AI computing for fast model inference

Inference is different from training: utilization, batch size, latency targets and model memory footprint often matter more than raw training throughput. The right AI Computer can cut serving cost without over-provisioning.

COMMON WORKLOADS

Where AI Computer acceleration can help

  • LLM inference endpoints
  • Vision model serving
  • Batch inference
  • Low-latency AI APIs
  • Video and generative workloads
START IN ONE CLICK

Ready-made notebooks for this

Shared by the ComputeBD team. Open one, change it to fit your work, then run it on an AI Computer — billed by the minute.

📓 Ready notebook

Bangla text-to-speech (Indic Parler-TTS)

বাংলা টেক্সট-টু-স্পিচ (Indic Parler-TTS)

Turn Bangla text into natural speech with described voices — with a clear consent-first voice-cloning policy.

Open this notebook ↗Read the short write-up →
📓 Ready notebook

Ask questions of match & talk-show transcripts (RAG)

ম্যাচ ও টক-শোর ট্রান্সক্রিপ্টে প্রশ্ন (RAG)

Search transcripts by meaning and get Bangla answers that cite the minute they were said.

Open this notebook ↗Read the short write-up →
RECOMMENDED AI COMPUTER CLASSES
NVIDIA A10 GPU chip render

NVIDIA A10

৳196*/hr
Ampere24 GBPCIe

Rendering, vision, medium training workloads

Tell us your workload and preferred AI Computer.

Join waitlist ↗
FREE TOOLS

Plan it before you start