This repository contains GGUF-formatted, quantized versions of Gemma 3 270M (base model), prepared and published by Open4Bits for efficient local inference on low-resource systems.

Open4Bits is a model distribution and optimization initiative under ArkAILabs, which is run and operated by ArkDevLabs. Through Open4Bits, ArkAI Labs publishes quantized, optimized, and deployment-ready models in GGUF and other inference-friendly formats.

About Open4Bits

Open4Bits focuses on making modern language models usable on real-world hardware.

Through Open4Bits, ArkAI Labs publishes:

Quantized language models
GGUF models for local inference
Optimized formats for CPU-friendly deployment
Lightweight variants for low-resource systems

The goal is to enable practical AI usage without requiring high-end GPUs.

Available Models

File	Quantization	Notes
`gemma-3-270m-IQ4_NL.gguf`	IQ4_NL	Ultra-light, fastest, lowest memory usage
`gemma-3-270m-IQ4_XS.gguf`	IQ4_XS	Slightly higher quality than IQ4_NL
`gemma-3-270m-Q4_0.gguf`	Q4_0	Legacy 4-bit quantization
`gemma-3-270m-Q4_1.gguf`	Q4_1	Legacy 4-bit with improved accuracy
`gemma-3-270m-Q4_K_S.gguf`	Q4_K_S	Modern K-quant (small)
`gemma-3-270m-Q4_K_M.gguf`	Q4_K_M	Modern K-quant (medium, recommended)
`gemma-3-270m-Q5_0.gguf`	Q5_0	Legacy 5-bit quantization
`gemma-3-270m-Q5_1.gguf`	Q5_1	Legacy 5-bit with improved accuracy
`gemma-3-270m-Q5_K_S.gguf`	Q5_K_S	Modern K-quant (small, higher quality)
`gemma-3-270m-Q5_K_M.gguf`	Q5_K_M	Modern K-quant (medium, high quality)
`gemma-3-270m-Q8_0.gguf`	Q8_0	Near-baseline quality (reference)

Recommended Variants

Q4_K_M – Recommended for most users (best balance of quality, speed, and memory)
Q5_K_M – Higher quality for users who can afford additional memory usage
Q8_0 – Near-baseline reference for evaluation and comparison

Quantization Overview

IQ4 Variants

Extremely small and fast
Suitable for very limited hardware
Noticeable quality reduction compared to K-quant variants

Q4_0 / Q4_1

Older quantization formats
Included for compatibility and comparison
Generally inferior to modern K-quant variants

K-Quant Variants (Q4_K_S, Q4_K_M, Q5_K_S, Q5_K_M)

Newer, higher-quality quantization methods
Better accuracy per bit
Standard choice for GGUF deployments

Q8_0

Near-baseline (FP16-like) quality
Highest memory usage among provided variants
Intended for reference, testing, and debugging

Usage with llama.cpp

bash

./main -m gemma-3-270m-Q4_K_M.gguf \
  -p "Explain what GGUF quantization is." \
  -n 128

Usage with Ollama

Create a Modelfile:

FROM ./gemma-3-270m-Q4_K_M.gguf

Then run:

bash

ollama create gemma-270m -f Modelfile
ollama run gemma-270m

System Requirements (Approximate)

Quantization	Memory Requirement
IQ4_NL / IQ4_XS	~300–400 MB
Q4_0 / Q4_1	~450–500 MB
Q4_K_S	~500 MB
Q4_K_M	~550–600 MB
Q5_K_S	~600–650 MB
Q5_K_M	~650–750 MB
Q8_0	~900 MB – 1 GB

Actual memory usage depends on context length and runtime configuration.

Intended Use and Limitations

This model is a small, lightweight base language model optimized for low-resource inference.

It is suitable for:

Token generation and experimentation
Embedding-style or downstream fine-tuning use
Educational and demonstration purposes
Lightweight local inference

Limitations:

Not instruction-tuned
Not designed for complex reasoning tasks
Not suitable for advanced code generation
May hallucinate or produce incomplete outputs for complex prompts

License

This repository follows the original Gemma model license.

Users are responsible for complying with all upstream license terms and usage restrictions.

Credits

Original model: Google (Gemma)
Quantization and GGUF packaging: Open4Bits (ArkAI Labs, operated by ArkDevLabs)
Tooling: llama.cpp

Support

Open4Bits is an initiative under ArkAI Labs, operated by ArkDevLabs, focused on open and accessible AI.

If you find these models useful, please consider supporting the work by:

Liking the model on Hugging Face
Sharing feedback or reporting issues
Using Open4Bits models in your projects and research

Organization Links

Open4Bits on Hugging Face: https://huggingface.co/Open4Bits
ArkAI Labs on Hugging Face: https://huggingface.co/ArkAiLab-Adl
ArkDevLabs Website: https://arkdevlabs.com

Open4bits/gemma-3-270m-it-gguf

gemma-3-270m-gguf