{"product_id":"k-ai-192-rome-arcprob70-tbd-6-intel-arc-pro-b70-epyc-milan-pre-order","title":"K-AI 192 Rome ArcProB70 TBD — 6× Intel Arc Pro B70 — EPYC Milan (Pre-Order)","description":"\u003cdiv style=\"font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,sans-serif;line-height:1.7;color:#1a1a1a\"\u003e\n\n\u003cdiv style=\"background:linear-gradient(135deg,#0d0d0d 0%,#1a1a2e 100%);color:#fff;padding:32px;border-radius:12px;margin-bottom:32px\"\u003e\n\u003cdiv style=\"background:rgba(250,180,0,0.25);border:2px solid #fab400;border-radius:8px;padding:12px 20px;margin-bottom:20px;text-align:center\"\u003e\n\u003cp style=\"margin:0;font-size:16px;font-weight:800;color:#fab400;text-transform:uppercase;letter-spacing:2px\"\u003eIN PREPARATION\u003c\/p\u003e\n\u003cp style=\"margin:4px 0 0 0;font-size:13px;color:#ccc\"\u003ePre-order — Intel Arc Pro B70 shipping target Q3 2026\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cp style=\"font-size:18px;margin:0 0 20px 0;color:#ccc\"\u003eK-AI 192 Rome ArcProB70 TBD\u003c\/p\u003e\n\u003cp style=\"font-size:28px;font-weight:700;margin:0 0 16px 0;line-height:1.3\"\u003e192 GB VRAM Intel Xe2 Inference Server\u003cbr\u003e6x Arc Pro B70 | EPYC Milan | TOPS TBD\u003c\/p\u003e\n\u003cdiv style=\"display:flex;gap:16px;flex-wrap:wrap;margin-top:24px\"\u003e\n\u003cdiv style=\"background:rgba(250,180,0,0.15);border:1px solid #fab400;border-radius:8px;padding:14px 16px;text-align:center;flex:1;min-width:100px\"\u003e\n\u003cdiv style=\"font-size:26px;font-weight:800;color:#fab400\"\u003eTBD\u003c\/div\u003e\n\u003cdiv style=\"font-size:11px;color:#ccc;text-transform:uppercase;letter-spacing:1px\"\u003eINT8 TOPS\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"background:rgba(250,180,0,0.15);border:1px solid #fab400;border-radius:8px;padding:14px 16px;text-align:center;flex:1;min-width:100px\"\u003e\n\u003cdiv style=\"font-size:26px;font-weight:800;color:#fab400\"\u003e192 GB\u003c\/div\u003e\n\u003cdiv style=\"font-size:11px;color:#ccc;text-transform:uppercase;letter-spacing:1px\"\u003eVRAM pool\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"background:rgba(250,180,0,0.15);border:1px solid #fab400;border-radius:8px;padding:14px 16px;text-align:center;flex:1;min-width:100px\"\u003e\n\u003cdiv style=\"font-size:26px;font-weight:800;color:#fab400\"\u003eIntel\u003c\/div\u003e\n\u003cdiv style=\"font-size:11px;color:#ccc;text-transform:uppercase;letter-spacing:1px\"\u003eXe2 Battlemage\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"background:rgba(250,180,0,0.15);border:1px solid #fab400;border-radius:8px;padding:14px 16px;text-align:center;flex:1;min-width:100px\"\u003e\n\u003cdiv style=\"font-size:26px;font-weight:800;color:#fab400\"\u003e6-card\u003c\/div\u003e\n\u003cdiv style=\"font-size:11px;color:#ccc;text-transform:uppercase;letter-spacing:1px\"\u003eOpenVINO \/ SYCL\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp style=\"margin-top:20px;font-size:15px;color:#aaa\"\u003eBudget-oriented high-VRAM build targeting the Intel open-source inference stack. Pricing locked at Intel availability.