Dataset Splitter
Split a dataset into training, validation and test files with a repeatable shuffle.
Quantization Size Calculator
See the file size of every GGUF quant of a model, and which ones fit your memory.
Quick Tool Overview
The Quantization Size Calculator lists the file size of every GGUF quantization of a model, from F16 to IQ2_XS, using measured bits per weight, and highlights the highest-quality quant that fits your GPU or Mac with room for context.
- What it does
- Calculates GGUF file sizes and which quants fit
- You give it
- A parameter count and the memory you have
- You get back
- Every quant with its size, fit and quality note
- Best for
- Choosing which GGUF file to download
About the Quantization Size Calculator
Model repositories list a dozen quantizations of the same model — Q8_0, Q6_K, Q5_K_M, Q4_K_M, IQ3_XS and more — and the right download is the highest-quality one that still fits in your memory with room left for context. This calculator works that out for you.
Choose a model or enter any parameter count, pick your GPU or Mac, and every quantization is listed with its effective bits per weight, file size, size relative to F16, the memory it needs with context headroom, and whether it fits. The best quant that fits is highlighted, each row carries a note on the quality trade-off, and a key explains what the letters in the names mean.
Sizes use measured bits-per-weight averages rather than the number in the name, because k-quants mix precisions between tensors: Q4_K_M averages about 4.8 bits, not 4. That is why the estimates line up with the files you actually download.
Key features of the Quantization Size Calculator
Measured bits per weight
Q4_K_M is sized at about 4.8 bits, matching the files you actually download.
Best fit highlighted
The highest-quality quant that fits your memory is marked in green.
Context headroom
Choose a little, some or plenty of room for context on top of the weights.
Quality note per quant
Each level explains its trade-off, from lossless Q8_0 to heavily degraded Q2_K.
Naming explained
A key to K, S, M, L, IQ and legacy _0 and _1 suffixes.
How to use the Quantization Size Calculator
-
1
Choose a model
Pick a model or type its parameter count in billions.
-
2
Choose your memory
Select a GPU or Mac, or type the usable memory in gigabytes.
-
3
Set the context headroom
More headroom for long documents, less for short chats.
-
4
Download the highlighted quant
The highest quality that fits is marked in green.
Frequently asked questions
Q4_K_M is the usual default and the best balance of size and quality. Use Q5_K_M or Q6_K if you have the memory, and only drop below four bits to fit a model that would not otherwise run.
Q4 is roughly four bits per weight, K means the k-quant method that mixes precisions between tensors, and M is the medium variant that keeps more tensors at higher precision than S.
Q8_0 is effectively lossless and Q6_K is very close. Q4_K_M loses a small amount that is rarely noticeable in chat. Below about 3.5 bits the degradation becomes clear.
Often a larger model at Q4 beats a smaller one at higher precision, but below three bits the larger model usually loses that advantage.
Importance-matrix quantizations, calibrated on sample text so the weights that matter most keep more precision. They are noticeably better than standard quants at very low bit widths.
Reviews of the Quantization Size Calculator
What people who use the Quantization Size Calculator think of it. Reviews come from visitors and are posted as written.
No ratings yet
Yours would be the first.
- 5 0 reviews rated 5 stars
- 4 0 reviews rated 4 stars
- 3 0 reviews rated 3 stars
- 2 0 reviews rated 2 stars
- 1 0 reviews rated 1 star
0 reviews
Newest first
No reviews yet
Be the first to rate the Quantization Size Calculator. It takes half a minute and no account.
Write the first reviewMore AI tools
JSONL Validator
Validate a JSONL file line by line, and check fine-tuning datasets before you upload.
Function Schema Generator
Write valid tool-calling JSON schemas without hand-editing braces.
GPU VRAM Calculator for LLMs
Work out how much GPU memory a local LLM needs to run or fine-tune.
Negative Prompt Generator
Build a Stable Diffusion negative prompt from the problems you keep getting.
Chat Transcript Formatter
Clean up a pasted chat log into a tidy transcript, Q&A pairs, JSON or CSV.
Embedding Cost Calculator
Estimate the cost and vector storage of embedding a document corpus for RAG.
AI Image Size Calculator
Find the right resolution for SDXL, FLUX, DALL-E or Midjourney at any aspect ratio.