Up to 2× more users on the same GPUs. Measured.
BTB Micro is the input-efficiency layer of the BTB inference system, for organisations that serve AI on their own GPUs. Under production load, the same GPU serves up to twice as many concurrent users at the same latency target, with answer quality held at parity under blinded judging.
The measured result
more concurrent users per GPU at the same latency target
median gain across five open models; best case 2.37×
same answer quality, held at parity in blinded judging
Measured by BTB Intelligence on NVIDIA B200 against a tuned vLLM setup, across five open models: the same model and serving configuration, with and without the layer. The gain depends on load — lightly loaded GPUs gain little. These are our measurements; the gain on other systems depends on their hardware and traffic.
How it deploys
- Once deployed, it runs on your infrastructure — your traffic and data stay in your environment.
- It works alongside the models and serving stack you already run. No retraining.
- It combines with the other layers of the BTB inference system.
- The method is not disclosed; a patent application is in preparation.
Talk to us about your inference
If you run LLM inference on NVIDIA GPUs and want to know what this could mean for your workload, write to us — we answer personally.
Email: info@btbintelligence.com
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