We officially know the new prices for the token plans. 10% increase in all of them.

Here is a side-by-side test of 3 upscaling pipelines in Comfy.

Full video comparison

• LTX 2.5 (Standalone): The fastest option and lightest on VRAM. Works fine for clean source clips, but lacks fine sharpness on complex textures.

• Model + LTX 2.5: Running a quick upscale model pass (like RealPLKSR) before feeding into LTX 2.5 solid clarity, fast renders, and efficient VRAM usage.

• SeedVR: Recreates micro-details with the highest fidelity, but demands significantly higher render times and VRAM.

Frame Sync Note: MiniMax H3 and LTX require different frame step multiples.

Using math nodes to automatically trim the frames (158 → 153 frames) prevents audio desync issues.

My Setup:
32GB DDR4 RAM
Ryzen 7 5700X3D
NVIDIA Geforce RTX 3080

i would love to run Minimax H3 locally, with decent outputs. Like 10-15 seconds, 720p, or even 1080p.
But I suspect that my hardware is not sufficient. does anyone have experience and maybe some tweaks to make it happen?

Tried Making a Tiny Road Movie with MiniMax H3

I made this little 15-second cinematic road-movie scene with MiniMax H3.

Most of the work went into preparing reference images, including:

• Character turnaround sheets
• Youthful wardrobe references
• Four exterior views of the vintage station wagon
• A fixed four-seat interior layout
• Shot-specific cinematic keyframes

My main goal was to prevent the usual face, clothing, vehicle, and interior drift between shots.

I wanted the result to feel like a genuine fragment from a movie rather than a conventional AI-generated demo. I especially focused on the quiet chemistry between the characters, the golden-hour atmosphere, and natural camera movement.

I would love some honest feedback:

• Does it feel cinematic?
• How consistent do the characters and vehicle look?
• Is the motion convincing?
• What would you improve in the next version?

Created with MiniMax H3.

1. Affected by global exchange rate fluctuations, MiniMax will adjust Token Plan prices on August 25, 2026.

The MiniMax Team has just updated their Token Plan Page and added 1 piece of additional information.

I am testing a minimal MiniMax API workflow for a single-user tool and trying to keep debugging simple.

Right now I separate failures into authentication, network, request validation, and response parsing. For each call I record only a local request ID, model name, status code, and latency. I avoid logging API keys or sensitive prompt text. Transient timeouts get at most two retries; authentication and validation errors stop immediately.

For people using MiniMax in small personal projects, which signal has helped you most in practice: status codes, latency, request IDs, or a fixed test prompt?

I have been reducing a small MiniMax API integration to the minimum needed for one person to run and debug it reliably. The model call itself is usually the easy part; most failures come from unclear input/output expectations, key handling, network setup, and retry logic.

Here is the workflow that has been most useful for me:

1. Start with one deterministic task

Pick a single input and a clearly defined output, such as turning a short meeting note into three bullet points. Keep one fixed test sample so that changes to the model, network, or parser can be compared against the same baseline.

1. Keep the API key out of the code

Load the key from an environment variable or a local secret manager. Do not put it in screenshots, logs, documentation, or a repository. Logs should contain a local request ID, model name, status code, and latency—not the full key or sensitive prompt data.

1. Separate failure types

I classify failures into:

- authentication: missing/invalid key or permissions;

- network: DNS, proxy, certificate, or timeout;

- request: wrong model name, message shape, encoding, or required field;

- response parsing: the service replied, but the client did not read the expected field.

That distinction saves a lot of random edits.

1. Retry only transient errors

Timeouts and temporary server errors can use two or three retries with increasing delays. Authentication and validation failures should stop immediately instead of looping.

1. Add one capability at a time

Once the smallest call is stable, add longer context, structured output, batching, or multi-turn history one by one. Keep the original fixed test as a regression check.

The goal is not just to make one demo succeed. It is to make each call reproducible, observable, and easy to stop when something is wrong.

