Private LLM in SingaporeAnyone can drop a model on your server.

Yes. Open-weight models such as Qwen, Llama, DeepSeek, Gemma, GPT-OSS and Mistral run entirely inside your own network. Our own box, a 128 GB AMD Strix Halo mini PC, serves a 125B mixture-of-experts model with vision and a 131K-token context for our team. No data leaves the building and there is no per-token API bill.

On-prem removes the hardest PDPA risks, cross-border transfer and third-party processing, because data never leaves your environment. It is not automatically compliant on its own: you still need access control, audit trails and governance, which we build in. No serious vendor should claim 'fully PDPA-compliant' out of the box.

On our own AMD Strix Halo box, Qwen3.8-Flash-Next (125B parameters, 6B active per token, with vision) reads prompts at about 1,050 tokens a second and writes at about 37 tokens a second on prose and 46 on code, measured on 9 Oct 2026. 32K tokens into a conversation it averaged about 29 tokens a second (three of four runs at 33 to 37, one at 11). Four requests sent at once all finished within about 12 seconds. That is interactive for chat, document extraction and agents.

The model and the way it is served, for your box. We pick the model and the quantization (how many bits each weight keeps) that fit your memory with room for long context, choose the serving engine, and tune multi-token prediction and the context cache. On our own box, changing the serving engine alone made prompt reading 3.0 to 4.3 times faster for the same model file. We measure every change on your hardware before we keep it.

For one team, a desk-sized box with 128 GB of unified memory: an AMD Strix Halo mini PC (Ryzen AI Max+ 395) from S$4,325 for value, an NVIDIA GB10 box such as the DGX Spark or ASUS Ascent GX10 from S$6,624 for the CUDA tooling, or an Apple Mac Studio with M5 Ultra from S$7,999 (96 GB as standard, up to 512 GB) for memory bandwidth and silence. Prices as read from each seller's own page on 9 Oct 2026. For many people at once you move to server GPUs.

Writing speed on these boxes is set mostly by memory bandwidth. On paper the AMD Strix Halo (about 256 GB/s) and the NVIDIA GB10 (273 GB/s) are within 7% of each other, while the Mac Studio M5 Ultra has about 1.2 TB/s, over four times either. The GB10's strengths are compute for long prompts and the mature CUDA stack (vLLM, TensorRT-LLM). Strix Halo is the cheapest 128 GB box. Pick on budget, software and noise; we then optimize the model for the box you chose.

When data cannot leave your perimeter (regulated data), when you sustain enough volume that per-token API costs outrun owning the hardware, or when you need predictable low latency. Below that, cloud APIs are usually cheaper and faster to start, and we will tell you which side of the line you are on.

Yes. We run a 125B mixture-of-experts model on one 128 GB box, as a 4-bit build. Mixture-of-experts models are the sweet spot for these boxes: large-model quality, but only a few billion parameters are active per token (6B for ours), so they stay fast on hardware that is limited by memory bandwidth.

A working proof of concept in two to three weeks and production use in eight to ten weeks is typical, longer if new hardware has to be bought first: hardware sizing, model selection and optimization, the inference gateway, governance and audit, then integration with your systems. We hand over a documented stack your team can run.

Qwen (including Qwen3.8-Flash-Next, which we run ourselves), Llama, DeepSeek, Google Gemma, GPT-OSS and Mistral families, plus OCR and vision models for document work. We match the model to your task, hardware and quality bar rather than defaulting to the biggest one.

Either. We advise on and size the hardware (Strix Halo, DGX Spark, Mac Studio, server GPUs), or deploy onto kit you already own or run in your own VPC. The whole stack, models, gateway and governance, runs inside your control; day-to-day operations stay with your team unless you want a managed retainer.

Every morning our Deneb engine reads each seller's own product page: Singapore resellers, Apple Singapore, and overseas stores such as GMKtec and Bosgame. Overseas prices are converted to SGD with 9% GST at import added; shipping is not included. This page re-reads that feed every six hours, so prices change without anyone editing the page. They are list prices on the day, not a quote.

Deneb is our setup agent for private LLMs. It lives on your box, reads the logs, diagnoses problems and applies fixes only with your say-so, with a human engineer behind it. The client is open source, read-only by default, and never runs anything destructive or privileged. On the web, Deneb also answers whether on-prem AI fits your business and what it costs.