Gemma 3 12B IT Ultra Heretic GGUF — Hardware Requirements & GPU Compatibility
Vision
6.8K downloads
3 likesSpecifications
- Publisher
- llmfan46
- Family
- Gemma
- Parameters
- 12B
- License
- Gemma Terms
Get Started
HuggingFace
How Much VRAM Does Gemma 3 12B IT Ultra Heretic GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| IQ3_XXS | 3.10 | 5.1 GB | — | 4.65 GB | Importance-weighted 3-bit |
| IQ3_XS | 3.30 | 5.5 GB | — | 4.95 GB | Importance-weighted 3-bit, extra small |
| IQ3_S | 3.40 | 5.6 GB | — | 5.10 GB | Importance-weighted 3-bit, small |
| IQ3_M | 3.60 | 5.9 GB | — | 5.40 GB | Importance-weighted 3-bit, medium |
| IQ4_XS | 4.30 | 7.1 GB | — | 6.45 GB | Importance-weighted 4-bit, compact |
| IQ4_NL | 4.50 | 7.4 GB | — | 6.75 GB | Importance-weighted 4-bit, non-linear |
| Q5_K_S | 5.50 | 9.1 GB | — | 8.25 GB | 5-bit small quantization |
| Q5_K_M | 5.70 | 9.4 GB | — | 8.55 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 10.9 GB | — | 9.90 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 13.2 GB | — | 12.00 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Gemma 3 12B IT Ultra Heretic GGUF?
IQ4_XS · 7.1 GBGemma 3 12B IT Ultra Heretic GGUF (IQ4_XS) requires 7.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 10+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080.
Runs great
— Plenty of headroom
Which Devices Can Run Gemma 3 12B IT Ultra Heretic GGUF?
IQ4_XS · 7.1 GB33 devices with unified memory can run Gemma 3 12B IT Ultra Heretic GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Gemma 3 12B IT Ultra Heretic GGUF need?
Gemma 3 12B IT Ultra Heretic GGUF requires 5.1 GB of VRAM at IQ3_XXS, or 13.2 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 12B × 3.1 bits ÷ 8 = 4.7 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
IQ3_XXS5.1 GB- What's the best quantization for Gemma 3 12B IT Ultra Heretic GGUF?
For Gemma 3 12B IT Ultra Heretic GGUF, IQ4_NL (7.4 GB) offers the best balance of quality and VRAM usage. Q5_K_S (9.1 GB) provides better quality if you have the VRAM. The smallest option is IQ3_XXS at 5.1 GB.
VRAM requirement by quantization
IQ3_XXS5.1 GB~70%IQ3_S5.6 GB~75%IQ4_NL ★7.4 GB~88%Q5_K_S9.1 GB~92%Q5_K_M9.4 GB~92%Q8_013.2 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run Gemma 3 12B IT Ultra Heretic GGUF on a Mac?
Gemma 3 12B IT Ultra Heretic GGUF requires at least 5.1 GB at IQ3_XXS, 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 3 12B IT Ultra Heretic GGUF locally?
Yes — Gemma 3 12B IT Ultra Heretic GGUF can run locally on consumer hardware. At IQ3_XXS quantization it needs 5.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma 3 12B IT Ultra Heretic GGUF?
At IQ3_XXS, Gemma 3 12B IT Ultra Heretic GGUF can reach ~569 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~128 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 ÷ 5.1 × 0.55 = ~569 tok/s
Estimated speed at IQ3_XXS (5.1 GB)
AMD Instinct MI300X~569 tok/sNVIDIA GeForce RTX 4090~128 tok/sNVIDIA H100 SXM~426 tok/sAMD Instinct MI250X~352 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Gemma 3 12B IT Ultra Heretic GGUF?
At IQ3_XXS, the download is about 4.65 GB. The full-precision Q8_0 version is 12.00 GB.
- Which GPUs can run Gemma 3 12B IT Ultra Heretic GGUF?
35 consumer GPUs can run Gemma 3 12B IT Ultra Heretic GGUF at IQ3_XXS (5.1 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Gemma 3 12B IT Ultra Heretic GGUF?
33 devices with unified memory can run Gemma 3 12B IT Ultra Heretic GGUF at IQ3_XXS (5.1 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.