LLM Inference Optimization Services for Your Business
TensorRT LLM optimization compiles your model into an engine tuned for NVIDIA GPUs, so each token arrives faster and each GPU serves more users. Omeiro builds the engine, applies in-flight batching and FP8 or INT8 precision, and serves it through Triton.
How LLM inference optimization 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 inference optimization
Ultra-low latency kernel compilation via NVIDIA TensorRT-LLM. In-flight batching, FP8 precision execution, and custom CUDA optimization on H100 and A100 GPU clusters.
Basic Package
TensorRT-LLM engine build for 1 model, latency benchmark. 7-day delivery, 1 round + 30-day fixes.
Standard Package
FP8/INT8 tuning, in-flight batching, Triton server setup. 12-day delivery, 1 round + 30-day fixes.
Premium Package
Up to 3 models, multi-GPU H100/A100, CI rebuilds, 30 days support. 20-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 inference optimization works
Baseline
We time your current serving.
Compile
The model is converted into a TensorRT-LLM engine.
Tune precision
FP8 or INT8 is tried, checking quality.
Serve
Triton is configured and benchmarked.
TensorRT LLM optimization: what changes, and what to expect
Engines are built for a specific model, GPU type and set of settings. TensorRT LLM optimization therefore starts with the exact model version, precision target, maximum batch size and sequence length you expect, because the engine is compiled around them. Before ordering, tell us the GPUs, driver and CUDA environment, plus the latency or throughput target. A change of model or hardware later means a rebuild, which is why CI rebuilds exist on Premium.
Precision is the quality trade-off. FP8 and INT8 reduce memory and speed up generation, but outputs can change slightly, so TensorRT LLM optimization should be validated on your own prompts, not only on benchmark averages. In-flight batching raises throughput by mixing requests at different stages, which helps when users arrive constantly. Keep the original serving setup available for comparison, and agree acceptance numbers in advance so the benchmark gives a clear pass or fail.
In short
- Delivery in 7 to 20 days, by package.
- Fixed price, shown before you order.
- Teams on H100 or A100 hardware who need lower latency.
- Engineers considering nvidia llm inference acceleration for a production model.
- Copyright yours after full payment.
LLM Inference Optimization: common questions
How much does LLM inference optimization cost?
Prices are fixed and shown by package on our LLM Inference Optimization pricing page, so you see the full price before you order. You can also ask for a custom quote.
How much does LLM inference optimization cost?
Prices are fixed and shown by package on our LLM Inference Optimization pricing page, so you see the full price before you order. You can also ask for a custom quote.
How long does nvidia LLM inference acceleration take?
Delivery depends on the package: Basic 7-day delivery; Standard 12-day delivery; Premium 20-day delivery.
What is included in the Basic Package?
The Basic Package includes: TensorRT-LLM engine build for 1 model, latency benchmark. Higher packages add more scope, revisions and support.
Can I get a custom low latency LLM serving 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.
TensorRT-LLM or vLLM?
TensorRT-LLM can be faster on NVIDIA hardware but is more work to build and rebuild. vLLM is simpler to run.
Does lower precision hurt quality?
Sometimes slightly, so we test it.
Do I need NVIDIA GPUs?
Yes.
What are CI rebuilds?
Automatic engine rebuilds when the model changes. Premium includes them.
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 inference optimization?
Compare the packages and pick the one that fits. Not sure which? Write to us and we will help you choose.