{"id":304,"date":"2026-11-03T15:00:00","date_gmt":"2026-11-03T09:30:00","guid":{"rendered":"https:\/\/akshaymaurya.in\/blog\/?p=304"},"modified":"2026-11-03T08:40:45","modified_gmt":"2026-11-03T03:10:45","slug":"hydrogen-1-0-science-model-hindi","status":"publish","type":"post","link":"https:\/\/akshaymaurya.in\/blog\/hydrogen-1-0-science-model-hindi\/","title":{"rendered":"Hydrogen-1.0 \u0915\u094d\u092f\u093e \u0939\u0948: 753B Parameter \u0935\u093e\u0932\u093e Open Science Model \u091c\u094b Research \u092e\u0947\u0902 GPT-6-Astra \u0915\u094b \u092a\u0940\u091b\u0947 \u091b\u094b\u0921\u093c\u0924\u093e \u0939\u0948"},"content":{"rendered":"\n<p>2 November 2026 \u0915\u094b Deep Principle \u0928\u093e\u092e \u0915\u0940 company \u0928\u0947 \u0905\u092a\u0928\u0947 scientific AI model Hydrogen-1.0 \u0915\u0947 \u092a\u0942\u0930\u0947 weights public \u0915\u0930 \u0926\u093f\u090f, \u091c\u0948\u0938\u093e \u0915\u093f \u0909\u0938\u0915\u0947 <a href=\"https:\/\/huggingface.co\" target=\"_blank\" rel=\"noopener\">Hugging Face model card<\/a> \u092e\u0947\u0902 detail \u092e\u0947\u0902 \u092c\u0924\u093e\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u092f\u0939 \u090f\u0915 753 billion parameter \u0935\u093e\u0932\u093e model \u0939\u0948, \u091c\u094b \u0916\u093e\u0938 \u0924\u094c\u0930 \u092a\u0930 science \u0915\u0947 \u0938\u0935\u093e\u0932\u094b\u0902 \u0915\u0947 \u0932\u093f\u090f \u092c\u0928\u093e\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 Derivations, experimental planning, research papers \u091c\u0948\u0938\u0947 \u0915\u093e\u092e\u094b\u0902 \u092e\u0947\u0902 \u092e\u0926\u0926 \u0915\u0930\u0928\u093e \u0907\u0938\u0915\u093e \u092e\u0915\u0938\u0926 \u0939\u0948\u0964 \u0938\u092c\u0938\u0947 \u092c\u0921\u093c\u0940 \u092c\u093e\u0924 \u092f\u0939 \u0939\u0948 \u0915\u093f \u0907\u0938\u0915\u0947 weights MIT License \u0915\u0947 \u0924\u0939\u0924 release \u0939\u0941\u090f \u0939\u0948\u0902, \u092f\u093e\u0928\u0940 \u0915\u094b\u0908 \u092d\u0940 \u0907\u0928\u094d\u0939\u0947\u0902 download \u0915\u0930\u0915\u0947 \u0905\u092a\u0928\u0947 servers \u092a\u0930 \u091a\u0932\u093e \u0938\u0915\u0924\u093e \u0939\u0948\u0964<\/p>\n<h2>Hydrogen-1.0 \u0915\u094d\u092f\u093e \u0939\u0948<\/h2>\n<p>Hydrogen-1.0 \u090f\u0915 scientific problem solving \u0914\u0930 research assistance model \u0939\u0948\u0964 Normal AI models \u0939\u0930 \u0924\u0930\u0939 \u0915\u0947 \u0938\u0935\u093e\u0932\u094b\u0902 \u0915\u0947 \u091c\u0935\u093e\u092c \u0926\u0947\u0924\u0947 \u0939\u0948\u0902\u0964 \u092f\u0939 model science \u092a\u0930 focused \u0939\u0948\u0964 Physics \u0915\u0947 equations, chemistry \u0915\u0947 reactions, research papers \u0915\u0940 analysis, experiments \u0915\u0940 planning, \u0910\u0938\u0947 \u0915\u093e\u092e\u094b\u0902 \u0915\u0947 \u0932\u093f\u090f \u0907\u0938\u0947 specially train \u0915\u093f\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u092f\u0939 model Zhipu AI \u0915\u0947 GLM-5.3 \u092a\u0930 based \u0939\u0948, \u091c\u093f\u0938\u0947 scientific data \u092a\u0930 supervised fine-tuning \u0914\u0930 reinforcement learning \u0938\u0947 \u0906\u0917\u0947 train \u0915\u093f\u092f\u093e \u0917\u092f\u093e\u0964<\/p>\n<p>\u092f\u0939\u093e\u0902 \u090f\u0915 honesty note \u091c\u0930\u0942\u0930\u0940 \u0939\u0948\u0964 Deep Principle \u0928\u0947 weights \u0924\u094b \u0916\u094b\u0932 \u0926\u093f\u090f, \u0932\u0947\u0915\u093f\u0928 \u092a\u0942\u0930\u0947 training datasets \u0914\u0930 training recipes share \u0928\u0939\u0940\u0902 \u0915\u093f\u090f\u0964 \u092f\u093e\u0928\u0940 model \u0915\u093e \u0938\u0940\u0916\u093e \u0939\u0941\u0906 \u091c\u094d\u091e\u093e\u0928 \u092e\u093f\u0932 \u0930\u0939\u093e \u0939\u0948, \u0932\u0947\u0915\u093f\u0928 \u0935\u0939 \u0938\u093f\u0916\u093e\u092f\u093e \u0915\u0948\u0938\u0947 \u0917\u092f\u093e, \u0907\u0938\u0915\u0940 \u092a\u0942\u0930\u0940 recipe company \u0915\u0947 \u092a\u093e\u0938 \u0939\u0940 \u0939\u0948\u0964<\/p>\n<h2>753B Parameters \u0915\u093e \u092e\u0924\u0932\u092c \u0938\u092e\u091d\u093f\u090f<\/h2>\n<p>753 billion parameters \u0915\u093e \u092e\u0924\u0932\u092c \u0939\u0948 \u090f\u0915 \u092c\u0939\u0941\u0924 \u092c\u0921\u093c\u093e model\u0964 Comparison \u0915\u0947 \u0932\u093f\u090f, \u0939\u093e\u0932 \u0939\u0940 \u092e\u0947\u0902 release \u0939\u0941\u0906 <a href=\"https:\/\/akshaymaurya.in\/blog\/nace-ai-drex-max-v1-open-weight-hindi\/\">Nace AI \u0915\u093e Drex Max v1<\/a> 27 billion parameters \u0915\u093e \u0925\u093e, \u0914\u0930 <a href=\"https:\/\/akshaymaurya.in\/blog\/mistral-large-4-le-chonk-open-weights-hindi\/\">Mistral Large 4<\/a> 1 trillion parameters \u0915\u093e \u0939\u0948\u0964 Hydrogen-1.0 \u0907\u0928\u0915\u0947 \u092c\u0940\u091a \u092e\u0947\u0902 \u0916\u0921\u093c\u093e \u0939\u0948, \u0932\u0947\u0915\u093f\u0928 \u0907\u0938\u0915\u0940 \u0916\u093e\u0938\u093f\u092f\u0924 size \u092e\u0947\u0902 \u0928\u0939\u0940\u0902, focus \u092e\u0947\u0902 \u0939\u0948\u0964 \u092f\u0939 general purpose giant \u0928\u0939\u0940\u0902, science specialist \u0939\u0948\u0964<\/p>\n<p>\u0907\u0924\u0928\u093e \u092c\u0921\u093c\u093e model \u0906\u092e computer \u092a\u0930 \u0928\u0939\u0940\u0902 \u091a\u0932\u0947\u0917\u093e\u0964 Company \u0928\u0947 BF16 weights \u0915\u0947 \u0938\u093e\u0925 NVFP4 \u0914\u0930 MXFP4 quantized versions \u092d\u0940 \u0926\u093f\u090f \u0939\u0948\u0902, \u091c\u094b NVIDIA B200\/B300 \u0914\u0930 AMD Instinct MI350X\/MI355X GPUs \u092a\u0930 \u091a\u0932\u0924\u0947 \u0939\u0948\u0902\u0964 Deep Principle \u0928\u0947 