\u003c\/p\u003e\n\u003c\/div\u003e\n\n\u003cp style=\"font-size:17px;color:#333;margin-bottom:24px\"\u003eA 4U rack-mount inference server with six Intel Arc Pro B70 Creator cards (32 GB Xe2-HPG \"Battlemage\" each, 192 GB aggregate), one AMD EPYC 7643 Milan CPU (48C\/96T), 384 GB DDR4 ECC, 2 TB NVMe boot, and a 2 kW ATX PSU (dual-PSU upgrade strongly recommended). Built for the Intel software ecosystem: OpenVINO 2025+, IPEX-LLM, llama.cpp SYCL backend, and vLLM-Intel forks. CUDA-only workloads do not run on this hardware.\u003c\/p\u003e\n\n\u003ch2 style=\"font-size:22px;font-weight:700;margin:40px 0 16px 0;padding-bottom:8px;border-bottom:3px solid #2563eb\"\u003eHardware\u003c\/h2\u003e\n\n\u003ctable style=\"width:100%;border-collapse:collapse;margin-bottom:24px;font-size:15px\"\u003e\n\u003cthead\u003e\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\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\"\u003e6x Intel Arc Pro B70 Creator 32 GB (Xe2-HPG \"Battlemage\", 250 W, PCIe 5.0 x16, dual-slot)\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\"\u003e192 GB aggregate across 6 cards (no inter-card fabric — peer traffic over PCIe)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background:#f8f8f8\"\u003e\n\u003ctd style=\"padding:10px 16px;font-weight:600\"\u003eCPU\u003c\/td\u003e\n\u003ctd style=\"padding:10px 16px\"\u003eAMD EPYC 7643 Milan (48C\/96T, 225 W, 128x PCIe 4.0 lanes)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding:10px 16px;font-weight:600\"\u003eMotherboard\u003c\/td\u003e\n\u003ctd style=\"padding:10px 16px\"\u003eASRock Rack ROMED8-2T (SP3, 7x PCIe 4.0 x16, 8x DDR4 ECC, 2x 10 GbE, IPMI)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background:#f8f8f8\"\u003e\n\u003ctd style=\"padding:10px 16px;font-weight:600\"\u003eSystem RAM\u003c\/td\u003e\n\u003ctd style=\"padding:10px 16px\"\u003e384 GB DDR4-2666 ECC RDIMM (6x 64 GB)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding:10px 16px;font-weight:600\"\u003eBoot \/ storage\u003c\/td\u003e\n\u003ctd style=\"padding:10px 16px\"\u003e2 TB NVMe M.2 (PCIe 4.0 x4)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background:#f8f8f8\"\u003e\n\u003ctd style=\"padding:10px 16px;font-weight:600\"\u003ePower supply\u003c\/td\u003e\n\u003ctd style=\"padding:10px 16px\"\u003e1x 2 kW ATX PSU (dual 2 kW synced upgrade strongly recommended)\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\"\u003e4U rack-mount (6-slot layout)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"background:#f8f8f8\"\u003e\n\u003ctd style=\"padding:10px 16px;font-weight:600\"\u003eCooling\u003c\/td\u003e\n\u003ctd style=\"padding:10px 16px\"\u003eSP3 tower cooler (Arctic Freezer 4U-M) + front-to-back directed airflow (industrial fans)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding:10px 16px;font-weight:600\"\u003eNetwork\u003c\/td\u003e\n\u003ctd style=\"padding:10px 16px\"\u003eOnboard dual 10 GbE (Intel X550)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003cdiv style=\"display:flex;gap:16px;flex-wrap:wrap;margin-bottom:32px\"\u003e\n\u003cdiv style=\"flex:1;min-width:250px;background:#f4f4f4;border-radius:8px;padding:20px\"\u003e\n\u003ch3 style=\"font-size:16px;font-weight:700;margin:0 0 12px 0\"\u003ePower envelope\u003c\/h3\u003e\n\u003cul style=\"margin:0;padding-left:18px;font-size:14px;color:#444\"\u003e\n\u003cli\u003eGPU draw: 6 x 250 