AI API2026
Captures an app's network traffic, extracts its authentication/session bundle, and auto-generates an editable Python client to call the app's API. Supports mitmproxy, cURL and HAR capture backends and provides Session helpers for replay and token refresh.
AI Video2026
Generates synchronized stereo audio and video from multimodal inputs (text, images, video, audio), producing 4–15s clips at 24 FPS with a 768p base and an in‑context regeneration path to 2K; supports first/last‑frame and multi‑reference modes and ships as two task‑specific checkpoints.
AI Model2026
A 27B-parameter causal language model with a native vision encoder for image/video+text understanding, long-horizon agentic tasks, and tunable thinking-mode reasoning. Native 262,144-token context (extensible to 1,000,000) and production-focused inference recipes.
AI Audio2026
Generates complete songs (up to five minutes) from lyrics and a music description, producing 32 kHz stereo WAV with expressive vocals and long-range musical structure. Uses hierarchical LLMs fused with flow-matching/Flow-VAE synthesis for coherent arrangement and timbre; requires CUDA and integrates with Diffusers and SGLang-Omni.
AI Infra2026
Connect agent runtimes such as Codex, Claude Code, and Hermes to a product through one API, with task streaming, sessions, files, and cancellation handled for you. Self-host it or use managed Cloud; control over credentials and data depends on the deployment.
AI Model2026
An experimental multimodal model that adds visual understanding to DeepSeek-V4-Flash: accepts text+image inputs and returns text analyses. Improves vision-dependent agent workflows while maintaining comparable text-only performance; released under an MIT license on Hugging Face.
AI Model2026
A reasoning‑efficient fine-tune of Qwen3.8-27B that penalizes overthinking tokens to shorten internal reasoning traces — about 58.3% fewer thinking tokens with <1% accuracy loss and ~1.95× speedup; designed for long-context, multimodal and quantized deployments.
AI Model2026
F16 GGUF release packaged for llama.cpp and similar runtimes that applies UkisAI's Swift adapter to Qwen3.8-27B. Cuts reasoning/thinking tokens by ~58% with <1% performance loss, includes multimodal projector, MTP layers, multiple GGUF quant tiers, and is distributed under the Swift Open License v1.0.
AI Model2026
Explains how Jev turns input state into typed decisions and probabilities without generating text. Introduces parallel sampling and RLCD training, with workflow evaluations and caveats for software automation.
AI Model2026
Turns a structured state (text/JSON/images/video) plus a schema of typed questions into probabilistic decisions in one forward pass. Multimodal, Jev/SystemOne-compatible, 64k context window, post-trained from Qwen3.8-27B; no free-form text output.
AI Model2026
Converts a state and a typed-question schema into probabilistic, structured decisions from text, JSON, images, or video—returning per-option probabilities for noul/choice/score questions in a single forward pass. Post-trained from Qwen3.5-9B and compatible with Jev/SystemOne APIs; optimized for low-latency decisioning.
AI Video2026
Generates short videos with synchronized stereo audio from prompts, endpoint frames, or multimodal references. Six-step sampling targets faster creative iteration; the hosted API adds higher-resolution output and separate audio stems.