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Comfy Router is live One API for frontier image, video, 3D, and audio models. Same model string. Same arguments. No new SDK, no new key, no redeploy. What Comfy Router gives you: → Explicit routing. You name the provider, we call that provider. It's down? The request fails there.... No silent fallback. → Every job returns the provider that ran it. Log it, bill it, debug it. → Async. submit() returns a request ID immediately. The queue retries 429s and transient errors until a slot opens. subscribe() submits and polls to completion. → Batch-friendly. Queue a few hundred jobs, hold the IDs, pull results as they land. Nothing blocking on a 5-min video render. → 24h retention on inputs and outputs, then deleted. → Comfy credits. No sub, no Router fee. Providers at launch: Comfy. Runware, Wavespeed, Fal, Higgsfield. Multi-provider where the model supports it. Get Your API Key with the link below. ⬇️show more

ComfyUI

59,709 subscribers

7,421,590 просмотров • 3 дней назад •via X (Twitter)

Образование Здоровье и велнес Наука и технологии

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Комментарии: 34

Фото профиля ComfyUI

ComfyUI3 дней назад

Get Your API Key today:

Фото профиля ComfyUI

ComfyUI3 дней назад

Learn more with the blog:

Фото профиля Robin Huang

Robin Huang3 дней назад

Great work team!!

Фото профиля Yoland Yan

Yoland Yan3 дней назад

LFG!

Фото профиля Maximus

Maximus3 дней назад

Finally

Фото профиля Tara Ding

Tara Ding3 дней назад

Congratulations!!!

Фото профиля Bohan

Bohan3 дней назад

Sick!

Фото профиля TongTong C

TongTong C3 дней назад

🔥🔥🔥

Фото профиля Atul Kumar

Atul Kumar3 дней назад

The biggest win here is consistency. One workflow across image, video, 3D, and audio means teams can focus on building products instead of maintaining integrations.

Фото профиля Ethan Kurzweil

Ethan Kurzweil3 дней назад

Sweet! 🎡

Фото профиля mathurah

mathurah3 дней назад

ahh this is going to be such a game changer! congrats to the team on the launch :)

Фото профиля Carl Wheatley

Carl Wheatley3 дней назад

Great launch!!!

Фото профиля Will Phillips

Will Phillips3 дней назад

Epic! Feel like Router is the word of the quarter 🚀

Фото профиля TongTong C

TongTong C3 дней назад

finally

Фото профиля Shun Ito

Shun Ito3 дней назад

congrats for the launch!!

Фото профиля Grace

Grace3 дней назад

This is a major upgrade LFG!

Фото профиля Sponko

Sponko3 дней назад

😮‍💨

Фото профиля Aaliya

Aaliya3 дней назад

The “finding out who did it” line fits nicely with the Beast Mode theme while keeping the CX message clear.

Фото профиля Olivia Li

Olivia Li3 дней назад

Let’s go!!

Фото профиля Orestis Lykos

Orestis Lykos3 дней назад

fal all the way down!

Фото профиля Rob Muresan

Rob Muresan3 дней назад

DAMN!

Фото профиля rob - comfyui

rob - comfyui3 дней назад

Very important things happening

Фото профиля Hasanuzzaman Khan

Hasanuzzaman Khan3 дней назад

Batch workflows are going to save teams a surprising amount of time.

Фото профиля Ian Lim

Ian Lim3 дней назад

Huge 🔥

Фото профиля Annette Sung

Annette Sung3 дней назад

lit

Фото профиля Ashley Nicole

Ashley Nicole3 дней назад

AI tooling is maturing—observability is finally becoming part of the conversation.

Фото профиля Arish Ai

Arish Ai3 дней назад

The multimodal ecosystem is getting crowded—having one workflow across providers makes a lot of sense.

Фото профиля David Kwon

David Kwon3 дней назад

Let's go! Great job @yoland_yan and team

Фото профиля David Marco💡

David Marco💡3 дней назад

Less glue code. More building. That's the kind of tradeoff every engineering team wants.

Фото профиля Tiger

Tiger3 дней назад

Hyped!

Фото профиля AlphaEcho

AlphaEcho3 дней назад

This is the kind of infrastructure launch developers actually appreciate less integration work, more shipping.

Фото профиля joao fig

joao fig3 дней назад

@yoland_yan killing it 🔥

Фото профиля Arnez Ai

Arnez Ai3 дней назад

Production-ready details like request IDs and retries are what make platforms stick.

Фото профиля Alishba

Alishba3 дней назад

This feels like infrastructure built for builders, not just demos.

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Atenov int.

