Gemma 2 2B IT GGUF — Hardware Requirements & GPU Compatibility
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This is a GGUF-quantized version of Google's Gemma 2 2B IT, repackaged by Bartowski. Gemma 2 2B IT is a lightweight instruction-tuned model from Google's Gemma 2 family, designed for efficient on-device inference while maintaining strong performance on conversational and instruction-following tasks. With only 2 billion parameters, this is one of the smallest capable instruction-tuned models available. The GGUF format makes it compatible with llama.cpp and its ecosystem of frontends, and the small size means it can run comfortably on virtually any modern hardware, including systems with limited VRAM or even CPU-only setups.
860.5K downloads
85 likesSpecifications
- Publisher
- Bartowski
- Family
- Gemma 2
- Parameters
- 2B
- Release Date
- 2024-08-05
- License
- Gemma Terms
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HuggingFace
How Much VRAM Does Gemma 2 2B IT GGUF Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| IQ3_M | 3.60 | 1.0 GB | — | 0.90 GB | Importance-weighted 3-bit, medium |
| Q3_K_L | 4.10 | 1.1 GB | — | 1.02 GB | 3-bit large quantization |
| IQ4_XS | 4.30 | 1.2 GB | — | 1.07 GB | Importance-weighted 4-bit, compact |
| Q4_K_S | 4.50 | 1.2 GB | — | 1.13 GB | 4-bit small quantization |
| Q4_K_M | 4.80 | 1.3 GB | — | 1.20 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_S | 5.50 | 1.5 GB | — | 1.38 GB | 5-bit small quantization |
| Q5_K_M | 5.70 | 1.6 GB | — | 1.43 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 1.8 GB | — | 1.65 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 2.2 GB | — | 2.00 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Gemma 2 2B IT GGUF?
Q4_K_M · 1.3 GBGemma 2 2B IT GGUF (Q4_K_M) requires 1.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2+ GB is recommended. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run Gemma 2 2B IT GGUF?
Q4_K_M · 1.3 GB33 devices with unified memory can run Gemma 2 2B IT GGUF, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Gemma 2 2B IT GGUF need?
Gemma 2 2B IT GGUF requires 1.3 GB of VRAM at Q4_K_M, or 2.2 GB at Q8_0.
VRAM = Weights + KV Cache + Overhead
Weights = 2B × 4.8 bits ÷ 8 = 1.2 GB
KV Cache + Overhead ≈ 0.1 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M1.3 GB- What's the best quantization for Gemma 2 2B IT GGUF?
For Gemma 2 2B IT GGUF, Q4_K_M (1.3 GB) offers the best balance of quality and VRAM usage. Q5_K_S (1.5 GB) provides better quality if you have the VRAM. The smallest option is IQ3_M at 1.0 GB.
VRAM requirement by quantization
IQ3_M1.0 GB~78%IQ4_XS1.2 GB~87%Q4_K_M ★1.3 GB~89%Q5_K_S1.5 GB~92%Q5_K_M1.6 GB~92%Q8_02.2 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run Gemma 2 2B IT GGUF on a Mac?
Gemma 2 2B IT GGUF requires at least 1.0 GB at IQ3_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 2 2B IT GGUF locally?
Yes — Gemma 2 2B IT GGUF can run locally on consumer hardware. At Q4_K_M quantization it needs 1.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Gemma 2 2B IT GGUF?
At Q4_K_M, Gemma 2 2B IT GGUF can reach ~2208 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~496 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 ÷ 1.3 × 0.55 = ~2208 tok/s
Estimated speed at Q4_K_M (1.3 GB)
AMD Instinct MI300X~2208 tok/sNVIDIA GeForce RTX 4090~496 tok/sNVIDIA H100 SXM~1651 tok/sAMD Instinct MI250X~1365 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Gemma 2 2B IT GGUF?
At Q4_K_M, the download is about 1.20 GB. The full-precision Q8_0 version is 2.00 GB. The smallest option (IQ3_M) is 0.90 GB.