FuriosaAI's newly launched NXT RNGD server could change the economics of enterprise AI deployments, delivering high-performance inference while using far less energy than the market's most expensive GPU systems, according to the company.
Global power demand from data centers is projected to climb 50% by 2027 and as much as 165% by 2030, driven largely by artificial intelligence workloads, according to Goldman Sachs (NYSE: GS).
Furiosa NXT RNGD Cuts Power Use by 70% Against Nvidia's DGX H100
FuriosaAI said the NXT RNGD – pronounced "Renegade" – server consumes just 3 kilowatts of power, compared to more than 10 kilowatts for an Nvidia (NASDAQ: NVDA) DGX H100 server. A typical 15-kilowatt data center rack could hold up to five RNGD servers, compared to a single DGX H100.
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The company said this efficiency allows businesses to scale large models inside existing facilities without investing in costly infrastructure upgrades.
The server delivers 4 petaFLOPS of compute performance in a standard rack-sized unit powered by eight RNGD cards. Each card is based on Furiosa's Tensor Contraction Processor architecture, designed specifically for AI inference workloads rather than graphics processing.
LG AI Research Reports 2.25 Times Efficiency Gains Using Furiosa Hardware
LG AI Research adopted RNGD hardware for inference on its EXAONE family of large language models in July. According to FuriosaAI, LG found RNGD delivered "2.25x better LLM inference performance vs. GPUs" while also meeting demanding latency and throughput requirements.
The agreement with LG AI Research expands the deployment of RNGD servers across industries, including electronics, telecommunications, finance, and biotechnology. FuriosaAI said this validation demonstrates the system's ability to deliver measurable savings while keeping pace with performance benchmarks.
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OpenAI Runs GPT-OS-120b On Just Two RNGD Cards
Earlier this month, FuriosaAI partnered with OpenAI to showcase its gpt-oss-120b model running on just two RNGD cards. The demonstration used MXFP4 precision and highlighted RNGD's ability to support new open-weight large language models with fewer resources.
The company said this proof-of-concept illustrates how enterprises can run advanced reasoning and generative models at scale without needing massive GPU clusters. By consuming less energy and fitting inside standard racks, FuriosaAI said the RNGD server helps customers manage both performance and cost constraints.
RNGD Software Stack Expands to Meet Enterprise AI Demands
Alongside the hardware launch, FuriosaAI released updates to its software development kit, versions 2025.3 and 2025.3.1. The company said the new SDK introduces inter-chip tensor parallelism, advanced compiler optimizations, improved runtime synchronization, and support for models such as Qwen 2 and Qwen 2.5.
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FuriosaAI added that expanded quantization formats and Hugging Face Hub integration make RNGD servers compatible with a broad range of enterprise use cases. The SDK is designed as a drop-in replacement for existing inference frameworks, offering customers flexibility while reducing vendor lock-in.
Furiosa Targets Early 2026 for RNGD Server Rollout
FuriosaAI said the NXT RNGD server is currently sampling with enterprise customers worldwide. The system is expected to be available for order in early 2026.
By reducing energy costs, enabling data sovereignty, and offering compatibility with widely used inference frameworks, FuriosaAI said the RNGD server is positioned as an alternative for enterprises struggling with the costs of GPU-based AI deployments.
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