30-SECOND SUMMARY
What to take away
- GGUF stores model tensors and standardized metadata for inference.
- Q4_K is approximately 4.5 bits per weight and Q5_K approximately 5.5.
- Compare quality, speed, memory, and stability with identical prompts instead of choosing by file size alone.
From weights to local runtime
Quantization reduces size and may change quality.
- 01WEIGHTS
Original model
- 02QUANTIZE
Reduce precision
- 03GGUF
Tensors and metadata
- 04TEST
Compare on-device
What GGUF contains
GGUF packages tensors with metadata such as architecture and tokenizer information for efficient inference in llama.cpp-compatible runtimes.
The format does not validate the publisher, training data, license, or safety of the model.
What quantization changes
Quantization represents weights with fewer bits, reducing file and memory size. The trade-off is possible information loss, which can affect tasks differently.
Published GGUF tables describe Q4_K at about 4.5 bits per weight, Q5_K at 5.5, and Q6_K at 6.5625.
| Format | Approx. bits/weight | Planning use |
|---|---|---|
| Q3_K | 3.4375 | Severe memory limits |
| Q4_K | 4.5 | Practical first baseline |
| Q5_K | 5.5 | Compare when memory allows |
| Q6_K | 6.5625 | Higher-capacity test |
Leave memory headroom
The weight file is only part of total usage. KV cache, runtime buffers, the operating system, and other applications also consume memory.
A model that barely fits may spill to slower memory or fail with longer context.
Compare Q4 and Q5 correctly
Keep the base model, runtime, prompt, temperature, and context fixed. Change only the quantization and repeat each task several times.
Include your real language and workload: factual extraction, summarization, JSON, long documents, and answer-not-found cases.
Check source and license
Use trusted publishers and verify hashes when available. Update the runtime because model parsers can have security vulnerabilities.
Quantization does not erase the original model license. Review commercial-use and redistribution terms before deployment.
Frequently asked questions
Is Q4_K_M always the best choice?
No. It is a useful baseline, but compare Q4 and Q5 on your own workload and hardware.
Is GGUF file size the RAM requirement?
No. Context cache, runtime, and operating-system memory are additional.
Does quantization change the license?
It generally does not remove the obligations of the original model license.
Primary sources
Check the original documentation for version-specific details.