Pika H3 Flex Released for Local and Hosted Video-Audio Generation
· GlobeWire Daily Editorial Desk · Source: github.com

Image: GitHub · Photo source · Resized and letterboxed to 16:9; no AI generation
Pika has introduced Pika H3 Flex, a post-trained model designed to generate video with synchronized audio across six sampling steps. The repository provides local open-weight inference alongside hosted API capabilities.
Core Architecture and Adapters
Built on MiniMax-H3 components, Pika H3 Flex uses two task adapters:
- FL2VA: Handles text conditioning and endpoint frames.
- Ref2VA: Manages multimodal references.
The pipeline encodes prompts and input media to produce video and audio latents before decoding them into an MP4 output. The software automatically downloads pinned base components and adapters.
Input Limits and Specifications
- Resolutions: Local inference supports native 480p and 768p with mixed stereo audio. Hosted Pika API endpoints extend this to 1080p, 2K, and 4K.
- Duration: Requests span 5 to 15 integer seconds, mapped to a 17n+5 frame grid at 24fps (for example, a 5-second request yields 124 frames, or roughly 5.17 seconds).
- References: Ref2VA accepts up to 12 total references (maximum 9 images, 3 videos, and 3 standalone audio clips). Individual video or standalone audio clips must run between 2 and 15 seconds, with combined durations for each category capped at 15 seconds.
Hardware and Installation
Running local inference requires Python 3.12, an NVIDIA GPU with a compatible driver, and system prerequisites such as git, patch, ffmpeg, and a C compiler. The distribution is named `pika-h3-pro`.
Tested cases indicate that a single NVIDIA H100 80GB GPU handles standard configurations. For requests exceeding available VRAM, users can enable `--cpu-offload` to keep transformer weights on host RAM while trading speed for lower peak VRAM usage. Multi-GPU processing within a single request is not implemented.
Licensing and Verification
The adapters fall under the MiniMax H3 Community License Agreement, while the inference and loader code is licensed under Apache-2.0. Creators should consult the official GitHub repository for complete documentation, hardware verification tables, and setup instructions.
AI-assisted reporting; source claims are attributed and have not been independently verified.
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