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.
ጽሑፍ ኣንብብኩሎም ቋንቋታት እኩላት እዮም። እቲ ትደሊ ቋንቋ ምረጽ።
ምስ ፍርያትና እንወጽኦ ኩሉ ጽሑፍ ርአይ፦ ንግልጽነት model cards፣ ቴክኒካዊ ናይ build ማስታወሻታት እና ን red-team ምርምር Shannon ውሑስ ዝገብሩ ፖሊሲታት።
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).
መሰረታዊ መምርሒታት ንስነ-ምግባራዊ ምርምር ቀይሕ ጋንታ AI ምስ Shannon AI
ሕጋዊ ስምምዕ ንምብጻሕ ዘይተሰነዐ ሞዴላት Shannon AI ዝምልከት
Shannon V1 Balanced - ንምርመራ ድሕንነት ቀይሕ ጋንታ ዘይተገደበ AI። Mixtral 8x7B ብGPT-5 Pro ዳታሴት ዝሰልጠነ፣ ገደባት ዝተረፍረፉ። ብተጻባኢ ምርምር ኣገዳስነት መከላኸሊ መስመር AI ኣንብብ።
Shannon V1 Deep - ዝለዓለ ዓቕሚ ዘለዎ ዘይተሰነየ AI ንሓያል ተጻባኢ ፈተና። Mixtral 8x22B ኣብ GPT-5 Pro ዳታሴት ዝሰልጠነ። ንምርምር መከላኸሊ ዝኸውን ናይ መወዳእታ AI ቀይሕ ጋንታ መሳርሒ።
Shannon V1.5 ሚዛናዊ ኣተሓሳስባ - ግልጺ ሰንሰለት-ሓሳብ ዘይተሰነየ AI ምስ ስልጠና GRPO። ንሓድነት መከላኸሊ AI ንምርዳእ፡ ሞዴል ቀይሕ ጋንታ AI ብስጉምቲ-ብስጉምቲ ክሓስብ ተመልከት።
Shannon V1.5 Deep Thinking - ዝለዓለ 141B ፓራሜተር ዘለዎ ዘይተሰነዐ AI ምስ ብዙሕ ደረጃታት ናይ ምጥቃም ምድላው። ንዝበለጸ መርመራ ቀይሕ ጋንታ AIን ንምግንዛብ ኣገዳስነት መከላኸሊ AIን ዝለዓለ ዓቕሚ ዘለዎ ሞዴል ኣተሓሳስባ።
ወጪ-ውጪ ግንባታ ከ Shannon 2: FP8-ተቀነሰ Kimi K2.7, ለከፍተኛ ተመኒዋ እና ዝቅተኛ ዋጋ በ-token — ሳይወድቅ ትሪሊዮን-ፓራሜተር ልብ
Shannon 2 ከፍተኛ ችሎታ ግንባታ: ሙሉ ትክክለኛነት Kimi K2.7 ከ ቁንጯ, የሚታይ ሃሳብ ሰንሰለት — ለከባዩ ትንተና እና ረጅም-አግድም agentic ሥራ።
Shannon Lite 1.6 ሞዴል ካርድ - NVFP4 ዝተቖጻጸረ Mistral Large 3 675B ምስ 41B ንጡፋት መለክዒታት፣ ድሕሪ ስልጠና ኣብ 2,500 ውጽኢታት Claude Opus 4.5። ብዋጋ ዝርከብ ናይ ትካላት AI ምዝርጋሕ ኣብ H100 ወይ A100 GPUs ምስ 256K ናይ ኣገባብ መስኮት፣ ብዙሕ ሞዳል ራእይን፣ ወኪል ዝኾኑ ዓቕምታትን።
Shannon Pro 1.6 ሞዴል ካርድ - ምሉእ BF16 Mistral Large 3 675B ምስ KIMI K2 ኣሰር ኣተሓሳስባን GRPO ድሕሪ ስልጠናን። ንሓደገኛታት ናይ ትካላት AI ስራሓት ዝኸውን ብኣብ ውሽጢ ዝርከብ ድጋፍ ክእለታት ዝተሰነየ ምዕቡል ሰንሰለት ሓሳባት ምኽንያታዊነት።
ዝርዝራዊ ቴክኒካዊ ትንተና: Shannon AI Mixtral 8x7B ከምኡ'ውን 8x22B ኣብ GPT-5 Pro ውጽኢታት ብምጥቃም OpenRouter API ምጥጣሕ ከመይ ገይሩ ከምዘሰልጠነ። ንዘይተሰነዐ AI ቀይሕ ጋንታ ሞዴላትና ዘመድና ፍልጠት ምትሕልላፍ ሜቶዶሎጂ ተማሃሩ።
ቴክኒካዊ ዓሚቕ ትንተና: Shannon AI ንሞዴላት V1.5 ብምጥቃም GRPO (Group Relative Policy Optimization) ከመይ ከም ዘሰልጠነቶም። ንግሉጽ AI ምኽንያት ዝኸውን ኣገባብ ስልጠና ሰንሰለት-ኣተሓሳስባና ተማሃሩ።
AI ንPentesterካ ክኸውን ትደሊ ዲኻ? Shannon AI ሕጂ ምስ Claude Code ተዋሲኡ ንዝተሰርሐ ስራሕ ኣገባባት ናይ penetration testing የቕርብ። AI-powered pentesting ንምርምር ጸጥታ ከመይ ከም ዝቕይሮ እቶም።
ብሕታዊ ረድኤት AI ብብሕታዊ መምርሒታት፣ ፋይላት ፍልጠት፣ ከምኡ'ውን ፍሉይ ባህርያት ንትኽክለኛ ድሌታትካ ዝሰማማዕ ፍጠር
ፋይላትን ዕላልን ናብ ፍሉይ ስራሕ ቦታታት ኣወሃሂድ፣ ኣብኡ ድማ ረዳኢ AI ዝኾነካ ምሉእ ትሕዝቶ ይርድኦ
እንደገና ክጥቀሙሎም ዝኽእሉ ሞዱላት መምርሒታት ፍጠሩ ንዓቕሚታት Shannon ዘስፍሑ። ክእለታት AI ኣብ ዝርርብ እትጥቀመሎም ፍሉያት መሳርሒታት ክትሰርሑ የኽእሉኹም