BF16 serving \u0915\u094b \u0906\u0920 GPUs \u092a\u0930 SGLang \u0915\u0947 \u0938\u093e\u0925 test \u0915\u093f\u092f\u093e \u0939\u0948\u0964 \u0938\u093e\u092b \u0939\u0948, \u092f\u0939 model research labs \u0914\u0930 companies \u0915\u0947 data centers \u0915\u0947 \u0932\u093f\u090f \u0939\u0948, \u0918\u0930 \u0915\u0947 laptop \u0915\u0947 \u0932\u093f\u090f \u0928\u0939\u0940\u0902\u0964<\/p>\n<h2>Benchmarks: company \u0915\u0947 \u0905\u092a\u0928\u0947 \u0926\u093e\u0935\u0947<\/h2>\n<p>Benchmarks \u0915\u094b \u0939\u092e\u0947\u0936\u093e company \u0915\u0947 \u0926\u093e\u0935\u0947 \u0915\u0940 \u0924\u0930\u0939 \u092a\u0922\u093c\u0928\u093e \u091a\u093e\u0939\u093f\u090f, independent verification \u0915\u0940 \u0924\u0930\u0939 \u0928\u0939\u0940\u0902\u0964 Deep Principle \u0915\u0947 \u092e\u0941\u0924\u093e\u092c\u093f\u0915 Hydrogen-1.0 \u0928\u0947 FrontierScience-Research benchmark \u092a\u0930 OpenAI \u0915\u0947 GPT-6-Astra \u0915\u094b \u092a\u0940\u091b\u0947 \u091b\u094b\u0921\u093c\u093e \u0939\u0948\u0964<\/p>\n<p>Company \u0915\u0947 \u0905\u092a\u0928\u0947 research-task tests \u092e\u0947\u0902 Hydrogen-1.0 scientific computing \u092e\u0947\u0902 GPT-6-Astra \u0938\u0947 5.13 points \u0906\u0917\u0947 \u0930\u0939\u093e, \u0914\u0930 forward reaction prediction \u092e\u0947\u0902 4.76 points \u0906\u0917\u0947\u0964 \u0932\u0947\u0915\u093f\u0928 NMR structure elucidation \u092e\u0947\u0902 3.33 points \u092a\u0940\u091b\u0947 \u092d\u0940 \u0930\u0939\u093e\u0964<\/p>\n<p>\u092e\u0947\u0930\u0947 \u0939\u093f\u0938\u093e\u092c \u0938\u0947 \u092f\u0939 mixed result \u0939\u0940 \u0907\u0938 report \u0915\u094b credible \u092c\u0928\u093e\u0924\u093e \u0939\u0948\u0964 \u091c\u094b company \u0938\u093f\u0930\u094d\u092b \u0905\u092a\u0928\u0940 \u091c\u0940\u0924 \u092c\u0924\u093e\u090f \u0914\u0930 \u0939\u093e\u0930 \u091b\u093f\u092a\u093e\u090f, \u0909\u0938 \u092a\u0930 \u0936\u0915 \u0915\u0930\u0928\u093e \u091a\u093e\u0939\u093f\u090f\u0964 Deep Principle \u0928\u0947 \u0935\u0939 category \u092d\u0940 \u092c\u0924\u093e\u0908 \u091c\u0939\u093e\u0902 \u0935\u0939 \u092a\u0940\u091b\u0947 \u0939\u0948\u0964 \u092f\u0939 honest evaluation \u0915\u0940 \u0928\u093f\u0936\u093e\u0928\u0940 \u0939\u0948\u0964<\/p>\n<h2>MIT License \u0915\u094d\u092f\u094b\u0902 \u092c\u0921\u093c\u0940 \u092c\u093e\u0924 \u0939\u0948<\/h2>\n<p>Weights MIT License \u0915\u0947 \u0924\u0939\u0924 release \u0939\u0941\u090f \u0939\u0948\u0902\u0964 \u092f\u0939 AI world \u0915\u0940 \u0938\u092c\u0938\u0947 permissive licenses \u092e\u0947\u0902 \u0938\u0947 \u090f\u0915 \u0939\u0948\u0964 \u0907\u0938\u0915\u093e \u092e\u0924\u0932\u092c \u0939\u0948 \u0915\u093f \u0915\u094b\u0908 \u092d\u0940 \u0907\u0938 model \u0915\u094b download \u0915\u0930 \u0938\u0915\u0924\u093e \u0939\u0948, modify \u0915\u0930 \u0938\u0915\u0924\u093e \u0939\u0948, \u0914\u0930 commercial products \u092e\u0947\u0902 \u092d\u0940 \u0907\u0938\u094d\u0924\u0947\u092e\u093e\u0932 \u0915\u0930 \u0938\u0915\u0924\u093e \u0939\u0948, \u092c\u093f\u0928\u093e company \u0938\u0947 permission \u0932\u093f\u090f\u0964<\/p>\n<p>\u0907\u0938\u0915\u0940 \u0924\u0941\u0932\u0928\u093e \u0939\u093e\u0932 \u0915\u0947 \u0926\u0942\u0938\u0930\u0947 open-weight releases \u0938\u0947 \u0915\u0940\u091c\u093f\u090f\u0964 Nace AI \u0928\u0947 Drex Max v1 \u0915\u094b Open RAIL-M license \u092e\u0947\u0902 \u0926\u093f\u092f\u093e \u0925\u093e, \u091c\u093f\u0938\u092e\u0947\u0902 responsible use \u0915\u0940 \u0936\u0930\u094d\u0924\u0947\u0902 \u0939\u0948\u0902\u0964 Hydrogen-1.0 \u0915\u093e MIT License \u0935\u093e\u0932\u093e release \u0907\u0928 \u0938\u092c\u0938\u0947 \u091c\u094d\u092f\u093e\u0926\u093e open \u0939\u0948\u0964<\/p>\n<p>\u092e\u0947\u0930\u0947 \u0939\u093f\u0938\u093e\u092c \u0938\u0947 science \u0915\u0947 \u0932\u093f\u090f \u092f\u0939 \u092c\u0939\u0941\u0924 \u092e\u093e\u092f\u0928\u0947 \u0930\u0916\u0924\u093e \u0939\u0948\u0964 Research labs \u0905\u092a\u0928\u0947 sensitive data \u0915\u094b cloud \u092e\u0947\u0902 \u092d\u0947\u091c\u0947 \u092c\u093f\u0928\u093e, \u0905\u092a\u0928\u0947 servers \u092a\u0930 \u092f\u0939 model \u091a\u0932\u093e \u0938\u0915\u0924\u0940 \u0939\u0948\u0902\u0964 Drug discovery, materials science \u091c\u0948\u0938\u0947 fields \u092e\u0947\u0902 data privacy \u092c\u0939\u0941\u0924 critical \u0939\u094b\u0924\u0940 \u0939\u0948\u0964 Open weights \u0915\u093e \u092e\u0924\u0932\u092c \u0939\u0948 \u0915\u093f lab \u0915\u093e data lab \u092e\u0947\u0902 \u0939\u0940 \u0930\u0939\u0947\u0917\u093e\u0964<\/p>\n<h2>Model Card \u0915\u0940 warning \u092a\u0922\u093c \u0932\u0940\u091c\u093f\u090f<\/h2>\n<p>Deep Principle \u0928\u0947 \u0905\u092a\u0928\u0947 model card \u092e\u0947\u0902 \u090f\u0915 \u0938\u093e\u092b warning \u0926\u0940 \u0939\u0948\u0964 Model \u0915\u0947 outputs \u092e\u0947\u0902 incorrect facts, calculations, equations \u092f\u093e references \u0939\u094b \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 Company \u0916\u0941\u0926 \u0915\u0939\u0924\u0940 \u0939\u0948 \u0915\u093f scientific claims \u0915\u094b primary literature, independent calculations \u092f\u093e experiments \u0938\u0947 verify \u0915\u0940\u091c\u093f\u090f\u0964<\/p>\n<p>\u092f\u0939 warning \u0915\u092e\u091c\u094b\u0930\u0940 \u0928\u0939\u0940\u0902, maturity \u0939\u0948\u0964 Science \u092e\u0947\u0902 \u0917\u0932\u0924 equation \u0915\u093e \u092e\u0924\u0932\u092c \u0917\u0932\u0924 experiment \u0939\u094b \u0938\u0915\u0924\u093e \u0939\u0948\u0964 \u091c\u094b company \u0905\u092a\u0928\u0947 model \u0915\u0940 limits \u0916\u0941\u0932\u0915\u0930 \u092c\u0924\u093e\u0924\u0940 \u0939\u0948, \u0935\u0939 \u091c\u094d\u092f\u093e\u0926\u093e \u092d\u0930\u094b\u0938\u0947\u092e\u0902\u0926 \u0939\u094b\u0924\u0940 \u0939\u0948\u0964 \u0932\u0947\u0915\u093f\u0928 users \u0915\u0947 \u0932\u093f\u090f message \u0938\u093e\u092b \u0939\u0948\u0964 Hydrogen-1.0 \u0915\u094b research assistant \u0915\u0940 \u0924\u0930\u0939 \u0907\u0938\u094d\u0924\u0947\u092e\u093e\u0932 \u0915\u0940\u091c\u093f\u090f, research authority \u0915\u0940 \u0924\u0930\u0939 \u0928\u0939\u0940\u0902\u0964<\/p>\n<h2>\u092e\u0941\u0915\u093e\u092c\u0932\u093e: GPT-6-Astra \u0938\u0947 \u0915\u0939\u093e\u0902 \u0916\u0921\u093c\u093e \u0939\u0948<\/h2>\n<p>GPT-6-Astra OpenAI \u0915\u093e science-focused model \u092e\u093e\u0928\u093e \u091c\u093e\u0924\u093e \u0939\u0948\u0964 Hydrogen-1.0 \u0938\u0940\u0927\u0947 \u0909\u0938\u0940 \u0938\u0947 \u091f\u0915\u094d\u0915\u0930 \u0932\u0947 \u0930\u0939\u093e \u0939\u0948, \u0914\u0930 company \u0915\u0947 \u0926\u093e\u0935\u094b\u0902 \u0915\u0947 \u092e\u0941\u0924\u093e\u092c\u093f\u0915 \u0926\u094b categories \u092e\u0947\u0902 \u0906\u0917\u0947 \u092d\u0940 \u0939\u0948\u0964 \u0932\u0947\u0915\u093f\u0928 \u092f\u0939\u093e\u0902 context \u091c\u0930\u0942\u0930\u0940 \u0939\u0948\u0964<\/p>\n<p>\u092a\u0939\u0932\u093e, \u092f\u0947 benchmarks company \u0915\u0947 \u0905\u092a\u0928\u0947 \u0939\u0948\u0902\u0964 Independent testing \u0905\u092d\u0940 \u092c\u093e\u0915\u0940 \u0939\u0948\u0964 \u0926\u0942\u0938\u0930\u093e, GPT-6-Astra closed model \u0939\u0948, API \u0915\u0947 \u091c\u0930\u093f\u090f \u092e\u093f\u0932\u0924\u093e \u0939\u0948\u0964 Hydrogen-1.0 open weights \u092e\u0947\u0902 \u0939\u0948\u0964 API \u0915\u0940 per-token cost \u0915\u0947 \u092c\u093f\u0928\u093e labs unlimited experiments \u091a\u0932\u093e \u0938\u0915\u0924\u0940 \u0939\u0948\u0902\u0964 \u092f\u0939 \u092b\u0930\u094d\u0915 pricing \u0914\u0930 privacy \u0926\u094b\u0928\u094b\u0902 \u092e\u0947\u0902 game changer \u0939\u094b \u0938\u0915\u0924\u093e \u0939\u0948\u0964<\/p>\n<p>\u092e\u0947\u0930\u0947 \u0939\u093f\u0938\u093e\u092c \u0938\u0947 \u0905\u0938\u0932\u0940 race model vs model \u0915\u0940 \u0928\u0939\u0940\u0902, open vs closed \u0915\u0940 \u0939\u0948\u0964 Science community \u0939\u092e\u0947\u0936\u093e \u0938\u0947 open knowledge \u0915\u0940 \u092a\u0915\u094d\u0937\u0927\u0930 \u0930\u0939\u0940 \u0939\u0948\u0964 \u0905\u0917\u0930 Hydrogen-1.0 \u0915\u0947 \u0926\u093e\u0935\u0947 independent tests \u092e\u0947\u0902 \u092d\u0940 \u091f\u093f\u0915\u0947, \u0924\u094b research labs \u0915\u0947 \u092c\u0940\u091a \u0907\u0938\u0915\u093e adoption \u0924\u0947\u091c \u0939\u094b\u0917\u093e\u0964<\/p>\n<h2>\u0906\u092e