{"id":15284,"date":"2026-08-28T01:27:58","date_gmt":"2026-08-28T01:27:58","guid":{"rendered":"https:\/\/rdp.in\/gpu-mart\/product\/quasar-ryzen-ai-max-2l-liquid-cooled-ai-pc\/"},"modified":"2026-08-30T15:13:58","modified_gmt":"2026-08-30T15:13:58","slug":"quasar-ryzen-ai-max-2l-liquid-cooled-ai-pc","status":"publish","type":"product","link":"https:\/\/rdp.in\/gpu-mart\/product\/quasar-ryzen-ai-max-2l-liquid-cooled-ai-pc\/","title":{"rendered":"QUASAR Ryzen AI Max 2L Liquid-Cooled AI PC"},"content":{"rendered":"

Cooling is what protects throughput.<\/strong> This 2 L unit carries twin liquid-cooling radiator fans<\/strong> and runs the Ryzen AI Max+ 395 at a 147 W<\/strong> envelope — the highest in the family. Independent validation work on AI hardware keeps finding the same thing: parts that pass every health test still lose double-digit throughput to thermal throttling under sustained load. This is the configuration engineered so that does not happen.<\/p>\n

Key highlights<\/h3>\n
    \n
  • 147 W sustained envelope<\/strong> \u2014 the highest-performance Strix Halo configuration in the line.<\/li>\n
  • Twin liquid-cooling radiator fans<\/strong> \u2014 engineered for sustained load, not burst.<\/li>\n
  • Up to 128 GB LPDDR5X-8000<\/strong>, 256-bit, up to 96 GB assignable to graphics.<\/li>\n
  • 16C \/ 32T<\/strong> Ryzen AI Max+ 395 with 40-CU Radeon 8060S and 50 TOPS NPU.<\/li>\n
  • Holds clocks through multi-hour inference and adapter-training runs.<\/li>\n
  • 2 L desktop chassis<\/strong> \u2014 the thermal design, not the size, is what changed.<\/li>\n
  • Windows 11 or Ubuntu, imaged and bench-validated by RDP before dispatch.<\/li>\n<\/ul>\n

    AI workload fit<\/h3>\n
      \n
    • Multi-hour sustained inference<\/strong> without throttling.<\/li>\n
    • Fine-tuning<\/strong> and LoRA\/QLoRA adapter training on small to mid models.<\/li>\n
    • Continuous agentic AI<\/strong> workloads that run unattended.<\/li>\n
    • RAG<\/strong> and generative AI<\/strong> production work on-premises.<\/li>\n
    • NLP & speech<\/strong> pipelines processing long-running batches.<\/li>\n
    • A shared team machine that several people queue work onto.<\/li>\n<\/ul>\n

      AI workload positioning<\/h3>\n

      Same silicon as the CARINA units, different engineering brief. The extra 15–27 W of envelope matters less than the cooling headroom behind it<\/strong>: throughput measured in the first minute is not what you get in the second hour unless the thermal design supports it. This remains an inference and light-fine-tuning platform — a liquid loop does not turn an integrated GPU into a training accelerator, and we will not imply that it does.<\/p>\n

      Industry use cases<\/h3>\n
        \n
      • Enterprise & GCCs:<\/strong> a shared team AI machine running continuous workloads.<\/li>\n
      • BFSI:<\/strong> sustained batch inference over regulated data on-premises.<\/li>\n
      • Healthcare:<\/strong> long-running clinical document and imaging pipelines.<\/li>\n
      • Public sector & sovereign:<\/strong> departmental AI capacity with on-soil residency.<\/li>\n
      • Research & education:<\/strong> a lab workhorse shared across a research group.<\/li>\n<\/ul>\n

        Performance & how to be sure<\/h3>\n

        Ask for the sustained<\/strong> figure, never the peak \u2014 the useful measurement is throughput in the last window of a long run against the first, and RDP reports the droop rather than the headline. Rather than quote a tokens\/sec figure that will not match your workload, RDP offers a “benchmark your model”<\/strong> session: bring the model, precision and context length you actually intend to run, and we will validate it on this exact configuration before you commit.<\/p>\n

