{"product_id":"k-node-h200-8x-sxm5-1128gb","title":"Kentino AI Node H200 — 8× NVIDIA H200 SXM5, 1,128 GB HBM3e","description":"\u003cdiv style=\"font-family: -apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,sans-serif; line-height: 1.7; color: #1a1a1a;\"\u003e\n\u003c!-- IMAGE PLACEHOLDER 1: 8U node front, white background --\u003e \u003c!-- IMAGE PLACEHOLDER 2: HGX H200 baseboard, 8 SXM5 modules + NVSwitch --\u003e \u003c!-- IMAGE PLACEHOLDER 3: rear showing redundant PSU bank and NIC slots --\u003e \u003c!-- IMAGE PLACEHOLDER 4: installed in rack, cable management visible --\u003e\n\u003cdiv style=\"background: linear-gradient(135deg,#0d0d0d 0%,#1a1a2e 100%); color: #fff; padding: 32px; border-radius: 12px; margin-bottom: 32px;\"\u003e\n\u003cp style=\"font-size: 18px; margin: 0 0 20px 0; color: #ccc;\"\u003eKentino AI Node H200\u003c\/p\u003e\n\u003cp style=\"font-size: 28px; font-weight: bold; margin: 0 0 16px 0; line-height: 1.3;\"\u003e1,128 GB HBM3e in One Chassis\u003cbr\u003e8x H200 SXM5 | NVSwitch | 15,832 INT8 TOPS\u003c\/p\u003e\n\u003cdiv style=\"display: flex; gap: 16px; flex-wrap: wrap; margin-top: 24px;\"\u003e\n\u003cdiv style=\"background: rgba(51,79,180,0.12); border: 1px solid #334fb4; border-radius: 8px; padding: 14px 16px; text-align: center; flex: 1; min-width: 110px;\"\u003e\n\u003cdiv style=\"font-size: 24px; font-weight: 800; color: #334fb4;\"\u003e1,128 GB\u003c\/div\u003e\n\u003cdiv style=\"font-size: 11px; color: #555; text-transform: uppercase; letter-spacing: 1px;\"\u003eHBM3e pool\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"background: rgba(51,79,180,0.12); border: 1px solid #334fb4; border-radius: 8px; padding: 14px 16px; text-align: center; flex: 1; min-width: 110px;\"\u003e\n\u003cdiv style=\"font-size: 24px; font-weight: 800; color: #334fb4;\"\u003e4.8 TB\/s\u003c\/div\u003e\n\u003cdiv style=\"font-size: 11px; color: #555; text-transform: uppercase; letter-spacing: 1px;\"\u003eper-GPU bandwidth\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"background: rgba(51,79,180,0.12); border: 1px solid #334fb4; border-radius: 8px; padding: 14px 16px; text-align: center; flex: 1; min-width: 110px;\"\u003e\n\u003cdiv style=\"font-size: 24px; font-weight: 800; color: #334fb4;\"\u003e900 GB\/s\u003c\/div\u003e\n\u003cdiv style=\"font-size: 11px; color: #555; text-transform: uppercase; letter-spacing: 1px;\"\u003eany-to-any NVLink\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"background: rgba(51,79,180,0.12); border: 1px solid #334fb4; border-radius: 8px; padding: 14px 16px; text-align: center; flex: 1; min-width: 110px;\"\u003e\n\u003cdiv style=\"font-size: 24px; font-weight: 800; color: #334fb4;\"\u003efp8\u003c\/div\u003e\n\u003cdiv style=\"font-size: 11px; color: #555; text-transform: uppercase; letter-spacing: 1px;\"\u003enative\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp style=\"margin-top: 20px; font-size: 15px; color: #aaa;\"\u003eThe tier where frontier models stop needing quantisation.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cp style=\"font-size: 17px; color: #333; margin-bottom: 24px;\"\u003eAn 8U node carrying eight NVIDIA H200 SXM5 modules on a single NVLink\/NVSwitch baseboard: 1,128 GB of HBM3e pooled at 4.8 TB\/s per GPU, with full any-to-any 900 GB\/s GPU-to-GPU bandwidth. Dual Intel Xeon Platinum processors, 2 TB of DDR5 system memory, U.2 NVMe boot and data tiers, and high-speed networking. This is a different class of machine from a PCIe multi-GPU build: because every GPU talks to every other GPU at full bandwidth, tensor parallelism scales close to linearly instead of degrading on dense models.