This is DeepSeek R1’s reasoning distilled into a 70B Llama base \u2014 an attempt to carry
\nR1’s step-by-step chain-of-thought behaviour onto hardware a single team can actually own.
\nIt is MIT-licensed with a 128K context, needs about 40 GB of VRAM at 4-bit, and runs on two
\nRTX 4090s or one 48 GB card.<\/p>\n
That hardware line is the whole point. Full DeepSeek R1 needs roughly 400 GB at the same
\nquantisation; this distill needs a tenth of that, which moves it from “rent a server” to
\n“buy a workstation”. The trade is real \u2014 a distill inherits the teacher’s reasoning style
\nmore faithfully than its raw capability, so expect it to show its working well but to fall
\nshort of R1 on the hardest problems. Where it earns its place is in workloads that must stay
\non-premises: regulated data, air-gapped environments, or products whose margins cannot
\nabsorb per-token API pricing at volume. At $0.80 for both input and output it is also
\nunusually simple to budget, since the input\/output ratio is 1:1 and generation-heavy
\nworkloads cost no more than prompt-heavy ones.<\/p>","protected":false},"excerpt":{"rendered":"
What is DeepSeek R1 Distill Llama 70B? This is DeepSeek R1’s reasoning distilled into a 70B Llama base \u2014 an […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"cm_developer":"DeepSeek","cm_model_type":"LLM (dense, reasoning)","cm_modality":"Text \u2192 Text","cm_parameters":"70B","cm_context_window":"128K","cm_max_output":"","cm_license":"MIT (open)","cm_open_weights":"yes","cm_release_date":"2025","cm_input_price":"0.80","cm_output_price":"0.80","cm_api_providers":"DeepInfra, OpenRouter, Ollama","cm_vram_fp16":"","cm_vram_q4":"~40 GB","cm_min_gpu":"2\u00d7 RTX 4090 \/ 1\u00d7 48GB","cm_benchmarks":"","cm_official_url":"https:\/\/huggingface.co\/deepseek-ai"},"class_list":["post-1252","ai_model","type-ai_model","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/ai_model\/1252","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/ai_model"}],"about":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/types\/ai_model"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/de\/wp-json\/wp\/v2\/media?parent=1252"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}