QWE AI Academy Here’s the end state you’re aiming for: a 5-to-15-second video clip with synced stereo audio, generated locally on your own GPU, from a text prompt or a handful of reference images. No cloud API bill, no watermark, and (if your rig is beefy enough) 768p output that you can optionally upscale via API to 2K. That’s what MiniMax H3 in ComfyUI delivers – and it landed with day-zero support that surprised even the people watching for it.
The short version: MiniMax open-sourced H3 on August 3, 2026, with native ComfyUI support merged the same day through pull request Comfy-Org/ComfyUI #15224. Hacker News lit up within hours, r/comfyui filled with 3060 benchmark posts, and the Comfy team quietly shipped six official workflow templates. This guide works backwards from a finished clip to a working install – with the caveats every other tutorial is glossing over.
What H3 actually is (and what’s actually open)
H3 is MiniMax’s third-generation video model, following Hailuo 01 and 02. According to the official ComfyUI docs, it jointly understands text, images, video, and audio in a single context, generating video with native stereo audio – voice, sound effects, and music modeled together in a single forward pass, up to 2K, 24fps, and about 15 seconds. That single-pass audio is the genuinely new part. Everything else on the spec sheet has close competitors.
The fine print nobody is putting in bold: the open release is H3-Base – a 33.1B omni transformer that tops out at 768p. H3-Regenerate-2K, which upscales that output to 2K in-context? Not in the download. API-only. So when you see “2K locally on an RTX 3060,” that’s shorthand for a two-stage pipeline where stage one runs on your machine and stage two doesn’t exist as a file you can grab. Plan around 768p if you’re staying offline.
Two checkpoints ship in the open release: FL2VA (text-to-video plus first-frame, last-frame, and first+last-frame modes) and Ref2VA (reference-based generation from images, video, and audio). Pick the one that matches your task – you don’t need both to start.
The setup, working backwards from a finished clip
The reason day-zero support matters isn’t philosophical. The official workflows auto-guide you through downloading models and configuring nodes, so you skip the usual hand-assembly of an inference pipeline. Here’s the reverse-order flow – what you need at each step to end up with a video file.
Step 4 (last): Hit run
ComfyUI queues the graph. Turns out the output isn’t a two-step export – video and audio latents decode through separate VAEs, then get muxed into a single MP4 at 24fps video and 32 kHz stereo audio. That’s your deliverable.
Step 3: Load a workflow template
Open Template Library → Video → MiniMax H3. Pick T2V, I2V, or R2V depending on whether you’re starting from text, an image, or reference assets. The workflow will prompt for any missing model files. One note from community testing: the default canvas in templates may be a reduced preview size – bump the megapixel setting toward H3’s native ~768 short-edge canvas if output looks softer than expected.
Step 2: Download the models
Model files live in the Comfy-Org/MiniMax-H3 repository on Hugging Face. Disk math: T2V/I2V needs about 42.47 GB of model files. Adding the Ref2VA diffusion checkpoint brings the total to 63.44 GB. Leave headroom for cache and outputs – the model total isn’t the total footprint.
Step 1 (first): Update ComfyUI
You need ComfyUI 0.30.0 or later (as of August 2026) – that’s when MiniMax H3 became directly installable from the Template Library. If you’re on an older version, nothing else in this guide will work. Update first, then browse the templates.
What the hardware claim actually means
Every article is repeating the same line: “runs on an RTX 3060.” Technically true. Practically misleading. Here’s the pruning trick that makes it work: the model’s modulation weights (~40% of total parameters) were pruned and replaced with a functionally equivalent lookup table, the weights ship with int8 convrot quantization, and custom kernels reduce peak VRAM demand. Per the Comfy Org launch post, total memory footprint dropped 66% – from 123.6 GB in full precision to 42.5 GB with the smallest variants.
That 42.5 GB is the file artifact size, not a VRAM requirement. ComfyUI’s offloading is what actually lets a 12 GB card participate. Reality check: a 3060 12GB with 32 GB system RAM and a good NVMe SSD generated a 5-second (124 frames) 864×480 clip at 20 steps in just under 9 minutes end-to-end (community-reported, August 2026). Not “real-time-ish.” Coffee-break-ish. And that’s at 480p, not 2K.