\u003c\/p\u003e\n\u003ch2 style=\"font-size: 22px; font-weight: bold; margin: 40px 0 16px 0; padding-bottom: 8px; border-bottom: 3px solid #334fb4;\"\u003eHardware\u003c\/h2\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse; margin-bottom: 24px; font-size: 15px;\"\u003e\n\u003cthead\u003e\n\u003ctr style=\"background: #0d0d0d; color: #fff;\"\u003e\n\u003cth style=\"padding: 12px 16px; text-align: left;\"\u003eComponent\u003c\/th\u003e\n\u003cth style=\"padding: 12px 16px; text-align: left;\"\u003eDetail\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eGPUs\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e8x NVIDIA H200 SXM5 141 GB HBM3e (Hopper, 700 W per module)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eVRAM pool\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e1,128 GB HBM3e, NVSwitch-pooled - usable as one address space\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eMemory bandwidth\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e4.8 TB\/s per GPU\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eGPU interconnect\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003eNVLink 4 via 4x NVSwitch, 900 GB\/s any-to-any (not PCIe-limited)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eCompute\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e7,912 TFLOPS bf16 dense | 15,832 TFLOPS fp8 dense | 15,832 INT8 TOPS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eCPUs\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e2x Intel Xeon Platinum, dual-socket\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eSystem memory\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e2 TB DDR5\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eStorage\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e2x 1.92 TB U.2 NVMe boot + 2x 3.84 TB U.2 NVMe data. Expandable\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eNetworking\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e2x NVIDIA ConnectX-7. Up to 8x on request for multi-node InfiniBand fabric\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eChassis\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e8U rack-mount, front-to-back airflow, 24\/7 rated\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003ePower\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003eRedundant, up to 10.2 kW peak system draw\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch2 style=\"font-size: 22px; font-weight: bold; margin: 40px 0 16px 0; padding-bottom: 8px; border-bottom: 3px solid #334fb4;\"\u003eWhat it runs\u003c\/h2\u003e\n\u003cp\u003e1,128 GB is the point at which the largest open-weight models run at their native precision instead of being squeezed into a quantisation that costs you quality. Estimates below are for this 8-GPU configuration with tensor parallelism.\u003c\/p\u003e\n\u003ctable style=\"width: 100%; border-collapse: collapse; margin-bottom: 24px; font-size: 15px;\"\u003e\n\u003cthead\u003e\n\u003ctr style=\"background: #0d0d0d; color: #fff;\"\u003e\n\u003cth style=\"padding: 12px 16px; text-align: left;\"\u003eComponent\u003c\/th\u003e\n\u003cth style=\"padding: 12px 16px; text-align: left;\"\u003eDetail\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eDeepSeek-V3.2 \/ R1 671B\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003eNative fp8, full context. ~30-50 tok\/s single stream, 2,000+ tok\/s batched\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eKimi-K2 1T class\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003efp8 with room for KV cache - no 1.58-bit compromise needed\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eLlama 3.3 70B \/ Qwen3-72B\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003efp8. ~90-130 tok\/s single stream, 5,000+ tok\/s batched\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eQwen3-235B-A22B MoE\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003efp8 native with long-context headroom\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background: #f8f8f8;\"\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eLong-context serving\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e128k+ context with KV cache resident, not spilled\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding: 10px 16px; font-weight: 600;\"\u003eFull fine-tune 70B\u003c\/td\u003e\n\u003ctd style=\"padding: 10px 16px;\"\u003e8-way tensor parallel, no gradient offload\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"font-size: 14px; color: #666;\"\u003e\u003cem\u003eThroughput figures are estimates derived from published vendor specifications and community benchmarks for this GPU generation, not measurements taken on this exact configuration. We will give you measured numbers for your model and context length before you commit.