Hi r/comfyui, Comfy MCP is now local and open-source!

When we shipped Cloud MCP in June, the response was immediate and consistent: make it work locally. So we did and it's fully open source.

Connect Claude, Codex, Cursor, or any MCP client to your local ComfyUI.

Your agent reads the GPU you actually have and gives you a straight answer on whether a model is worth running before you commit to the download. It reads every node and model you've installed. It handles the setup that usually stops people at step one.

It is now the easiest way to help with your local Minimax H3 workflows!

Cloud MCP still does everything it did. Tell your agent where a job goes, or let it decide.

Hi r/StableDiffusion, I know it's been a long wait for everyone but MiniMax H3 open weight model just dropped and we have day 0 support in ComfyUI.

Here are some details:

• text-to-video, image-to-video, first-and-last-frame, reference-to-video, and editing a shot in place
• up to 2K, up to 15 seconds a clip
• real stereo audio generated with the video, not bolted on afterward
• Blog link: https://blog.comfy.org/p/minimax-h3-day-0-support-in-comfyui
• Workflow templates:
  • I2V: https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_i2v.json
  • R2V: https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_r2v.json
  • T2V: https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_minimax_h3_t2v.json
• Model Links:
  • https://huggingface.co/MiniMaxAI/MiniMax-H3 (please support them there)
  • Comfy repackage for smaller size: https://huggingface.co/Comfy-Org/MiniMax-H3

Getting H3 to run well on consumer hardware took significant machine learning engineering. We found that the model's modulation weights (~40% of the total parameters) could be pruned and replaced with a functionally equivalent lookup table, dramatically shrinking the memory footprint with no loss in output quality.

On top of that, the weights ship with an accurate and efficient int8 convrot quantization, and custom kernels reduce the peak VRAM use during inference.

The result gives a total memory footprint reduced by 66%, from 123.6 GB in full precision to 42.5 GB with the smallest models variants. Combining this with our dynamic VRAM offloading enables a next-generation 2K video model to run locally on a GPU like the RTX 3060.

EDIT:

08-02-26 20:02 PST - Added blog link

Join us tomorrow for a special live conversation with Mohammad Norouzi (CEO, Ideogram) and Yoland Yan (CEO, Comfy.org), hosted by Purz & Rob.

We sit down with the founders behind Ideogram 4.0 and ComfyUI to talk about building an open-weight text-to-image model from scratch, where open weights stand against closed APIs, and what's next for both teams. Then we open it up to the community for a live Q&A.

What we will cover:

• Founders interview with Mohammad Norouzi & Yoland Yan
• The story behind Ideogram 4.0 and its open-weight release
• Structured JSON prompting & bounding box layout control
• Community Q&A — bring your questions

📅 June 18th - 2:30pm PST
📢 Live on Youtube, X, and Twitch
🔗 https://www.youtube.com/watch?v=gO-D5eO8VlA

Hi r/comfyui bet yall didn't see this one coming, it's a big day for the open-source community! Ideogram 4.0 is a 9.3B parameter open-weight text-to-image model. It is now natively supported in ComfyUI (latest update)
Weights, inference code, full prompting guide, and sampler presets are public. The repository ships both fp8 and nf4 checkpoints; the nf4 variant fits on a single 24 GB GPU.

Why this is a massive deal for local generation:

• Unmatched Text & Layout Control: It scores 0.97 on X-Omni English OCR accuracy and sits at #2 overall (and #1 for open-weights) on designer preference ELO, beating out models like FLUX 2 [dev] and Nano Banana 2.
• Structured JSON Prompting: The model was trained exclusively on structured JSON captions. This means you can condition generations directly with exact color palette hex codes, precise bounding-box layouts [y_min, x_min, y_max, x_max], and typed text elements for multi-line, multi-font in-image text.
• Unique Architecture: It's a 34-layer single-stream DiT that uses Qwen3-VL-8B-Instruct as its text encoder, consuming hidden states from 13 intermediate layers rather than a single slice.
• Asymmetric CFG & Resolution Flexibility: The unconditional pass drops text tokens entirely to speed up sampling, and a single set of weights handles everything from ultra-wide banners to phone wallpapers without needing a dedicated LoRA or model.

If you have been waiting for a powerful open model that can handle complex posters, precise graphic design layouts, and readable copy without sending your prompts to a closed API, this is the one to try.