Watch out: System RAM matters as much as VRAM on low-end cards. Because model files exceed what the GPU can hold, offloading spills into host memory – 32 GB has been demonstrated to work, but some users have reported host-memory failures at that same capacity. If you’re on 16 GB of system RAM, treat that as a blocker, not an optional upgrade.
Pitfalls you’ll hit in the first hour
These are the ones the launch-day tutorials don’t call out:
- Audio references can’t ride alone. Ref2VA accepts up to 9 reference images, 3 reference videos (2-15 s each, 15 s total max), and 3 reference audio clips – but those audio clips must always accompany an image or video reference. Drop in audio without any visual and the workflow won’t do what you expect.
- No local 2K, full stop. Nothing in the open release upscales beyond 768p-class output. Anyone selling you a “local 2K workflow” is either hitting the API for stage two or exaggerating.
- Your disk bill is bigger than the model size. Hugging Face cache, incomplete download retries, ComfyUI outputs, temp files – budget materially more than the 42.47 or 63.44 GB totals.
- Older ComfyUI breaks the template flow. Version 0.30.0 is the hard floor (as of August 2026). Pre-0.30.0 installs won’t surface the MiniMax H3 templates in the library at all.
How it stacks up (and when to skip local entirely)
The right comparison isn’t H3 vs. Sora or Kling in the abstract. It’s H3-Base-local vs. H3-API vs. running a different model. Here’s the honest table:
| Path | Resolution | Audio | Cost | Time to first clip |
|---|---|---|---|---|
| H3-Base local (3060 12GB) | up to ~768p | Native stereo, one pass | Electricity | ~9 min for 5s @ 480p |
| H3-Base local (4070 + 64GB) | up to ~768p | Native stereo, one pass | Electricity | ~167s for 608×352 @ 20 steps |
| H3 API (Regenerate-2K) | 2K | Native stereo, one pass | ~$0.13/s reported (~$1.95 for 15s, as of August 2026 – subject to change) | Seconds to submit |
As of August 2026, Artificial Analysis ranks H3 #1 in Video Editing, #2 in Text-to-Video, and #3 in Image-to-Video. Third-party numbers, not vendor claims – read them as “at or near the top on editing, competitive but not first on pure generation.”
Is any of this the death of paid closed-source video? Probably not this week. The gap between what you can run at home (768p, ~9 minutes per 5 seconds) and what the API produces (2K in seconds) is real. But it’s the smallest that gap has ever been for a model this capable – and that’s the actual story.
FAQ
Can I actually get 2K video out of my local ComfyUI install?
No. The open weights only include H3-Base, which caps at 768p-class output. The 2K Regenerate module is API-only.
My 12 GB card is technically supported – should I bother?
Depends on your patience and your other components. On a 3060 12GB with 32 GB RAM and an NVMe SSD, a 5-second 480p clip at 20 steps runs in about 9 minutes. Iterating on 30 prompt variations tonight? That’s five hours of render time alone. Fine for testing, rough for production. A 4070 with 64 GB RAM cuts that loop to noticeably faster – we’re talking 2-3 minutes vs. 9 for a comparable clip size.
How is the audio actually generated – is it worth using over a separate TTS or music model?
H3 predicts audio and video latents together in one pass, then decodes through separate VAEs before muxing to MP4. The real advantage isn’t audio quality – a dedicated TTS will still beat it on raw fidelity. It’s timing. Dialogue, sound effects, and ambience are locked to what’s on screen because they were generated simultaneously. If your workflow already involves post-hoc audio dubbing, H3 collapses that step. If you just want clean voiceover, stick with a dedicated TTS.
Next action: Update to ComfyUI 0.30.0, open the Template Library, and pick the T2V workflow. Run it once at the default preview size before touching any settings – that gives you a baseline for how long your specific machine takes, which is the only number that matters for planning real work.