Inference accelerator for modern workloads
RNGD is presented as FuriosaAI’s flagship accelerator for enterprise and cloud inference, with support for LLM and multimodal deployment.
AI accelerators and servers for enterprise inference workloads
FuriosaAI designs AI accelerators for data-center inference, with RNGD as its flagship product and the NXT RNGD Server as a packaged deployment option. The company frames the hardware around high-performance, power-efficient execution for computer vision, generative AI, LLMs, and agentic workloads.
The product family centers on Tensor Contraction Processor architecture, which FuriosaAI describes as a hardware-software approach optimized for tensor contraction. The site emphasizes deployment in enterprise and cloud settings, including air-cooled data centers, on-premises installations, managed environments, and colocation facilities, supported by a software stack for compilation, optimization, and production rollout.
RNGD is presented as FuriosaAI’s flagship accelerator for enterprise and cloud inference, with support for LLM and multimodal deployment.
The platform uses Tensor Contraction Processor architecture, which FuriosaAI says is built around tensor contraction rather than fixed matmul primitives.
RNGD is described with a 180W power profile and the NXT RNGD Server with a 3 kW power consumption target for air-cooled data centers.
Furiosa Software provides compilation, optimization, and production deployment workflows for LLM inference and agentic workloads.
Furiosa provides compilation, quantization, runtime execution, and LLM serving tools, including torch.compile integration, vLLM-compatible interfaces, an OpenAI-compatible API server, container support, and Kubernetes plugins.
RNGD supports BF16, FP8, INT8, and INT4 arithmetic. Its specifications list SR-IOV with up to eight virtual instances, ECC memory, and secure boot with a hardware root of trust. Hardware arithmetic support does not mean every quantization mode is available in every SDK version.
Run high-throughput LLM inference in data centers where power density and rack utilization matter, using RNGD or the NXT RNGD Server as the deployment target.
Deploy multimodal models in cloud or enterprise environments where the site highlights low-latency execution and production-ready software support.
Evaluate, integrate, and qualify accelerators through the Furiosa Access Program before moving to production deployment.
Package inference into an air-cooled appliance for on-premises, managed, or colocation environments using the NXT RNGD Server.
Use the Furiosa software stack to compile, optimize, and ship models with PyTorch 2.x and cloud-native tooling.
FuriosaAI positions RNGD as an AI accelerator for enterprise and cloud inference. The source describes it as supporting high-performance LLM and multimodal deployment capabilities, and the NXT RNGD Server as a 3 kW inference appliance for agentic systems.
Furiosa provides compilation, quantization, runtime execution, and LLM serving tools, including torch.compile integration, vLLM-compatible interfaces, an OpenAI-compatible API server, container support, and Kubernetes plugins.
Teams worldwide can request a dedicated NXT RNGD bare-metal server or an OpenAI-compatible API endpoint to evaluate performance, latency, power, and application compatibility. Access requires a request; it is not an unrestricted free plan.
Prices are not publicly listed. Contact FuriosaAI for a hardware configuration and quote.
Traffic data is for reference only.
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