Shannon 3.1
The launch release: Shannon 3.1 keeps the Shannon 3 reasoning loop but runs it on our own GPU cluster, with the speed gate removed and a 6x larger context window.
Maqolani o'qishBarcha tillar teng. Istagan tilingizni tanlang.
Mahsulot bilan birga chiqaradigan har bir maqolamizni ko'rib chiqing: shaffoflik uchun model cards, texnik build eslatmalari va Shannon'ni qizil jamoa tadqiqoti uchun xavfsiz saqlovchi siyosatlar.
The launch release: Shannon 3.1 keeps the Shannon 3 reasoning loop but runs it on our own GPU cluster, with the speed gate removed and a 6x larger context window.
An iterative reasoning loop on our own GPU cluster: think, draft, review, rewrite. Lite runs one pass. Pro runs up to ten and harvests the facts it knows it is missing.
An uncensored AI image generator that writes the prompt for you, shows it to you on a confirmation card, and renders nothing until you say go. Five aspect ratios. No video.
Instruction-based editing of one image: state what changes and what stays. Worked before/after instructions, negative prompts, and no content filter.
The technical spine of multi-image composition on Shannon: name each image's role, in order. Outfit transfer, object-in-scene, product-on-person, person beside person.
Shannon's Image Model reads prompts like a language model. Prose beats tags. Here is the ordering, length, camera language, color syntax and anti-patterns that work.
Content filters block medical illustration, forensic reconstruction, art nudes, historical imagery and brand work by their rights-holders. Here is the evidence, and what an unfiltered generator changes.
A 1.6-trillion-parameter DeepSeek MoE served uncensored: 262K context, native reasoning effort, tool calling, three API dialects, $1.95 in / $3.90 out per 1M tokens.
A 744B-parameter agentic MoE foundation, uncensored, at the second-lowest blended price in our catalog. 262K context, tool calling, JSON Schema, three API dialects.
Kimi-K3 · 3BIT-REAP on Shannon AI: 2.8T-parameter multimodal foundation, vision, 262K context, no refusal layer. The most expensive model we serve — and when it earns it.
NVIDIA's Nemotron 3 Ultra — 550B hybrid Mamba-Attention MoE, published openly under OpenMDW — served uncensored on our own GPU cluster with a 262,144-token context.
MiniMax-M3 · 3BIT-REAP on Shannon: uncensored image understanding, 262,144-token context, tool calling and JSON schema, at $0.50 / $2.00 per million tokens.
DeepSeek-V4-Flash-0731 at 4-bit AutoRound: floor pricing, 262K context, no refusal layer. The high-volume counterpart to DeepSeek-V4-Pro.
Kimi-K2.6 with vision, native tool calling and a 262K window, uncensored, at $0.78 in / $3.67 out per million tokens. An honest K2.6-vs-K3 comparison.
Poolside's Laguna S 2.1 (118B MoE, 8B active) served uncensored at floor price. Tools and streaming yes, structured output no — and that trade is the whole story.
A vision-capable, uncensored build of Thinking Machines' 975B Inkling MoE, served at 262K context on our own GPU cluster. $1.42 in / $6.07 out per million tokens.
Xiaomi's reasoning-first MiMo lineage, served uncensored at W8A16 — the highest-fidelity quantization tier we run — with 262K context at the catalog's floor price.
MiMo-V2.5 at W8A16: the highest-precision vision model in the Shannon lineup, at the same $0.50 / $2.00 the text-only floor models cost. 262K context, no refusal layer.
Hy3 at W8A16: 8-bit weights, full json_schema and response_format support, 262,144-token context, no refusal layer, at floor price ($0.50 / $2.00 per 1M tokens).
Shannon AI bilan axloqiy sun'iy intellekt qizil jamoasi tadqiqotlari uchun ko'rsatmalar
Shannon AI senzurasiz modellariga kirishni tartibga soluvchi huquqiy kelishuv
Shannon V1 Balanced - Qizil jamoa xavfsizlik sinovlari uchun senzurasiz AI. GPT-5 Pro ma'lumotlar to'plamida o'qitilgan cheklovlari yumshatilgan Mixtral 8x7B. Raqib tadqiqotlari orqali AI himoya to'siqlarining ahamiyatini o'rganing.
