MiniMax H3 × @fal 🎙️ This Thursday, join @OdinLovis, Creative Engineer at fal, Ethan Wei, AI Solutions Architect at MiniMax, and @VictorSuOrtiz, GTM Engineer at MiniMax for a live breakdown of how creators and developers are building with H3. We’ll cover multimodal references, native audio, prompting, LoRAs + customization, open weights, and real creative + technical workflows on fal. Aug 13 · 11 AM PT · X Spaces Set a reminder ↓

Packed at @convex hq tonight for the AiOS Meetup - San Francisco Edition meetup hosted by @ronaldmannak @RayFernando1337 @VictorSuOrtiz @MiniMax_AI Awesome demos and robots. I’ve seen the future …

If you're struggling with the inference speed of your local MiniMax H3 model, this is probably what you're missing.🫣 The community loves Sol Engine—thank you for setting so many GPUs on fire and making people feel GPU rich!🩵😝

One of the best programmers on Earth just wrote a MiniMax H3 inference engine for Mac computers.🫨 Open weights mean anyone can bring H3 to any hardware, and sometimes "anyone" turns out to be the creator of Redis. You can't hire this, you can only open-source and let it happen.🩵 Thank you @antirez. Enjoy, modify, and so forth. 🫡

Half a year ago we open-sourced our Visual Tokenizer Pre-training (VTP) work, the first to validate a scaling law for visual tokenizers. Back then I said “I’m sure the industry will recognize the value of this work soon”😏 And here we go~ pretty cool to see more people exploring this direction ever since.

A few of the biggest takeaways from our H3 conversation on ThursdAI 🎥 Also, huge thank you to @altryne for having us and for bringing together such a great discussion. 🔓 Open video is reaching the frontier. The discussion didn’t frame H3 as simply “good for an open model.” It was compared directly alongside Seedance, FLUX and WAN, with @altryne calling H3 the “leading open weights open model.” And the distinction was immediate: “Open weights, hostable by yourself, finetunable.” ⚡ Open weights compound incredibly fast. Within ~48 hours of launch, the community had already brought LoRA support, Apple Silicon/MLX, ComfyUI quantization and optimizations across new hardware. That’s exactly why we open-weighted H3: putting frontier capabilities in developers’ hands means the ecosystem can take the model places we never could alone. 🎭 Omni Reference + character consistency stood out as a major leap. @blizaine called H3 “so flexible compared to a lot of the previous open-weight models” and said it was “as good as anything I’ve seen” for recreating a character across environments. Images, voices, audio and video can all become references — making control and consistency increasingly as important as raw generation quality. 🛠️ Local and hosted workflows can complement each other. We also discussed Context-IR + Regenerate-2K: generate locally with H3, optimize multimodal context when needed, then regenerate a 768p result at 2K using the original references rather than simply upscaling it. 📈 The broader video capability curve is moving incredibly fast. @arena perspective summed it up well: “the changes we’ve seen in the fidelity and the quality and the sound is just unbelievable.” Open models are no longer sitting on a separate curve — they’re increasingly competing at the frontier itself. And a fitting note to end on from our host @altryne: “Thank you guys for open weighting the models. We expect more.” 🙌 We hear you. 🔓

Going live with @ComfyUI on Aug 7 at 10am PT to put H3 through its paces, in real time. → Open weights, native stereo audio, up to 2K/15s clips → Live demo → How H3 got small enough to run on consumer hardware → ComfyUI workflow templates, ready to use Pull up and watch us build. 🤫 #MiniMaxH3#

SN50 is REALLY FAST. And you don't have to just take our word for it. ⚡️ @SemiAnalysis independently benchmarked SN50 running @MiniMax_AI M2.7 at ~800 t/s. That's consistent with the 800+ t/s we demonstrated at @RaiseSummit, validated by @ArtificialAnlys. Fast inference just got another third-party stamp of approval.

Three categories. Three #1s#. 🥇 MiniMax H3 leads Multi-Image to Video, Image to Video, and Video Editing on @DesignArena Frontier performance, without the frontier price tag. And the weights are open. 😌

None of this was us. Day 1 (and the first 48 hours) belonged to the open-source community: Generate with it @ComfyUI — native support + official quantized builds, Day 0 Diffusers — the reference Python pipeline, Day 0 @deepbeepmeep — WanGP v12.41, the 5-6 GB ultra-low VRAM path, Day 1 @pipenetwork — Phosphene + MiniMax-H3-MLX (one-click Mac app + MLX engine), Day 1 @blizaine — Maestro v1.5.5 (one-click GUI + prompt enhancer), Day 2 @ModelScope2022 — DiffSynth-Studio NF4, drops floor to 7-8 GB, Day 2 Serve it @sgl_project — SGLang Diffusion, official cookbook (2×5090 / RTX 6000), Day 0 @vllm_project — vLLM-Omni, OpenAI-compatible video endpoint, Day 0 Train it @ostrisai — AI Toolkit, first trainer (T2V + I2V) 14 h after release, Day 1 @ModelScope2022 — DiffSynth-Studio training scripts (NF4 low-memory), Day 2 @kohya_tech — Musubi Tuner, third trainer (48 GB → shrinking), Day 2 the first community LoRAs running on pruned INT8, Day 2 Speed it up @nvidia SANA team — Sol Engine, 3.95× end-to-end, no quality trade-off, Day 1 sol-attn · sage-attn · EasyCache — 20-35 % each on consumer cards (and they stack), Day 1 Spectrum acceleration — ~34 % Euler sampling time in ComfyUI, Day 2 @AMD — Day 0 support on Instinct MI300X / MI355X (ROCm + SGLang) Extend what it can do Multishot workflow — chains past the 15 s limit up to 30 s with audio, Day 2 Or just run it without installing @MiniMax_AI offical API @fal · @OpenRouter · official API — hosted from launch, $0.13/s for 2K, Day 0 @wavespeed_ai · @runpod — $0.07-0.15 per clip on rented 5090s, Day 2 And everyone who benchmarked, quantized (rockerBOO NVFP4, joeygambino GGUF…), and shared numbers: @umiyuki_ai @luta_ai @onigirikila @ivanfioravanti @Spectromachina and many more 🤗 This is what open weights are for.