12,200 просмотров • 1 месяц назад

NVIDIA is giving away free access to 140+ AI models for a full year > a lot of people building agents are paying $50-200/month just for API access NVIDIA just made that argument irrelevant models you get: GLM 5.2, MiniMax M3, Nemotron-3.5-lightning-30b-a3b, Muse-glimmer-30b from Meta and 130+ more setup: > step 1 - get your free key > go to > register -> bind phone -> copy API key > step 2 - add to Hermes agent > open Settings -> Model Provider -> Custom base_url = " api_key = "nvapi-xxxxxxxxxxxxxxxxxxxx" > step 3 - pick a model model = "z-ai/glm-5.2" model = "minimaxai/minimax-m3" model = "nvidia/nemotron-3-ultra-550b-a55b" model = "moonshot-ai/kimi-k2.7" > Hermes already has NVIDIA set as default base_url > paste the key and you're running instantly > works the same in Cursor and OpenCode > cost: $0 > limit: 40 req/min > expires: 1 year a free key changes what you can afford to run: > one prompt costs nothing either way > a loop firing 300 agents every week is where the bill shows up > for a year that bill is zero while everyone is paying for API access, this is sitting there for free with this many models in one place it is also the easiest way to test which one actually fits your agent before you commit to a paid provider

NVIDIA is giving away free access to 140+ AI models for a full year > a lot of people building agents are paying $50-200/month just for API access NVIDIA just made that argument irrelevant models you get: GLM 5.2, MiniMax M3, Nemotron-3.5-lightning-30b-a3b, Muse-glimmer-30b from Meta and 130+ more setup: > step 1 - get your free key > go to > register -> bind phone -> copy API key > step 2 - add to Hermes agent > open Settings -> Model Provider -> Custom base_url = " api_key = "nvapi-xxxxxxxxxxxxxxxxxxxx" > step 3 - pick a model model = "z-ai/glm-5.2" model = "minimaxai/minimax-m3" model = "nvidia/nemotron-3-ultra-550b-a55b" model = "moonshot-ai/kimi-k2.7" > Hermes already has NVIDIA set as default base_url > paste the key and you're running instantly > works the same in Cursor and OpenCode > cost: $0 > limit: 40 req/min > expires: 1 year a free key changes what you can afford to run: > one prompt costs nothing either way > a loop firing 300 agents every week is where the bill shows up > for a year that bill is zero while everyone is paying for API access, this is sitting there for free with this many models in one place it is also the easiest way to test which one actually fits your agent before you commit to a paid provider

Annatar.md

206,672 просмотров • 23 дней назад

Comfy Desktop is here - one app for every Comfy. We rebuilt the desktop experience from the ground up. Your existing workflows, custom nodes, models, and settings carry over untouched. Same name, completely new app. What's new: → Multiple ComfyUI instances — different custom nodes, different versions, all managed in one place → Automatic snapshots before every update and custom node change, with one-click rollback if something breaks → Day-0 ComfyUI releases — the moment a new version or nightly drops, you can update immediately If you're on our older desktop app, you'll see an update prompt automatically.

Comfy Desktop is here - one app for every Comfy. We rebuilt the desktop experience from the ground up. Your existing workflows, custom nodes, models, and settings carry over untouched. Same name, completely new app. What's new: → Multiple ComfyUI instances — different custom nodes, different versions, all managed in one place → Automatic snapshots before every update and custom node change, with one-click rollback if something breaks → Day-0 ComfyUI releases — the moment a new version or nightly drops, you can update immediately If you're on our older desktop app, you'll see an update prompt automatically.

ComfyUI

81,307 просмотров • 3 месяцев назад

NVIDIA IS HOSTING 100+ FRONTIER MODELS FOR FREE AND MOST PEOPLE STILL HAVEN'T NOTICED Everyone building agents is paying $50-200 a month for API access, and this key costs nothing and does not expire. I set it up and had GLM 5.2 answering in under five minutes. Getting the key: > Go to and register, phone verification and no card. > Copy the nvapi- key, you only see it once. Plugging it in anywhere that speaks OpenAI, including Cursor: > base_url = " > api_key = "nvapi-xxxxxxxxxxxx" What is sitting in the catalog: > GLM 5.2, landed two weeks after release. > Kimi K2.7, MiniMax M3, DeepSeek V4 Pro. > NVIDIA's own Nemotron line, and 100 more. The limit is around 40 requests a minute, which is plenty for one person and nothing for production -- that is the whole trade. It is also the fastest way to test which model actually fits your agent before you commit to a paid provider. Save & Try it ↓

NVIDIA IS HOSTING 100+ FRONTIER MODELS FOR FREE AND MOST PEOPLE STILL HAVEN'T NOTICED Everyone building agents is paying $50-200 a month for API access, and this key costs nothing and does not expire. I set it up and had GLM 5.2 answering in under five minutes. Getting the key: > Go to and register, phone verification and no card. > Copy the nvapi- key, you only see it once. Plugging it in anywhere that speaks OpenAI, including Cursor: > base_url = " > api_key = "nvapi-xxxxxxxxxxxx" What is sitting in the catalog: > GLM 5.2, landed two weeks after release. > Kimi K2.7, MiniMax M3, DeepSeek V4 Pro. > NVIDIA's own Nemotron line, and 100 more. The limit is around 40 requests a minute, which is plenty for one person and nothing for production -- that is the whole trade. It is also the fastest way to test which model actually fits your agent before you commit to a paid provider. Save & Try it ↓