W = 1 500 W (Intel-published TDP)\u003c\/li\u003e\n\u003cli\u003eSystem total at full load: ~1 825 W\u003c\/li\u003e\n\u003cli\u003ePSU total: 2 000 W (single) — only 8.75 % headroom\u003c\/li\u003e\n\u003cli\u003eDual 2 kW synced strongly recommended — restores ~45 % headroom\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"flex:1;min-width:250px;background:#f4f4f4;border-radius:8px;padding:20px\"\u003e\n\u003ch3 style=\"font-size:16px;font-weight:700;margin:0 0 12px 0\"\u003eLane topology\u003c\/h3\u003e\n\u003cp style=\"margin:0;font-size:14px;color:#444\"\u003eROMED8-2T provides 7x PCIe 4.0 x16 lanes. Six slots populated; one free for NIC upsell. Arc Pro B70 is PCIe Gen5 native; ROMED8-2T runs at Gen4 — bandwidth impact negligible for inference at 32 GB per card. No PCIe switch. No Xe-Link equivalent.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\n\u003ch2 style=\"font-size:22px;font-weight:700;margin:40px 0 16px 0;padding-bottom:8px;border-bottom:3px solid #2563eb\"\u003eWhat you can run\u003c\/h2\u003e\n\n\u003cdiv style=\"background:#fefaf0;border-left:4px solid #fab400;padding:16px 20px;margin-bottom:24px;border-radius:0 8px 8px 0\"\u003e\n\u003cp style=\"margin:0;font-size:15px;color:#333\"\u003eAll compatibility claims are Intel-software-stack paths (OpenVINO, IPEX-LLM, llama.cpp SYCL, vLLM-Intel). CUDA-only workloads do not run on this hardware. All figures cite published external sources and are subject to independent verification when cards ship.\u003c\/p\u003e\n\u003c\/div\u003e\n\n\u003ch3 style=\"font-size:18px;font-weight:700;margin:28px 0 12px 0;color:#0d0d0d\"\u003eLLMs — text \/ reasoning \/ coding\u003c\/h3\u003e\n\n\u003cp style=\"font-size:14px;font-weight:700;color:#fab400;text-transform:uppercase;letter-spacing:1px;margin-bottom:8px\"\u003eChinese frontier\u003c\/p\u003e\n\u003cul style=\"font-size:15px;color:#333;line-height:1.8\"\u003e\n\u003cli\u003e\n\u003cstrong\u003eQwen3 \/ Qwen3.5 (Alibaba):\u003c\/strong\u003e Qwen3-235B-A22B Q4 (~132 GB) with long context headroom; Qwen3-Coder-480B-A35B Q2 (~160 GB); Qwen3.5-397B-A17B Q3 (~170 GB)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eGLM \/ Z.ai:\u003c\/strong\u003e GLM-4.5 \/ 4.6 \/ 4.7 Q4 (~177 GB) — fits with moderate KV\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTencent Hunyuan:\u003c\/strong\u003e Hunyuan-Large Q3 (~160 GB); Hunyuan-A13B fp8 (~80 GB) if Xe2 fp8 path exposed in driver\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOthers:\u003c\/strong\u003e Baidu ERNIE-4.5-424B Q3 (~180 GB); MiniMax-M1 Q3 (~180 GB); DeepSeek-R2 32B (6x concurrent streams)\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp style=\"font-size:14px;font-weight:700;color:#fab400;text-transform:uppercase;letter-spacing:1px;margin:20px 0 8px 0\"\u003eWestern frontier\u003c\/p\u003e\n\u003cul style=\"font-size:15px;color:#333;line-height:1.8\"\u003e\n\u003cli\u003e\n\u003cstrong\u003eMeta Llama:\u003c\/strong\u003e Llama 3.3 70B Q6-Q8 with generous KV; Llama 4 Scout 109B\/17B Q4 (~63 GB) comfortable\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMistral:\u003c\/strong\u003e Mistral Small 3 \/ Magistral Small \/ Devstral Small 2 (24B) at bf16; Pixtral Large Q4-Q6\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOpenAI (open weights):\u003c\/strong\u003e gpt-oss-120b MXFP4 native (~80 GB) — if MXFP4 dequant available in Intel stack\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eNVIDIA Nemotron:\u003c\/strong\u003e Llama-3.1-Nemotron Ultra 253B Q4 (~120 GB)\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOthers:\u003c\/strong\u003e Gemma 3 27B bf16 multimodal; Phi-4 \/ Phi-4-reasoning 14B; Cohere Command R+ 104B Q4\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3 style=\"font-size:18px;font-weight:700;margin:28px 0 12px 0;color:#0d0d0d\"\u003eVision-Language Models\u003c\/h3\u003e\n\u003cp style=\"font-size:15px;color:#333\"\u003eQwen3-VL-8B \/ 32B; Qwen3-VL-30B-A3B MoE; InternVL3 up to 78B; InternVL3.5-38B; Llama 3.2 90B Vision Q4; Pixtral 12B; Molmo 72B Q4; Gemma 3 12B\/27B multimodal; MiniCPM-V 2.6 \/ MiniCPM-o 2.6. Intel's OpenVINO has strong vision-tower support — VLM is a plausible day-one strength.\u003c\/p\u003e\n\n\u003ch3 style=\"font-size:18px;font-weight:700;margin:28px 0 12px 0;color:#0d0d0d\"\u003eImage generation\u003c\/h3\u003e\n\u003cp style=\"font-size:15px;color:#333\"\u003eFLUX.1 [dev] \/ [schnell] fp8 or Q4 GGUF via llama.cpp SYCL; SDXL \/ SD 3.5 Large via OpenVINO genAI runtime; HunyuanDiT; HunyuanImage-2.1 bf16 (~34 GB); Kolors 2.0; AuraFlow; OmniGen; PixArt-Sigma.\u003c\/p\u003e\n\n\u003ch3 style=\"font-size:18px;font-weight:700;margin:28px 0 12px 0;color:#0d0d0d\"\u003eVideo generation\u003c\/h3\u003e\n\u003cp style=\"font-size:15px;color:#333\"\u003eWan 2.2 T2V-A14B \/ I2V-A14B MoE (~54 GB bf16); Wan 2.2 TI2V-5B; HunyuanVideo 13B bf16; HunyuanVideo 1.5; CogVideoX-5B; Open-Sora 2.0; LTX-Video; Pyramid Flow; Mochi-1 Q4. Video is the weakest Intel path today — expect functional but not throughput-optimal at ship time.\u003c\/p\u003e\n\n\u003ch3 style=\"font-size:18px;font-weight:700;margin:28px 0 12px 0;color:#0d0d0d\"\u003eAudio \/ Speech \/ TTS\u003c\/h3\u003e\n\u003cul style=\"font-size:15px;color:#333;line-height:1.8\"\u003e\n\u003cli\u003e\n\u003cstrong\u003eASR:\u003c\/strong\u003e Whisper v3 large \/ turbo via OpenVINO (first-class Intel Whisper support); Parakeet-TDT; Canary; SenseVoice\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTTS:\u003c\/strong\u003e CosyVoice 2\/3; Kokoro 82M; Stable Audio Open; XTTS v2; StyleTTS 2; Step-Audio-EditX\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRealtime \/ S2S:\u003c\/strong\u003e Kyutai Moshi; MusicGen \/ AudioGen \/ Bark; SeamlessM4T v2\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3 style=\"font-size:18px;font-weight:700;margin:28px 0 12px 0;color:#0d0d0d\"\u003eMulti-model \/ multi-tenant serving\u003c\/h3\u003e\n\u003cul style=\"font-size:15px;color:#333;line-height:1.8\"\u003e\n\u003cli\u003e6 concurrent streams of a 32 GB Q4 model (one per card) — e.g. 6x Qwen3-32B Q4 agents\u003c\/li\u003e\n\u003cli\u003eEmbedding-fleet at scale — 6x parallel BGE-M3 \/ E5 \/ Nomic Embed streams (OpenVINO-optimized)\u003c\/li\u003e\n\u003cli\u003eMixed residency — 70B Q4 (tensor-parallel over 3 cards) + FLUX.1 (1 card) + Whisper-turbo (1 card) + Moshi (1 card)\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2 style=\"font-size:22px;font-weight:700;margin:40px 0 16px 0;padding-bottom:8px;border-bottom:3px