The QUASAR 192-Core Arm Agentic Inference Server is a power-efficient Arm server built for high-concurrency agentic inference \u2014 a 192-core AmpereOne CPU that runs large fleets of AI agents, orchestration, RAG retrieval and quantised small-model inference at scale, without a GPU for every workload. It brings agent fleets in-house on energy-efficient cores, on-premises, in INR, on a GST invoice \u2014 and is GPU-ready when you need acceleration.<\/p>\n
Engineered for platform teams running many concurrent agents and RAG pipelines, it pairs 192 Arm cores with 768 GB of memory and fast NVMe, delivering high throughput-per-watt for orchestration-heavy and concurrency-bound agentic workloads \u2014 with PCIe slots to add GPUs for accelerated inference.<\/p>\n
This sits at the agent-fleet serving<\/strong> stage: the efficient node that runs orchestration, retrieval and high-concurrency agents. With 192 Arm cores and 768 GB of memory, it is sized to sustain<\/strong> large agent fleets at high throughput-per-watt \u2014 complementing GPU servers that handle the model-heavy inference.<\/p>\n We don’t publish inflated peak numbers. The honest picture: 192 Arm cores and 768 GB are sized for high-concurrency agent fleets, orchestration and retrieval, with optional GPUs for accelerated inference. Want certainty? Request a free benchmark of your agents and request mix on this exact configuration before you buy<\/strong>; we’ll send back real concurrency, throughput-per-watt and latency.<\/p>\n For sustained agent fleets, an efficient Arm server lowers both per-token API cost and per-agent power cost: you own the capacity, with no egress and full data residency. RDP pricing is fixed in INR with a GST input-credit-eligible invoice \u2014 ask for a cost-per-agent and throughput-per-watt comparison<\/strong>.<\/p>\n Ships ready to serve agents<\/strong>: the Arm Linux stack, Docker, with vLLM \/ llama.cpp (Arm-optimised), a vector DB and popular agent frameworks pre-configured on Ubuntu LTS for Arm. Optional managed agent-serving stack and observability.<\/p>\n A 2U air-cooled node with redundant PSUs and high performance-per-watt \u2014 specify rack power and cooling. (Exact PSU rating, BTU and airflow figures confirmed on the build sheet.)<\/em> BMC\/IPMI provides remote power, console and health monitoring.<\/p>\n 14 years of Make-in-India infrastructure and 300,000+ devices shipped<\/strong>. Indian OEM, INR pricing, GST tax invoice (HSN 8471), pan-India onsite engineers, GeM availability, and DPDP \/ sovereign-AI-ready deployment.<\/p>\n This is an efficient Arm agentic inference server, made to order \u2014 talk to an RDP solution architect<\/strong>, size the CPU\/GPU split for your agents, and benchmark your own workload on it before you commit.<\/strong> Request a quote to begin.<\/p>\n","protected":false},"excerpt":{"rendered":" AmpereOne 192-core Arm \u00b7 768 GB DDR5 ECC \u00b7 8 TB NVMe \u00b7 Rack 2U \u00b7 GPU-ready<\/p>\n","protected":false},"featured_media":2130,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"QUASAR 192-Core Arm Agentic Inference Server \u2014 192-core AmpereOne Arm, 768 GB, GPU-ready | RDP GPU Mart","rank_math_description":"Power-efficient Arm agentic inference server \u2014 192-core AmpereOne, 768 GB DDR5, GPU-ready. Run large fleets of AI agents and RAG at high throughput-per-watt on-prem. Make-in-India, GST invoice. Request a quote.","_hermes_jsonld":""},"product_brand":[],"product_cat":[22],"product_tag":[],"class_list":["post-1835","product","type-product","status-publish","has-post-thumbnail","product_cat-agentic-ai-pcs-edge-ai","pa_form-factor-rack","pa_series-quasar","pa_use-case-agentic-ai","pa_use-case-generative-ai","pa_use-case-inference","pa_use-case-nlp-speech","pa_use-case-rag","pa_workload-fit-arm-agentic-inference-cpu-forward-gpu-ready","first","instock","taxable","shipping-taxable","product-type-external"],"_links":{"self":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product\/1835","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/comments?post=1835"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media\/2130"}],"wp:attachment":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media?parent=1835"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_brand?post=1835"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_cat?post=1835"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_tag?post=1835"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Industry use cases<\/h3>\n
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Performance \u2014 and how to be sure<\/h3>\n
Series & upgrade path<\/h3>\n
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On-prem vs cloud \u2014 the TCO case<\/h3>\n
Software & day-one readiness<\/h3>\n
Power, cooling & rack integration<\/h3>\n
Deployment, warranty & support<\/h3>\n
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Why RDP<\/h3>\n
Buy with confidence<\/h3>\n