Links: Hugging Face weights, tweet, and full technical blog.

I will post some images and prompts in the comments

Hi r/comfyui, Nodes 2.0 has been in beta since last July, and we want to be transparent with the community about where we’re headed.

Over time, we plan to gradually make the new interface the default experience in ComfyUI.

We know the reception has been mixed. There are many things we handled ineffectively early on, and the team has been working hard over the past months to address them. We appreciate everyone who has continued testing, giving feedback, and pushing us on where the experience falls short.

The Problem With Canvas

Canvas rendering worked, but it cut us off from everything the modern web has built over the last two decades: component libraries, design systems, accessibility tooling, the entire ecosystem developers rely on to ship fast. Every widget had to be drawn pixel by pixel.

Generative AI doesn't sit still. New models, new modalities, new techniques, new ways of combining them. The workflows that made sense six months ago get rethought constantly. Our users are doing professional creative work, and they expect the controls that professional tools have had for years: curve editors, color grading, histograms, timeline scrubbing. We can't keep rebuilding those from scratch.

What a Modern Frontend Unlocks

With a modern frontend framework, a curve editor that would have taken weeks now takes days. A gradient slider with live preview, hours.

Since the Nodes 2.0 beta launched, we’ve already shipped:

• Curve editors
• Histogram displays
• Live cropping UI
• Before/after comparison sliders
• Image processing nodes for color correction, film grain, chromatic aberration, sharpening, and levels
• Realtime shader nodes with subgraph blueprints
• Inline error displays and status badges directly on nodes

This foundation also unlocks things that were previously impractical or impossible:

• Live execution previews on subgraphs
• Parallel node execution with realtime feedback
• Richer interfaces for future modalities and workflows

Custom Nodes

Most custom nodes work unchanged. For nodes that require updates, we’re investing heavily in migration support:

• A new public frontend API
• Documentation and migration guides
• Reference implementations
• Direct collaboration with node authors to identify gaps

We understand this creates additional work for maintainers. For many popular custom nodes, we’re happy to directly help submit PRs and assist with migration work ourselves.

Recent advances in coding agents have also made these frontend migrations significantly easier than they would have been even a year ago.

Thank you for your patience as we work through this transition together.

Timeline

There is no fixed cutoff timeline yet. Right now, the priority is being transparent early and giving the ecosystem time to adapt.

Current plan:

• Nodes 2.0 remains opt-in for now (Settings > Rendering > Nodes 2.0)
• It later becomes the default while legacy mode remains available
• Eventually, legacy mode will become unmaintained and will likely break over time

Going forward, new frontend-focused ComfyUI features will ship exclusively on Nodes 2.0.

Feedback

Please let us know what you think and the problems you run into. We need testing on complex workflows, large graphs, and custom nodes with unusual rendering. Report issues on GitHub or #bug-reports on Discord 🙏

Once again, thank you all for supporting Comfy.

And most importantly, thank you to all the custom node authors who continue making this ecosystem incredibly vibrant, creative, and powerful.

Hi r/comfyui! Today we’re excited to share that Comfy has raised $30M at a $500M valuation! Comfy has grown a lot over the past year, and especially over the past six months: more than 50% of our users joined the Comfy ecosystem during that period. Comfy Cloud/Partner Nodes has also grown quickly, with annualized bookings crossing $10M in 8 months.

This funding gives us more room to invest in the things this community cares about most: making Comfy more stable, improving the product experience, fixing bugs faster (sorry again for the bugs!) and continuing to launch powerful new features in the open!

The main goal of this announcement is to also attract top talent to build what we believe to be a generational mission of making sure open source creative tools win. If you are passionate about Comfy and OSS creative AI, join us at comfy.org/careers.

Please help us spread the news by spending 90s on comfy.org/share-the-news where you can help us to amplify our announcement and enter to win an exclusive ComfyUI Swag

We are an open source team, being in the open is part of our culture (although we have not been doing a great job at communicating at times). As part of the announcement, we would love to do a live AMA on Discord. Please upvote this post and add your questions there, we will go through them live at 3PM PST.

Tune in to the AMA here: https://www.reddit.com/r/comfyui/comments/1sumsoh/comfy_org_funding_announcement_ama_live_at_3pm_pst/