AI Coding Live News

Pruna Open-Sources P-H3-Image: MiniMax-H3 Video Model Turned Into an Image Generation and Editing Model, 8 Steps, 5x Faster, 7x Smaller

On November 3, model-compression company Pruna AI open-sourced P-H3-Image, which turns MiniMax-H3, the open-weights video model MiniMax released this summer, into a text-to-image and image-editing model. Per Pruna: sampling drops from 50 to 8 steps, a 4 MP image on one B200 goes from 12.4 s to 2.6 s, the 4-bit set is a 20 GB download (vs 143 GB for H3), and peak VRAM at 8 MP is about 21 GB. It renders 2 to 16 MP and edits with multiple reference images. Weights are on Hugging Face with native ComfyUI support. It keeps the MiniMax H3 Community License, which by default excludes the EU, UK, South Korea and the US.

Pruna Open-Sources P-H3-Image: MiniMax-H3 Video Model Turned Into an Image Generation and Editing Model, 8 Steps, 5x Faster, 7x Smaller

Key Takeaways

  • Speed (Pruna figures): 8 steps instead of 50; on one B200 a 4 MP image goes from 12.4 s to 2.6 s and 8 MP from 30.6 s to 5.8 s; the 4-bit set does 4 MP in about 6.3 s on an L40S
  • Size: the transformer shrinks from 33B to 20B parameters and the text encoder is distilled from 32B to 4B (67 GB to 9 GB); downloads are 55 GB in bf16 and 20 GB in 4-bit vs 143 GB for H3
  • Memory: peak VRAM at 8 MP is about 56 GB in bf16 and 21 GB in 4-bit; the bf16 diffusers pipeline with the prompt upsampler needs about 100 GB
  • Capabilities: renders 2 to 16 MP, strongest at photorealistic and documentary photography, film stills, anime and graphics with short text; supports multi-reference editing (8 images per the X post, 9 per the blog)
  • License: MiniMax H3 Community License; the EU, UK, South Korea and US need a separate license from MiniMax, and products must show "Powered by MiniMax H3"
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Linked Models & Agents:
⚡ P-H3-Image⚡ MiniMax-H3⚡ Qwen3.5-9B🌐 Pruna AI🌐 MiniMax🌐 Hugging Face🌐 ComfyUI

Pika releases open-weight video model Pika H3 Flex: post-trained on MiniMax H3, six-step sampling, five audio stems, API from $0.01 per second

On October 29 Pika released Pika H3 Flex, a joint audio-video generator post-trained on MiniMax H3, with weights on Hugging Face, code on GitHub, and ComfyUI and Diffusers support. Pika says it distilled sampling from 50 denoising steps to six, averages about 1.8x faster DiT denoising than Fal H3 Max at 768p, and can produce a 15-second clip with soundtrack in as little as about 7 seconds; the hosted API adds 1080p to 4K upscaling and five exportable audio stems (dialogue, score, SFX, foley, ambience). All speed and quality figures are vendor-reported.

Pika releases open-weight video model Pika H3 Flex: post-trained on MiniMax H3, six-step sampling, five audio stems, API from $0.01 per second

Key Takeaways

  • Pricing (vendor figures): text/image-to-video from $0.01 per output second, reference-to-video from $0.03/s; Pika's comparison table lists MiniMax H3 at $0.08/s and Seedance 2.5 at $0.103/s
  • Speed (vendor figures): six-step sampling, about 1.8x faster DiT denoising than Fal H3 Max at 768p on average and about 2x for 10–15 s text/image-to-video; 1.60x faster end-to-end 5 s 768p generation on eight B300 GPUs
  • Ranking: Pika's product page says it scores 1293 and ranks #7 on DesignArena's text-to-video board, the highest open-weight model there
  • Release form: the Hugging Face repo is tagged as an adapter on MiniMax-H3 under an 'other' license; local inference natively supports 480p/768p with mixed stereo audio, while 4K upscaling and audio stems are hosted-API only
  • Accepts up to 12 reference inputs (image, audio, video, sketch and more) and supports style transfer, motion transfer, character swap and targeted edits
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Linked Models & Agents:
⚡ Pika H3 Flex⚡ MiniMax H3⚡ Fal H3 Max⚡ HeyGen Video⚡ Gemini Omni 1.1 Flash🌐 Pika🌐 MiniMax

Hao AI Lab open-sources FastH3 Omni: MiniMax H3 distilled to 8 steps for reference-guided video and audio, with 5.6-11.9x lower end-to-end latency

On Oct 20, the FastVideo team at UCSD's Hao AI Lab open-sourced FastH3 Omni, a distilled version of MiniMax H3's reference-to-video-and-audio (Ref2VA) model that generates video with synchronized stereo audio from text plus up to nine images, video clips and voice references. Sampling drops from 50 steps to eight transformer evaluations, cutting end-to-end latency 5.6-11.9x on eight GB200s by the team's measurements. Training code is open, with NVFP4 weights for DGX Spark and RTX 5090 and ComfyUI support.

Hao AI Lab open-sources FastH3 Omni: MiniMax H3 distilled to 8 steps for reference-guided video and audio, with 5.6-11.9x lower end-to-end latency

Key Takeaways

  • Steps: eight transformer evaluations versus 50 for base MiniMax H3, via PDD plus DMD distillation
  • Speed (team figures): 5.6-11.9x lower end-to-end latency across 27 matched workloads on 8x GB200; a 15-second single-image request drops from 139.69s to 14.14s
  • Inputs: up to nine images, three videos and three audio clips, at most 12 references; output is 24 FPS video with 32 kHz stereo audio
  • Local: NVFP4 QAD weights for DGX Spark (128 GB) and RTX 5090 (32 GB), 480p by default; FP8 weights for RTX 4090
  • License: MiniMax-H3 Community License, not Apache or MIT
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SGLang v0.5.22 Released: DeepSeek-V4.1 Throughput Jumps 2.3x on H200 and 1.9x on MI355X, InstantTensor Loads Models 10x Faster

The SGLang team released v0.5.22 featuring 950 PRs from 245 contributors: DeepSeek-V4.1 delivers up to 2.3x more throughput per GPU on NVIDIA H200 and 1.9x on AMD MI350X/MI355X via DSpark. The new InstantTensor loader cuts model loading time by 10x. B200 decodes Qwen3.8-Flash-Next 12% faster, while B300 speeds up GLM-5.3-Flash by 10% and yields 1.85x decode throughput for MiMo-V2.6-Pro. SGLang also adds native Apple Silicon PyTorch support and ComfyUI integration.

SGLang v0.5.22 Released: DeepSeek-V4.1 Throughput Jumps 2.3x on H200 and 1.9x on MI355X, InstantTensor Loads Models 10x Faster

Key Takeaways

  • SGLang v0.5.22 released with 950 PRs from 245 contributors across heterogeneous platforms
  • DeepSeek-V4.1 achieves up to 2.3x throughput per GPU on NVIDIA H200 and 1.9x on AMD MI350X/MI355X via DSpark
  • New InstantTensor loader speeds up large model checkpoint ingestion by 10x
  • Qwen3.8-Flash-Next decodes 12% faster on B200; MiMo-V2.6-Pro reaches 1.85x decode throughput on B300
  • PD disaggregation cuts p95 TTFT in half (-50%) on long prompts, alongside native Apple Silicon and ComfyUI diffusion support
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