solid #2563eb\"\u003eTarget workloads\u003c\/h2\u003e\n\u003cul style=\"font-size:15px;color:#333;line-height:1.8\"\u003e\n\u003cli\u003eIntel-software evaluation pilot for CUDA-alternative LLM serving\u003c\/li\u003e\n\u003cli\u003eEmbedding \/ reranker backend where VRAM-per-EUR dominates throughput requirements\u003c\/li\u003e\n\u003cli\u003eBudget Q4 frontier-MoE inference (Qwen3-235B, GLM-4.5\/4.6\/4.7) for small internal dev teams\u003c\/li\u003e\n\u003cli\u003eOpenVINO-native model deployment alongside existing Intel Xeon \/ Arc Pro pipelines\u003c\/li\u003e\n\u003cli\u003eVLM \/ OCR \/ document-processing backend (Intel's OpenVINO strength)\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2 style=\"font-size:22px;font-weight:700;margin:40px 0 16px 0;padding-bottom:8px;border-bottom:3px solid #2563eb\"\u003eMeasured performance\u003c\/h2\u003e\n\n\u003cdiv style=\"background:#0d0d0d;color:#fff;border-radius:12px;padding:24px;margin-bottom:24px\"\u003e\n\u003cp style=\"margin:0 0 4px 0;font-size:13px;color:#888;text-transform:uppercase;letter-spacing:1px\"\u003eIntel-published specs | Subject to independent verification when cards ship\u003c\/p\u003e\n\u003ctable style=\"width:100%;border-collapse:collapse;margin-top:16px;font-size:14px\"\u003e\n\u003cthead\u003e\u003ctr style=\"border-bottom:1px solid #333\"\u003e\n\u003cth style=\"padding:8px 12px;text-align:left;color:#888;font-weight:600\"\u003eSpec\u003c\/th\u003e\n\u003cth style=\"padding:8px 12px;text-align:left;color:#888;font-weight:600\"\u003eValue\u003c\/th\u003e\n\u003c\/tr\u003e\u003c\/thead\u003e\n\u003ctbody\u003e\n\u003ctr style=\"border-bottom:1px solid #222\"\u003e\n\u003ctd style=\"padding:10px 12px;color:#ccc\"\u003eVRAM per card\u003c\/td\u003e\n\u003ctd style=\"padding:10px 12px;color:#fab400;font-weight:700\"\u003e32 GB GDDR6\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"border-bottom:1px solid #222\"\u003e\n\u003ctd style=\"padding:10px 12px;color:#ccc\"\u003eMemory bandwidth class\u003c\/td\u003e\n\u003ctd style=\"padding:10px 12px;color:#fff\"\u003e~450 GB\/s per card\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"border-bottom:1px solid #222\"\u003e\n\u003ctd style=\"padding:10px 12px;color:#ccc\"\u003eXe Matrix Extensions (XMX)\u003c\/td\u003e\n\u003ctd style=\"padding:10px 12px;color:#fff\"\u003eAccelerated via OpenVINO \/ IPEX-LLM\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"padding:10px 12px;color:#ccc\"\u003efp8 path\u003c\/td\u003e\n\u003ctd style=\"padding:10px 12px;color:#fff\"\u003eXe2 silicon — verify driver exposure at ship time\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp style=\"margin:12px 0 0 0;font-size:13px;color:#666\"\u003eNo Kentino measured data. Intel-published specs subject to independent verification. Kentino will publish first-party tok\/s \/ QPS \/ bandwidth numbers once the first unit passes burn-in.