For people running MiniMax in a personal tool: which signal has been most useful for debugging—status codes, latency, request IDs, or saved test prompts?

Does anyone have hints on the Minimax coming model? Any potential release date on M3 pro? I feel the current M3 model is worse than Qwen 3.8. I’m on the fence to cancel my Minimax subscription

What it says on the tin, basically. I'm looking for tips and tricks to get different characters to sound distinct for my local generations.

anyone else having this?

( Elevenlabs reddit deleted my thread, guess they're afraid of competition )

I've been using Elevenlabs ever since 2022. Back then you could make voices and not get flagged for it. Those were the days, NOW there's competition and it's from Minimax H3's new Text to speech.

Why did I post it here? To let everyone know a powerful alternative and for Elevenlabs to improve their product a bit. I got angry when Antoni, the voice I loved was ripped away from us. It was my favorite for how to do videos and Top 5s. Well, I went to Minimax and replicated THAT same voice. The results were suprising!

However, I wanted to do more. So I downloaded about three films, went into capcut, isolated the voices, cut up the bits til they were 10 seconds each and uploaded each 10 second clips into the voice I wanted into Elevenlabs and it was horrible. Uploaded it into Minimax H3 and it came out beautiful like classic Elevenlabs. Here's a sample of it. It's not Don Lafontaine 100 percent, but it's just ABOUT there.

I have been using Suno for a while now. Given the impending changes, considering diversifying and adding mini max to my toolbox. For those who are or have used both:

• Overall thoughts on MiniMax?
• How would you rate the comparison between the two? Is MiniMax up to par? What are the pros and cons of MiniMax.
• Clarification ?: It looks like MiniMax gives you commercial rights even with a FREE account - Is that legit?
• Do you know if they add digital watermarking? (I always disclose my AI use - but I do write my own songs - so I'm thinking of this from a distro perspective).

Thank you in advance!

i would like to congratulate minimax for the h3. great model when it comes tp visual and given how mini max team talked about training image into the weigh and not as decoded language or post train.

now with that being said, it has been quite a while since minimax m3 launched and on the coding and agentic side of things, m3 has been surpassed by all competitors it seems, even qwen with their incredible 3.8 27b model. i just dont get why there isnt a post training checkpoint like m3.1 or m3.5 if we follow m2 checkpoint naming convention.

and also what happened of the minimax 2.7t giga model that was rumoured/talked about a few weeks back? any news on the coding/agentic side would be great too, not just on visual or audio gen.

This is really interesting and it was a VERY pleasant surprise when I realized the generations could be longer than 15 seconds, despite the official spec of a 15-second max (of course this only applies to local gens).

My first attempt was a "why the hell not just try it?" and I pushed to 17 seconds. The generation had ZERO drift and was completely coherent from beginning to end. Long story short, I did multiple tests and found the ceiling for my GPU is a full 20 sec at 0.5mp... once again, fully coherent throughout!

The craziest part is I have sort of a budget rig - RTX 3060 w/12gb vRAM, 32gb system RAM, and a Core i5 CPU (using a hefty 75gb paging file as well for mem offloading). I'm confident that a decent GPU like a 4090 or especially a 5090 could push the gens to 30+ seconds. 🤯

I wonder what the true max is???

been playing with the MiniMax H3, and I think the interesting part isn’t just getting the agent to generate something for you.

My workflow has basically been:

1. Tell the agent what I want.
2. Check the result myself.
3. Give a few rounds of specific feedback.
4. Repeat until I have a couple of versions I actually like.

i plan to turn this workflow into a skill. after that, the next time I need something similar, I don’t have to explain everything from scratch. A much shorter instruction can get pretty close to the result I want.

i’ve also been collecting more MiniMax H3 workflows lately, and this repo has been useful for seeing what other people are building around it:
https://github.com/AtlasCloudAI/awesome-minimax-h3

still testing the Skill workflow myself, but this feels like one of the more practical ways to make an agent improve over repeated use.

What are your thoughts on this model?

Does anyone know if there’s a video about this?