        Series & upgrade path<\/h3>\n

        QUASAR<\/strong> performance tier. Below: the CARINA 1L and 2L<\/strong> units for lighter, quieter duty. Above: the 4L Desktop Workstation<\/strong> with an internal 350 W PSU, then RDP AI Workstations with discrete RTX PRO GPUs when fine-tuning throughput \u2014 not memory capacity \u2014 becomes the constraint.<\/p>\n

        On-prem vs cloud (TCO)<\/h3>\n

        For sustained daily AI work this configuration removes per-GPU-hour billing, queueing for scarce instances, and egress charges on your own data — and keeps everything on-premises for DPDP and data-residency obligations. Cloud still wins for burst capacity and one-off very large training runs; on-prem wins on sustained utilisation, control and predictable INR capital cost. We model the crossover with your actual usage rather than assert it.<\/p>\n

        Software & day-one readiness<\/h3>\n

        Ships with Windows 11<\/strong> or Ubuntu, and the AMD AI stack \u2014 ROCm<\/strong>, DirectML and ONNX Runtime \u2014 with local model runtimes (LM Studio, Ollama, llama.cpp) validated before dispatch. Because the GPU draws from the same unified pool as the CPU, you assign memory to the model rather than shopping for a card with enough VRAM. Migration from a CUDA workflow is a real exercise and RDP scopes it honestly rather than calling it a drop-in swap.<\/p>\n

        Power, thermal & acoustics<\/h3>\n

        147 W platform envelope with a closed liquid loop and twin radiator fans, on a standard socket. Quieter under sustained load than an air-cooled unit at the same power, because the fans are not the primary heat path. Exact wattage, BTU and dB(A) figures come from RDP bench measurement rather than estimates — ask for the site-readiness sheet with your quote.<\/em><\/p>\n

        Deployment, warranty & support<\/h3>\n

        Built to order by RDP Technologies. Supplied with GST invoice, pan-India onsite support, and availability through GeM for public-sector procurement. Built to order \u2014 this configuration is in final engineering; confirmed at quotation.<\/p>\n

        Why RDP<\/h3>\n

        RDP Technologies is a Make-in-India OEM with 14+ years and 300,000+ units shipped, supplying AI infrastructure from desk-side systems to rack-scale AI factories — with predictable INR pricing, GST invoicing and pan-India onsite service.<\/p>\n

        Buy with confidence<\/h3>\n

        Use Request a Quote<\/strong> to reach an RDP solution architect for sizing, a benchmark-your-model session, financing options and a delivery plan. No obligation.<\/p>\n","protected":false},"excerpt":{"rendered":"

        Ryzen AI Max+ 395 \u00b7 147W liquid-cooled \u00b7 up to 128GB unified \u00b7 2L<\/p>\n","protected":false},"featured_media":1007,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"QUASAR Ryzen AI Max 2L Liquid-Cooled AI PC | RDP GPU Mart","rank_math_description":"Liquid-cooled 2L Ryzen AI Max+ 395 AI PC at 147 W: up to 128 GB unified memory, sustained throughput without throttling. Request a quote from RDP.","_hermes_jsonld":""},"product_brand":[],"product_cat":[22],"product_tag":[],"class_list":["post-15284","product","type-product","status-publish","has-post-thumbnail","product_cat-agentic-ai-pcs-edge-ai","pa_form-factor-desktop","pa_gpu-model-amd-radeon-8060s","pa_industry-bfsi-hft","pa_industry-enterprise-gccs","pa_industry-healthcare-life-sciences","pa_industry-public-sector-sovereign-ai","pa_industry-research-higher-education","pa_series-quasar","pa_use-case-agentic-ai","pa_use-case-fine-tuning","pa_use-case-generative-ai","pa_use-case-inference","pa_use-case-nlp-speech","pa_use-case-rag","pa_workload-fit-sustained-desk-side-ai-inference","first","instock","taxable","shipping-taxable","product-type-external"],"_links":{"self":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product\/15284","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=15284"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media\/1007"}],"wp:attachment":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media?parent=15284"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_brand?post=15284"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_cat?post=15284"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_tag?post=15284"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}