gemma 4 E4b — Hardware Requirements & GPU Compatibility
Chat
Humanizer Gemma 4 E4b is a 7.9B-parameter open language model from jialinyyzz in the Gemma 4 family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 5.28 GB of VRAM — see which GPUs and Macs can run it below.
3.5K downloads
4 likesSpecifications
- Publisher
- jialinyyzz
- Family
- Gemma 4
- Parameters
- 7.9B
- Architecture
- Gemma4ForConditionalGeneration
- Context Length
- 131,072 tokens
- Vocabulary Size
- 262,144
- Release Date
- 2026-09-11
- License
- Gemma Terms
Get Started
HuggingFace
How Much VRAM Does Humanizer Gemma 4 E4b Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 3.9 GB | 17.8 GB | 3.37 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 4.4 GB | 18.3 GB | 3.87 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 5.3 GB | 19.2 GB | 4.76 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 6.2 GB | 20.1 GB | 5.66 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 7.1 GB | 20.9 GB | 6.55 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 8.5 GB | 22.3 GB | 7.94 GB | 8-bit quantization, near-lossless |
| BF16 | 16.00 | 16.4 GB | 30.3 GB | 15.88 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Humanizer Gemma 4 E4b?
Q4_K_M · 5.3 GBHumanizer Gemma 4 E4b (Q4_K_M) requires 5.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. Using the full 131K context window can add up to 13.9 GB, bringing total usage to 19.2 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Humanizer Gemma 4 E4b?
Q4_K_M · 5.3 GB58 devices with unified memory can run Humanizer Gemma 4 E4b, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Apple iPhone 17 Pro.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Humanizer Gemma 4 E4b need?
Humanizer Gemma 4 E4b requires 5.3 GB of VRAM at Q4_K_M, or 16.4 GB at BF16. Full 131K context adds up to 13.9 GB (19.2 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 7.9B × 4.8 bits ÷ 8 = 4.8 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 14.4 GB (at full 131K context)
VRAM usage by quantization
Q4_K_M5.3 GBQ4_K_M + full context19.2 GB- What's the best quantization for Humanizer Gemma 4 E4b?
For Humanizer Gemma 4 E4b, Q4_K_M (5.3 GB) offers the best balance of quality and VRAM usage. Q5_K_M (6.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.9 GB.
VRAM requirement by quantization
Q2_K3.9 GBQ4_K_M ★5.3 GBQ5_K_M6.2 GBQ6_K7.1 GBQ8_08.5 GBBF1616.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Humanizer Gemma 4 E4b on a Mac?
Humanizer Gemma 4 E4b requires at least 3.9 GB at Q2_K, 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 Humanizer Gemma 4 E4b locally?
Yes — Humanizer Gemma 4 E4b can run locally on consumer hardware. At Q4_K_M quantization it needs 5.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Humanizer Gemma 4 E4b?
At Q4_K_M, Humanizer Gemma 4 E4b can reach ~909 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~124 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 5.3 × 0.65 = ~985 tok/s
Estimated speed at Q4_K_M (5.3 GB)
~985 tok/s~124 tok/s~985 tok/s~909 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Humanizer Gemma 4 E4b?
At Q4_K_M, the download is about 4.76 GB. The full-precision BF16 version is 15.88 GB. The smallest option (Q2_K) is 3.37 GB.
- Which GPUs can run Humanizer Gemma 4 E4b?
52 consumer GPUs can run Humanizer Gemma 4 E4b at Q4_K_M (5.3 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Humanizer Gemma 4 E4b?
59 devices with unified memory can run Humanizer Gemma 4 E4b at Q4_K_M (5.3 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.