slash1s

31,426 просмотров • 1 месяц назад

NVIDIA is giving away free access to 140+ AI models for a full year > most people building AI agents are paying $50-200/month for API access NVIDIA just made that argument irrelevant models you get: GLM 5.2, MiniMax M3, Nemotron-3-Ultra-550B-A55B, Kimi K2.7, and 130+ more setup: > step 1 - get your free key > go to > register -> bind phone -> copy API key > step 2 - add to Hermes agent > open Settings -> Model Provider -> Custom base_url = " api_key = "nvapi-xxxxxxxxxxxxxxxxxxxx" > step 3 - pick a model model = "z-ai/glm-5.2" model = "minimaxai/minimax-m3" model = "nvidia/nemotron-3-ultra-550b-a55b" model = "moonshot-ai/kimi-k2.7" > Hermes already has NVIDIA set as default base_url > paste the key and you're running instantly > works the same in Cursor and OpenCode > cost: $0 > limit: 40 req/min > expires: 1 year while everyone is paying for API access, this is sitting there for free with this many models in one place, it is also the easiest way to test which one actually fits your agent before you commit to a paid provider

NVIDIA is giving away free access to 140+ AI models for a full year > most people building AI agents are paying $50-200/month for API access NVIDIA just made that argument irrelevant models you get: GLM 5.2, MiniMax M3, Nemotron-3-Ultra-550B-A55B, Kimi K2.7, and 130+ more setup: > step 1 - get your free key > go to > register -> bind phone -> copy API key > step 2 - add to Hermes agent > open Settings -> Model Provider -> Custom base_url = " api_key = "nvapi-xxxxxxxxxxxxxxxxxxxx" > step 3 - pick a model model = "z-ai/glm-5.2" model = "minimaxai/minimax-m3" model = "nvidia/nemotron-3-ultra-550b-a55b" model = "moonshot-ai/kimi-k2.7" > Hermes already has NVIDIA set as default base_url > paste the key and you're running instantly > works the same in Cursor and OpenCode > cost: $0 > limit: 40 req/min > expires: 1 year while everyone is paying for API access, this is sitting there for free with this many models in one place, it is also the easiest way to test which one actually fits your agent before you commit to a paid provider

Mr. Buzzoni

121,850 просмотров • 2 месяцев назад

Production traffic is not uniform. You get a few requests that need your best model, but most are simple questions and lookups you can solve with cheaper, faster models. The most expensive mistake you can make today is sending every request to your strongest model. You need routing. Period. This is the simplest trick to improve the architecture of whatever you are building. Please, don't implement routing yourself. You don't have to. I'm currently working with TrueFoundry's Auto Routing. It reads each request, classifies it as simple, medium, or complex, and sends it to the model assigned to that tier. You have two choices: 1. Send every request to the free heuristic classifier to score signals such as technical vocabulary, code, prompt length, and multi-step reasoning. 2. Send the request to an LLM classifier when its difficulty requires a more nuanced judgment. The beauty of using routing is that nothing changes in your code. You still call a single endpoint model, but routing works behind the scenes to pair every request with the best possible model. TrueFoundry ran several experiments with two different setups: 1. Send every request to Claude Opus 2. Send every request to a router with Haiku, Sonnet, and Opus The first experiment ran 550 deterministically graded academic prompts through every setup. Auto Routing was 69% cheaper while retaining 98% of the baseline quality. The second experiment ran three production-shaped workloads through every setup, using user chats, developer chats, and long agent tasks. Auto Routing was 80% cheaper. Thanks to the TrueFoundry team for partnering with me on this post.

Production traffic is not uniform. You get a few requests that need your best model, but most are simple questions and lookups you can solve with cheaper, faster models. The most expensive mistake you can make today is sending every request to your strongest model. You need routing. Period. This is the simplest trick to improve the architecture of whatever you are building. Please, don't implement routing yourself. You don't have to. I'm currently working with TrueFoundry's Auto Routing. It reads each request, classifies it as simple, medium, or complex, and sends it to the model assigned to that tier. You have two choices: 1. Send every request to the free heuristic classifier to score signals such as technical vocabulary, code, prompt length, and multi-step reasoning. 2. Send the request to an LLM classifier when its difficulty requires a more nuanced judgment. The beauty of using routing is that nothing changes in your code. You still call a single endpoint model, but routing works behind the scenes to pair every request with the best possible model. TrueFoundry ran several experiments with two different setups: 1. Send every request to Claude Opus 2. Send every request to a router with Haiku, Sonnet, and Opus The first experiment ran 550 deterministically graded academic prompts through every setup. Auto Routing was 69% cheaper while retaining 98% of the baseline quality. The second experiment ran three production-shaped workloads through every setup, using user chats, developer chats, and long agent tasks. Auto Routing was 80% cheaper. Thanks to the TrueFoundry team for partnering with me on this post.

Santiago

15,543 просмотров • 15 дней назад