\u003c\/p\u003e\n\u003c\/div\u003e\n\n\u003ch2 style=\"font-size:22px;font-weight:700;margin:40px 0 16px 0;padding-bottom:8px;border-bottom:3px solid #2563eb\"\u003eNot ideal for\u003c\/h2\u003e\n\u003cul style=\"font-size:15px;color:#333;line-height:1.8\"\u003e\n\u003cli\u003eCUDA-native workloads — no CUDA on Intel, expect migration friction\u003c\/li\u003e\n\u003cli\u003eProduction SLA-critical deployments until Intel Arc Pro supply and tooling stabilize\u003c\/li\u003e\n\u003cli\u003eFrontier 600B+ MoE at Q4+ (requires 6x RTX Pro 6000 \/ 576 GB pool)\u003c\/li\u003e\n\u003cli\u003eTraining workloads — Arc Pro is inference-first, framework maturity for distributed training is limited\u003c\/li\u003e\n\u003cli\u003eCustomers who require measured benchmarks before purchase — this SKU is pre-order\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2 style=\"font-size:22px;font-weight:700;margin:40px 0 16px 0;padding-bottom:8px;border-bottom:3px solid #2563eb\"\u003eWarranty and lead time\u003c\/h2\u003e\n\u003cdiv style=\"display:flex;gap:16px;flex-wrap:wrap;margin-bottom:24px\"\u003e\n\u003cdiv style=\"flex:1;min-width:150px;background:#f4f4f4;border-radius:8px;padding:20px;text-align:center\"\u003e\n\u003cdiv style=\"font-size:24px;font-weight:800;color:#0d0d0d\"\u003e2 years\u003c\/div\u003e\n\u003cdiv style=\"font-size:13px;color:#666;text-transform:uppercase;letter-spacing:1px\"\u003eparts warranty\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"flex:1;min-width:150px;background:#f4f4f4;border-radius:8px;padding:20px;text-align:center\"\u003e\n\u003cdiv style=\"font-size:24px;font-weight:800;color:#0d0d0d\"\u003e1 year\u003c\/div\u003e\n\u003cdiv style=\"font-size:13px;color:#666;text-transform:uppercase;letter-spacing:1px\"\u003elabor warranty\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"flex:1;min-width:150px;background:#f4f4f4;border-radius:8px;padding:20px;text-align:center\"\u003e\n\u003cdiv style=\"font-size:24px;font-weight:800;color:#0d0d0d\"\u003eQ3 2026\u003c\/div\u003e\n\u003cdiv style=\"font-size:13px;color:#666;text-transform:uppercase;letter-spacing:1px\"\u003etarget shipping\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cp style=\"font-size:14px;color:#666\"\u003eKentino standard warranty (2 years parts, 1 year labor); Intel distribution terms supersede where stricter. Build includes assembly, BIOS configuration, driver install, burn-in testing, and functional verification. Reserve your first-wave delivery slot via the Kentino contact form. 30-day price-commit window at order.\u003c\/p\u003e\n\n\u003ch2 style=\"font-size:22px;font-weight:700;margin:40px 0 16px 0;padding-bottom:8px;border-bottom:3px solid #2563eb\"\u003eRecommended add-ons\u003c\/h2\u003e\n\u003cul style=\"font-size:15px;color:#333;line-height:1.8\"\u003e\n\u003cli\u003eDual 2 kW synced PSU upgrade (single-PSU headroom is tight at 1 825 W draw — strongly recommended)\u003c\/li\u003e\n\u003cli\u003eUpgrade RAM to 512 GB DDR4 (2x 64 GB — two slots open)\u003c\/li\u003e\n\u003cli\u003e4 TB NVMe secondary drive for model library\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003c\/div\u003e","brand":"Kentino s.r.o.","offers":[{"title":"Default Title","offer_id":52940209783112,"sku":null,"price":20793.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0843\/5479\/3800\/files\/kentino-ai-server-4-gpu-topdown_6b2c51b2-25c1-479d-929a-29eebe60e5ef.jpg?v=1776940959","url":"https:\/\/kentino.com\/de\/products\/k-ai-192-rome-arcprob70-tbd-6-intel-arc-pro-b70-epyc-milan-pre-order","provider":"Kentino","version":"1.0","type":"link"}