\u003c\/em\u003e\u003c\/p\u003e\n\u003ch2 style=\"font-size: 22px; font-weight: bold; margin: 40px 0 16px 0; padding-bottom: 8px; border-bottom: 3px solid #334fb4;\"\u003ePower and cooling\u003c\/h2\u003e\n\u003cp\u003eUp to 10.2 kW peak system draw, the bulk of it the 8x 700 W GPU complex. In practice that means a dedicated three-phase feed per node and a rack budget planned around roughly one node per 12 kW. Air-cooled at this density needs real front-to-back airflow with a contained cold aisle below 24 C - perforated doors alone will not do it. A liquid-cooled baseboard variant is available and is the better answer above two nodes per rack; it needs a CDU and secondary loop, which we will scope with you rather than assume.\u003c\/p\u003e\n\u003ch2 style=\"font-size: 22px; font-weight: bold; margin: 40px 0 16px 0; padding-bottom: 8px; border-bottom: 3px solid #334fb4;\"\u003eExport control - read this before ordering\u003c\/h2\u003e\n\u003cp\u003eThe H200 is classified as an Advanced Computing Item (ECCN 3A090.a). Shipment requires a completed \u003cstrong\u003eKYC form\u003c\/strong\u003e and an \u003cstrong\u003eEnd User Certificate\u003c\/strong\u003e naming the end user, the installation address and the intended use. This is not optional and it is not something we can waive.\u003c\/p\u003e\n\u003cp\u003ePractically: budget several weeks for clearance on top of hardware lead time, and expect to name the legal entity that will own and operate the machine. If the end user cannot be named, this hardware cannot be supplied - by us or by anyone else in the EU.\u003c\/p\u003e\n\u003ch2 style=\"font-size: 22px; font-weight: bold; margin: 40px 0 16px 0; padding-bottom: 8px; border-bottom: 3px solid #334fb4;\"\u003eWhat you get from Kentino\u003c\/h2\u003e\n\u003cp\u003eKentino supplies, configures and supports this node as a complete deployment: rack and power design against your site's actual feed, front-to-back airflow sizing for 24\/7 operation, OS and driver stack (Ubuntu with pinned NVIDIA driver, CUDA, container toolkit), the inference or training stack of your choice, burn-in with a written report, EU-based logistics and warranty.\u003c\/p\u003e\n\u003cp\u003eWe also handle the export paperwork with you rather than mailing you a form and hoping. That part takes longer than the hardware and is where most first-time buyers of this class of machine get stuck.\u003c\/p\u003e\n\u003cp style=\"font-size: 14px; color: #666;\"\u003e\u003cem\u003ePrice shown is EUR excluding VAT, \u003cstrong\u003eEXW Prague\u003c\/strong\u003e (Incoterms 2020). Collection, freight, insurance and any destination import duties are for the buyer’s account. Lead time on request.\u003c\/em\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cem\u003eChannel pricing on 8-GPU baseboards moves, so we confirm the figure against documented acquisition cost when you order — if it has moved in your favour, so does the price. Export clearance is part of the delivery. Contact us with your model, context length and site power envelope and we will come back with a firm quote, a measured throughput estimate and a delivery date.\u003c\/em\u003e\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Kentino","offers":[{"title":"Default Title","offer_id":54417214013768,"sku":null,"price":785132.0,"currency_code":"EUR","in_stock":true}],"url":"https:\/\/kentino.com\/es\/products\/k-node-h200-8x-sxm5-1128gb","provider":"Kentino","version":"1.0","type":"link"}