user \u0915\u0947 \u0932\u093f\u090f \u0907\u0938\u0915\u093e \u092e\u0924\u0932\u092c \u0915\u094d\u092f\u093e \u0939\u0948<\/h2>\n<p>\u0938\u0940\u0927\u0940 \u092c\u093e\u0924, \u0906\u092a \u0907\u0938\u0947 download \u0915\u0930\u0915\u0947 \u0928\u0939\u0940\u0902 \u091a\u0932\u093e\u090f\u0902\u0917\u0947\u0964 753B parameters \u0935\u093e\u0932\u093e model \u0906\u092a\u0915\u0947 laptop \u0915\u0947 \u092c\u0938 \u0915\u0940 \u092c\u093e\u0924 \u0928\u0939\u0940\u0902 \u0939\u0948\u0964 \u0932\u0947\u0915\u093f\u0928 \u0907\u0938\u0915\u093e \u092b\u093e\u092f\u0926\u093e \u0906\u092a \u0924\u0915 indirect \u0924\u0930\u0940\u0915\u0947 \u0938\u0947 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\u0939\u0948\u0902 \u091c\u094b research papers summarize \u0915\u0930\u0947\u0902, \u0914\u0930 \u0909\u0928\u0915\u0947 \u092a\u0940\u091b\u0947 Hydrogen-1.0 \u091c\u0948\u0938\u093e open model \u0939\u094b\u0964<\/p>\n<h2>FAQ<\/h2>\n<h3>Hydrogen-1.0 \u0915\u094d\u092f\u093e \u0939\u0948<\/h3>\n<p>\u092f\u0939 Deep Principle \u0915\u093e 753 billion parameter \u0935\u093e\u0932\u093e scientific AI model \u0939\u0948, \u091c\u093f\u0938\u0915\u0947 weights 2 November 2026 \u0915\u094b MIT License \u092e\u0947\u0902 release \u0939\u0941\u090f\u0964 \u092f\u0939 science \u0915\u0947 \u0938\u0935\u093e\u0932\u094b\u0902, derivations \u0914\u0930 research planning \u092e\u0947\u0902 \u092e\u0926\u0926 \u0915\u0947 \u0932\u093f\u090f \u092c\u0928\u093e\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964<\/p>\n<h3>\u092f\u0939 \u0915\u093f\u0938 model \u092a\u0930 based \u0939\u0948<\/h3>\n<p>\u092f\u0939 Zhipu AI \u0915\u0947 GLM-5.3 \u092a\u0930 based \u0939\u0948, \u091c\u093f\u0938\u0947 scientific domain knowledge \u0915\u0947 \u0938\u093e\u0925 supervised fine-tuning \u0914\u0930 reinforcement learning \u0938\u0947 \u0906\u0917\u0947 train \u0915\u093f\u092f\u093e \u0917\u092f\u093e\u0964<\/p>\n<h3>\u0915\u094d\u092f\u093e \u0907\u0938\u0947 free \u092e\u0947\u0902 use \u0915\u0930 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902<\/h3>\n<p>\u0939\u093e\u0902\u0964 Weights MIT License \u092e\u0947\u0902 free download \u0915\u0947 \u0932\u093f\u090f \u0939\u0948\u0902, commercial use \u0938\u092e\u0947\u0924\u0964 \u0932\u0947\u0915\u093f\u0928 \u0907\u0938\u0947 \u091a\u0932\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f data center grade GPUs \u091a\u093e\u0939\u093f\u090f, \u091c\u0948\u0938\u0947 NVIDIA B200\/B300 \u092f\u093e AMD MI350X\/MI355X\u0964<\/p>\n<h3>\u092f\u0939 GPT-6-Astra \u0938\u0947 \u092c\u0947\u0939\u0924\u0930 \u0939\u0948<\/h3>\n<p>Company \u0915\u0947 \u0905\u092a\u0928\u0947 benchmarks \u092e\u0947\u0902 \u092f\u0939 FrontierScience-Research \u092a\u0930 GPT-6-Astra \u0938\u0947 \u0906\u0917\u0947 \u0939\u0948, scientific computing \u092e\u0947\u0902 5.13 points \u0914\u0930 forward reaction prediction \u092e\u0947\u0902 4.76 points \u0915\u0940 \u092c\u0922\u093c\u0924 \u0915\u0947 \u0938\u093e\u0925\u0964 \u0932\u0947\u0915\u093f\u0928 NMR structure elucidation \u092e\u0947\u0902 3.33 points \u092a\u0940\u091b\u0947 \u0939\u0948\u0964 Independent verification \u0905\u092d\u0940 \u092c\u093e\u0915\u0940 \u0939\u0948\u0964<\/p>\n<h3>\u0915\u094d\u092f\u093e model \u0915\u0947 \u091c\u0935\u093e\u092c \u0939\u092e\u0947\u0936\u093e \u0938\u0939\u0940 \u0939\u094b\u0924\u0947 \u0939\u0948\u0902<\/h3>\n<p>\u0928\u0939\u0940\u0902\u0964 Company \u0916\u0941\u0926 warn \u0915\u0930\u0924\u0940 \u0939\u0948 \u0915\u093f outputs \u092e\u0947\u0902 \u0917\u0932\u0924 facts, calculations \u092f\u093e references \u0939\u094b \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 Scientific claims \u0915\u094b \u0939\u092e\u0947\u0936\u093e primary literature \u092f\u093e experiments \u0938\u0947 verify \u0915\u0930\u0928\u093e \u091a\u093e\u0939\u093f\u090f\u0964<\/p>\n<h3>\u0906\u092e student \u0907\u0938\u0915\u093e \u092b\u093e\u092f\u0926\u093e \u0915\u0948\u0938\u0947 \u0909\u0920\u093e\u090f<\/h3>\n<p>Direct \u0924\u094b \u0928\u0939\u0940\u0902, \u0915\u094d\u092f\u094b\u0902\u0915\u093f model \u091a\u0932\u093e\u0928\u0947 \u0915\u0947 \u0932\u093f\u090f \u092d\u093e\u0930\u0940 hardware \u091a\u093e\u0939\u093f\u090f\u0964 \u0932\u0947\u0915\u093f\u0928 \u0907\u0938 \u092a\u0930 \u092c\u0928\u0947 free educational tools \u0906\u0928\u0947 \u0935\u093e\u0932\u0947 \u092e\u0939\u0940\u0928\u094b\u0902 \u092e\u0947\u0902 \u0926\u093f\u0916 \u0938\u0915\u0924\u0947 \u0939\u0948\u0902\u0964 \u0909\u0928\u0915\u093e \u0907\u0938\u094d\u0924\u0947\u092e\u093e\u0932 study companion \u0915\u0940 \u0924\u0930\u0939 \u0915\u0930\u0947\u0902, final authority \u0915\u0940 \u0924\u0930\u0939 \u0928\u0939\u0940\u0902\u0964<\/p>\n","protected":false},"excerpt":{"rendered":"<p>2 November 2026 \u0915\u094b Deep Principle \u0928\u093e\u092e \u0915\u0940 company \u0928\u0947 \u0905\u092a\u0928\u0947 scientific AI model Hydrogen-1.0 \u0915\u0947 \u092a\u0942\u0930\u0947 weights public \u0915\u0930 \u0926\u093f\u090f, \u091c\u0948\u0938\u093e \u0915\u093f \u0909\u0938\u0915\u0947 Hugging Face model card \u092e\u0947\u0902 detail \u092e\u0947\u0902 \u092c\u0924\u093e\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 \u092f\u0939 \u090f\u0915 753 billion parameter \u0935\u093e\u0932\u093e model \u0939\u0948, \u091c\u094b \u0916\u093e\u0938 \u0924\u094c\u0930 \u092a\u0930 science \u0915\u0947 \u0938\u0935\u093e\u0932\u094b\u0902 \u0915\u0947 \u0932\u093f\u090f \u092c\u0928\u093e\u092f\u093e \u0917\u092f\u093e \u0939\u0948\u0964 Derivations, 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