LLM Quantization Services for Your Business
LLM quantization services convert a full-precision FP16 model into a compact format such as GGUF or AWQ, so it runs on smaller GPUs, laptops or edge devices. Omeiro picks bit levels, runs the conversion and tests that quality holds up on your tasks.
How LLM quantization works, step by step
A made-up example of one run, from start to finish. Each step is logged so you can see what happened.
- Something happens
A form, an email, a payment or a new row.
- The workflow runs
Steps you agreed, in the right order.
- Errors are caught
Failed steps retry or alert a person.
- You see what ran
A simple log of every run.
Sample Made-up names, data and steps to show how a run is logged. Your steps, tools and rules follow your business.
What you get with LLM quantization
Post-training quantization converting full FP16 models to AWQ and GGUF formats. Enabling high-speed local inference on edge hardware and commodity GPU instances with zero accuracy loss.
Basic Package
1 model quantized to GGUF or AWQ, 1 bit-level, test run. 2-day delivery, 1 round + 30-day fixes.
Standard Package
Up to 3 formats/bit-levels, accuracy; speed benchmark. 4-day delivery, 1 round + 30-day fixes.
Premium Package
Up to 3 models, edge/GPU serving setup, benchmark report, 30 days support. 7-day delivery, 1 round + 60-day fixes.
Clear brief first
We confirm what you need before work starts, so the scope is clear on both sides.
Revisions listed
Each package shows its revision rounds. A round is one list of changes sent together.
Yours once paid
Copyright of the final work passes to you once the order is paid in full.
Third-party tools, API usage and hosting are billed to your own accounts, so the setup stays with your business.
How our LLM quantization works
Pick the target
We agree the hardware, memory limit and format you need.
Convert
The model is quantized at the chosen bit levels.
Benchmark
Accuracy and speed are compared with the original.
Serve
Higher tiers add a serving setup for your edge device or GPU.
LLM quantization: matching bit level to hardware and task
Bit level is a trade-off you can measure. Lower precision shrinks memory use and speeds inference, but quality can slip, particularly on reasoning, code and non-English text. LLM quantization therefore starts from your hardware limit, then tests candidate levels on your actual prompts instead of generic scores. Before ordering, state your memory budget, target speed and the model you want to compress, along with a set of typical questions for testing.
Format follows runtime. GGUF is designed for llama.cpp-style runtimes that run on CPUs and mixed hardware, while AWQ suits GPU serving stacks, so the choice depends on where the model will live. LLM quantization also touches licences, since some models restrict redistribution of converted files. Keep the original weights, version every converted file and record the benchmark results next to it, so you can reverse the decision if quality turns out lower than expected.
In short
- Delivery in 2 to 7 days, by package.
- Fixed price, shown before you order.
- Teams who cannot afford a large GPU for each model they host.
- Developers asking for gguf model conversion to run a model with llama.cpp or Ollama.
- Copyright yours after full payment.
LLM Quantization: common questions
How much does LLM quantization cost?
Prices are fixed and shown by package on our LLM Quantization pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does gguf model conversion take?
Delivery depends on the package: Basic 2-day delivery; Standard 4-day delivery; Premium 7-day delivery.
What is included in the Basic Package?
The Basic Package includes: 1 model quantized to GGUF or AWQ, 1 bit-level, test run. Higher packages add more scope, revisions and support.
Can I get a custom awq quantization consulting package?
Yes. If none of the packages fits, use the custom package form on our pricing page to describe what you need, and our team sends you a fixed price.
Will quantization reduce quality?
Usually a little, and more at lower bit levels. That is why benchmarks are included from Standard.
GGUF or AWQ?
GGUF is common for CPU and local tools. AWQ suits GPU serving.
Can you quantize any model?
Most popular open models. Name yours before ordering.
What do I receive?
The converted model files and the test results for your tier.
What do 4-bit and 8-bit mean for a language model?
They describe how many bits store each weight. Fewer bits mean a smaller, faster model but usually a little less accuracy, so the level is chosen by testing.
Who owns the final work?
Copyright of the final work passes to you once the order is paid in full. Paid fonts, stock files or licences, if used, are licensed in your name.
Ready to start your LLM quantization?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.