Firmus
Firmus provides GPU-first AI cloud infrastructure across Asia-Pacific, combining on-demand and reserved GPU clusters, bare metal, and S3-compatible WEKA storage. Its modular AI Factories deliver high-density performance with lower power and water, backed by MLPerf-validated systems and sovereign deployment options.
Overview
Choose a region, select a GPU SKU and capacity, attach S3-compatible WEKA volumes, and launch training or fine-tuning jobs. Scale horizontally by adding nodes; vertically by reserving larger GPU pools. Telemetry tracks performance, energy, and thermals to right-size runs and control cost.
Capabilities and Architecture
Ideal for AI‑native companies training or adapting large models, enterprises consolidating fragmented GPU estates, research labs validating experiments at scale, and public‑sector teams requiring data residency. Typical workloads include LLM training and LoRA fine‑tuning, vision and multimodal pretraining, recommender systems, and high‑performance inference serving with predictable latency. Teams operating across multiple sites benefit from sovereign regions and consistent hardware, easing reproducibility, compliance reviews, and long‑term capacity planning.
- GPU clusters with Blackwell, H200, and L40S options for training, tuning, and inference.
- Liquid-cooled AI Factories reduce power, water, and space while sustaining dense performance.
- MLPerf Training and Power results validate efficiency and throughput across representative models.
- On-demand instances and reservations provide predictable scale across Singapore and Australia regions.
- S3-compatible WEKA storage delivers high-throughput data pipelines, checkpoints, and artifact management.
Key Highlights
Who Should Use Firmus
Begin by submitting an enquiry to confirm region, GPU type, and capacity reservations. After onboarding, provision clusters via the portal; attach S3‑compatible storage; and import datasets, containers, and checkpoints. Teams commonly schedule jobs with their preferred frameworks and orchestrators; programmatic access is available through the account team when required. Performance and energy telemetry help tune batch sizes, parallelism, and placement, while support assists with benchmarking, runbooks, and cost planning. Implementation typically includes security reviews, workload migration planning, and SLAs for capacity, availability, and response, with optional multi‑site designs for resilience and data residency.
Build compute where efficiency and transparency compound: measure, publish, and scale the system, not just square footage.
Getting Started
Firmus turns AI infrastructure into an engineered product: modular, efficient, and transparently benchmarked. Customers gain predictable training throughput, sovereign deployment choices, and storage that matches GPU scale—without overprovisioning traditional data‑center overhead. If you need fast scale, clear performance evidence, and lower resource intensity, Firmus fits. The focus on liquid cooling, end‑to‑end networking, and silicon‑aware operations often improves utilization and reduces queue times, turning capacity planning into a repeatable, measurable process for model teams and platform operators.
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Firmus
Firmus Technologies builds GPU-centric cloud infrastructure and modular AI Factories across Asia‑Pacific. The team combines data‑center engineering, HPC networking, and AI systems research to deliver high‑density, energy‑efficient deployments. Results published through MLPerf and real‑world case studies underscore a focus on measurable performance, sustainability, and sovereign regional access.
Firmus is a GPU-powered AI cloud provider building modular, energy‑efficient “AI Factories” across Asia‑Pacific. Workloads run on reserved or on‑demand GPU clusters—Blackwell GB300, H200 HGX, and L40S—interconnected with NVSwitch and full‑rail InfiniBand, with BlueField DPUs for offload. S3‑compatible WEKA storage supplies high‑throughput datasets, checkpoints, and artifacts. Architected as compute‑scale systems rather than traditional data centers, deployments emphasize liquid cooling, dense power delivery, and silicon‑aware orchestration to maximize performance per watt. Firmus publishes MLPerf Training and Power results to validate system efficiency and throughput. Customers adopt the platform for large‑scale training, fine‑tuning, and high‑performance inference, with sovereign options across Singapore and Australia, including Project Southgate. The result is predictable, scalable capacity that reduces time‑to‑production and total cost while improving sustainability. Operational transparency includes real‑time energy and thermal telemetry to inform planning and governance.
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