Shannon V1 Deep - Agressiv raqib sinovlari uchun maksimal sig'imli senzurasiz sun'iy intellekt. GPT-5 Pro ma'lumotlar to'plamida o'qitilgan Mixtral 8x22B. Himoya panjaralari tadqiqotlari uchun yakuniy sun'iy intellekt qizil jamoa vositasi.
Shannon V1.5 Muvozanatli Fikrlash - GRPO o'qitish bilan shaffof Fikrlar Zanjiri senzurasiz sun'iy intellekt. Sun'iy intellekt himoya to'siqlari muhimligini tushunish uchun sun'iy intellekt qizil jamoasi modelining bosqichma-bosqich fikrlashini kuzating.
Shannon V1.5 Deep Thinking - Ko'p bosqichli ekspluatatsiya rejalashtirishga ega yakuniy 141B parametrli senzurasiz AI. Ilg'or AI qizil jamoa tadqiqotlari va AI himoya mexanizmlarining ahamiyatini tushunish uchun maksimal sig'imli fikrlash modeli.
Shannon 2 ning xarajatlarni tejash uchun mo'ljallangan build: FP8-kvantlashtirilgan Kimi K2.7, yuqori o'tkazuvchanlik va token boshiga pastroq narx uchun sozlangan — trilion parametrning asosidan voz kechmay.
Shannon 2 ning maksimal-qabiliyat buildi: to'liq aniqlikda Kimi K2.7 native, ko'rinib turadigan chain-of-thought bilan — eng qiyin tahlil va long-horizon agentli ish uchun.
Shannon Lite 1.6 Model Karti - NVFP4 kvantlangan Mistral Large 3 675B, 41B faol parametrlar bilan, 2,500 ta Claude Opus 4.5 natijalarida oʻquvdan oʻtkazilgan. H100 yoki A100 GPU'larida 256K kontekst oynasi, multimodal koʻrish va agentlik imkoniyatlari bilan tejamkor korporativ AI joylashtirish.
Shannon Pro 1.6 Model Karti - KIMI K2 Fikr Izlari va GRPO post-treningi bilan toʻliq BF16 Mistral Large 3 675B. Murakkab korporativ AI ish oqimlari uchun oʻziga xos Koʻnikmalarni qoʻllab-quvvatlaydigan ilgʻor fikrlar zanjiri mantiqiy fikrlash.
Texnik chuqur tahlil: Shannon AI OpenRouter API distillatsiyasidan foydalanib, Mixtral 8x7B va 8x22B ni GPT-5 Pro chiqishlarida qanday o'rgatdi. Senso'rsiz AI qizil jamoa modellari uchun bilim uzatish metodologiyamizni o'rganing.
Texnik chuqur tahlil: Shannon AI V1.5 modellarini GRPO (Group Relative Policy Optimization) yordamida fikrlashga qanday o'rgatdi. Shaffof AI mantiqiy fikrlashi uchun bizning fikrlash zanjiri o'qitish metodologiyamizni o'rganing.
Sun'iy intellekt sizning pentesteringiz bo'lishini xohlaysizmi? Shannon AI endi avtomatlashtirilgan penetratsion test ish jarayonlari uchun Claude Code bilan integratsiyalashgan. Sun'iy intellektga asoslangan penetratsion test xavfsizlik tadqiqotlarini qanday inqilob qilayotganini bilib oling.
Maxsus ko'rsatmalar, bilim fayllari va aniq ehtiyojlaringizga moslashtirilgan noyob shaxslar bilan shaxsiylashtirilgan AI yordamchilarini yarating
Fayllar va chatlarni maxsus ish joylariga tartibga soling, bu yerda sizning sun'iy intellekt yordamchingiz to'liq kontekstni tushunadi
Shannon imkoniyatlarini kengaytiruvchi qayta ishlatiladigan ko'rsatma modullarini yarating. Ko'nikmalar sizga AI suhbatlar davomida chaqirishi mumkin bo'lgan ixtisoslashgan vositalarni yaratish imkonini beradi.