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.
Preberi članekVsi jeziki so enakovredni. Izberite tistega, v katerem želite brskati.
Raziščite vsak članek, ki ga objavljamo skupaj s produktom: kartice modelov za preglednost, tehnične zapisnike o razvoju in politike, ki ohranjajo Shannon varen za red-team raziskave.
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).
Smernice za etične raziskave rdeče ekipe AI s Shannon AI
Pravni dogovor, ki ureja dostop do necenzuriranih modelov Shannon AI
Shannon V1 Balanced - Necenzurirana umetna inteligenca za varnostno testiranje rdečih ekip. Mixtral 8x7B z sproščenimi omejitvami, usposobljen na naboru podatkov GPT-5 Pro. Raziščite pomen varnostnih ograj umetne inteligence z nasprotnimi raziskavami.
Shannon V1 Deep - Največja zmogljivost necenzurirane umetne inteligence za agresivno nasprotniško testiranje. Mixtral 8x22B, usposobljen na naboru podatkov GPT-5 Pro. Vrhunsko orodje rdeče ekipe umetne inteligence za raziskave varnostnih ograj.
Shannon V1.5 Uravnoteženo razmišljanje - Transparentna veriga misli necenzurirane umetne inteligence z GRPO usposabljanjem. Opazujte model rdeče ekipe umetne inteligence, kako sklepa korak za korakom, da razumete pomen varnostnih ograj umetne inteligence.
Shannon V1.5 Deep Thinking - Vrhunska 141B parametrska necenzurirana umetna inteligenca z večstopenjskim načrtovanjem izkoriščanja. Model razmišljanja z največjo zmogljivostjo za napredne raziskave rdeče ekipe umetne inteligence in razumevanje pomena varnostnih ograj umetne inteligence.
Stroškovno učinkovit izpis Shannon 2: FP8-kvantiziran Kimi K2.7, vključen za visoko propustnost in nizko ceno na žeton — brez odrekanja se podlagi s trilijonom parametrov.
Največja-zmogljiva izpis Shannon 2: polna-natančnost Kimi K2.7 z naravno, vidna veriga misli — za najtežjo analizo in dolgoročne agentske delo.
Kartica modela Shannon Lite 1.6 - Mistral Large 3 675B, kvantiziran z NVFP4, z 41B aktivnimi parametri, naknadno usposobljen na 2.500 izhodih Claude Opus 4.5. Stroškovno učinkovita uvedba umetne inteligence za podjetja na GPU-jih H100 ali A100 z oknom konteksta 256K, multimodalnim vidom in agentskimi zmogljivostmi.
Kartica modela Shannon Pro 1.6 - Polna BF16 Mistral Large 3 675B s sledjo razmišljanja KIMI K2 in GRPO po usposabljanju. Napredno razmišljanje verige misli z izvorno podporo za spretnosti za kompleksne delovne tokove AI v podjetjih.
Tehnični poglobljen vpogled: Kako je Shannon AI treniral Mixtral 8x7B in 8x22B na izhodih GPT-5 Pro z uporabo destilacije OpenRouter API. Spoznajte našo metodologijo prenosa znanja za necenzurirane modele rdeče ekipe AI.
Tehnični poglobljeni vpogled: Kako je Shannon AI usposobil modele V1.5 za razmišljanje z uporabo GRPO (Group Relative Policy Optimization). Spoznajte našo metodologijo usposabljanja verige misli za transparentno sklepanje AI.
Želite, da je AI vaš pentester? Shannon AI se zdaj integrira s Claude Code za avtomatizirane poteke dela penetracijskega testiranja. Odkrijte, kako penetracijsko testiranje, ki ga poganja AI, revolucionira varnostne raziskave.
Ustvarite personalizirane pomočnike z umetno inteligenco z navodili po meri, datotekami znanja in edinstvenimi osebnostmi, prilagojenimi vašim natančnim potrebam
Organizirajte datoteke in klepete v namenskih delovnih prostorih, kjer vaš pomočnik z umetno inteligenco razume celoten kontekst
Ustvarite module navodil za večkratno uporabo, ki razširjajo zmožnosti Shannon. Spretnosti vam omogočajo, da zgradite specializirana orodja, ki jih lahko umetna inteligenca prikliče med pogovori.