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Keep memory capacity, BIOS power behavior, and settings fixed and record average frame rate, 1% lows, GPU usage, and CPU package power for a reproducible comparison.\u003C\u002Fp>",193,{"slug":367,"type":367,"question":368,"answer":369,"page":9,"heat":370},"cores","How should the core and thread counts of Core Ultra 5 225 be understood, and do more cores help in games?","\u003Cp style=\"margin:0 0 4px;line-height:1.5;\">  Core Ultra 5 225 has 10 cores and 10 threads, with 6 performance cores and 4 efficiency cores; this Arrow Lake desktop chip has no Hyper-Threading. Gaming depends on performance-core response, the GPU, and resolution, with 1080p high refresh exposing CPU limits sooner. Compiling, encoding, and rendering benefit only when software uses the 10 threads well, and sustained work also depends on motherboard long-term power beyond the 65 W base class.\u003C\u002Fp>",187,{"slug":372,"type":372,"question":373,"answer":374,"page":9,"heat":375},"ai","The desktop 10-core Ultra 5 225 — enough for an AI desktop?","\u003Cp style=\"margin:0 0 4px;line-height:1.5;\">  The Ultra 5 225 is the desktop part at 10 cores\u002F10 threads, 4.9GHz boost, 20MB of L3, VNNI INT8, AI Boost around 23 TOPS and an iGPU on Arrow Lake. Ten cores\u002F10 threads reads entry-plus on desktop, and the 23-TOPS NPU plus VNNI cover local light AI: meeting enhancement, captions, OCR and small-model inference all flow.\u003C\u002Fp>\u003Cp style=\"margin:0 0 4px;line-height:1.5;\">  Its 'enough' is defined between office and light AI: 7B-class quantized grinds rather than flows, and heavy data work is on the weak side. It fits desktop users with tight budgets who mostly run office plus light AI; for more fluent local AI or thread-heavy data work, pay up to the 14- or 20-core.\u003C\u002Fp>",166,[377,381,384,387,389,391,393,396,398,401,403,405,407,409,411,414,416,418,420,422],{"slug_a":378,"slug_b":379,"name_a":9,"name_b":9,"i_heat":380},"core-ultra-5-225","core-ultra-7-268v",14,{"slug_a":382,"slug_b":378,"name_a":9,"name_b":9,"i_heat":383},"core-ultra-5-125u",13,{"slug_a":385,"slug_b":378,"name_a":9,"name_b":9,"i_heat":386},"core-i7-11600h",11,{"slug_a":388,"slug_b":378,"name_a":9,"name_b":9,"i_heat":386},"core-i7-12650h",{"slug_a":378,"slug_b":390,"name_a":9,"name_b":9,"i_heat":291},"core-ultra-5-225t",{"slug_a":378,"slug_b":392,"name_a":9,"name_b":9,"i_heat":311},"core-ultra-7-164u",{"slug_a":394,"slug_b":378,"name_a":9,"name_b":9,"i_heat":395},"core-i7-1270pe",8,{"slug_a":397,"slug_b":378,"name_a":9,"name_b":9,"i_heat":395},"core-i9-11950h",{"slug_a":378,"slug_b":399,"name_a":9,"name_b":9,"i_heat":400},"core-ultra-5-235u",7,{"slug_a":378,"slug_b":402,"name_a":9,"name_b":9,"i_heat":400},"core-ultra-5-230f",{"slug_a":404,"slug_b":378,"name_a":9,"name_b":9,"i_heat":400},"core-i9-11980hk",{"slug_a":406,"slug_b":378,"name_a":9,"name_b":9,"i_heat":297},"core-ultra-5-125ul",{"slug_a":408,"slug_b":378,"name_a":9,"name_b":9,"i_heat":297},"core-i3-1220p",{"slug_a":410,"slug_b":378,"name_a":9,"name_b":9,"i_heat":297},"core-i7-11800h",{"slug_a":378,"slug_b":412,"name_a":9,"name_b":9,"i_heat":413},"core-ultra-7-266v",5,{"slug_a":378,"slug_b":415,"name_a":9,"name_b":9,"i_heat":413},"core-ultra-5-336h",{"slug_a":378,"slug_b":417,"name_a":9,"name_b":9,"i_heat":413},"core-ultra-7-155ul",{"slug_a":419,"slug_b":378,"name_a":9,"name_b":9,"i_heat":413},"core-i7-1265ue",{"slug_a":421,"slug_b":378,"name_a":9,"name_b":9,"i_heat":413},"core-i7-11850h",{"slug_a":378,"slug_b":423,"name_a":9,"name_b":9,"i_heat":193},"core-ultra-5-235h"]