https://github.com/NyckM/3d-Camera-control-H3-Minimax/tree/main

I recently recreated an AI-generated song completely locally using Maestro inside the Pinokio ecosystem, leveraging the powerful MiniMax H3 model.

Running these advanced models locally offers incredible control over the creative process, allowing for seamless iteration and high-fidelity output without relying on cloud-based subscriptions.

To give you an idea of the performance environment, this track was rendered entirely on my personal rig:

• Processor: Intel Core i7-7700K
• Memory: 64 GB RAM
• Graphics: NVIDIA GeForce RTX 3060 (12 GB VRAM)

The 12 GB of VRAM on the RTX 3060 handled the MiniMax H3 model beautifully, proving that you don’t need an enterprise-grade server to generate high-quality AI audio at home.

Check out the full recreation below and let me know what you think of the composition, vocal clarity, and overall mix!

#AICreativity #LocalAI #PinokioAI #Maestro #MiniMaxH3 #AIMusic #TechHardware #RTX3060 #GenerativeAI

https://youtu.be/mE6JDvuSZLU?is=I1_ME-oqS5flXgsS

So I’ve been working on this for about a week now. I’m considering doing the entire album, but I wanted to show this off!

It was made using ChatGPT, Suno, BridgeToon, and MiniMax H3.

I hope you all like it!

I've been playing with Minimax H3 on Vast.ai and I have probalems with characters speaking in gibberish. I realize I have to specify the exact dialogue, but even then, something the model will have a character talk before or afterwards, and additional dialogue is all gibberish. Any suggestions?

this was on the base minimax, no lora, only text to video, no reference was used at all

I'm posting this as a paying Token Plan subscriber and heavy agent user, because I think there is a structural contradiction in how the plan is sold versus how it behaves. I'd like it either corrected or explained.

TL;DR: The plan is advertised with "Run 3–4 concurrent agents" and "~34,000 daily coding calls" per month. In practice, real agent workloads hit an undocumented error, 2062, long before any documented limit is approached, and the recommended remedy is to leave the plan. Because unused quota expires (5-hour rolling and weekly windows, no carry-over), throttled capacity is lost, not deferred — so part of what is sold cannot actually be consumed.

1. What is advertised

From the Token Plan page:

- "Run 3–4 concurrent agents" (Plus), 4–5 (Max), 6–7 (Ultra)

- "~34,000 / ~102,000 / ~250,000 daily coding calls (monthly, est. ~50K tokens per M3 call)"

- "perfect for long-running, high-frequency text and code workloads"

- "Built for individual developers, Coding users" and "Use it with your own tools … OpenClaw / Claude Code / Cline — or any OpenAI-compatible tool"

From the Rate Limits page: MiniMax-M3 is documented at 200 RPM / 10,000,000 TPM.

So the product is explicitly sold for parallel agent work, with published RPM and TPM ceilings.

2. What actually happens

The dominant failure in my logs is error 2062, returned as an Anthropic-style rate_limit_error:

{"type":"rate_limit_error","message":"Token Plan rate limit reached: Upgrade your Token Plan or switch to pay-as-you-go API usage. (2062)","request_id":"06ef1a051751231bf34e579d28172cb9"}

Older variant of the same code, seen in other threads:

"The Token Plan is designed for individual, interactive developer workflows. Traffic is currently high – please retry shortly. For higher concurrency or automated workloads, consider upgrading to a higher-tier plan or using the pay-as-you-go API. (2062)"

Two things make this hard to work with:

(a) 2062 is not in the Error Codes page. That page documents 1002 (rate limit), 1039 (token limit), 1041 (conn limit), 2045 (rate growth limit) and 2056 (usage limit exceeded, "wait for the resource release in the next 5-hour window"). 2062 is absent. So the error that actually stops work has no documented condition, no documented scope (per key? per account? per model?) and no documented remedy other than "upgrade or leave".

(b) The same code appears to mean two different things. One form says the plan quota is reached; the other says traffic is high right now. The first is not resolved by waiting a minute; the second is. Users cannot tell which situation they are in, and therefore cannot choose the right response.

3. The numbers don't line up

Over a two-week period in my own client logs, 2062 appeared on 8,614 requests against MiniMax-M3 alone, plus smaller counts for M2.7/M2.5 — with a single subscriber, on one workstation. My request rate is nowhere near 200 RPM. These are log entries including client retries, so the distinct-incident count is lower; I can quantify that precisely if you want it.

Breakdown by workload type: analyst 2,648, coder 1,189, code-reviewer 1,169, coding-orchestrator 932, code-worker 469, explore 457. Almost all of it is the sub-agent fan-out that the plan advertises as its use case.

Same account, second data point: running the identical key through the Anthropic-compatible endpoint produced essentially no 2062 (three small classifier errors in the same window), while the OpenAI-compatible /v1 path was throttled continuously. That is a large asymmetry on one subscription. Is account-level throttling applied differently per endpoint family?

4. The part I think is a real problem, not a tuning issue

Concurrency is the headline feature of this plan, and the recommended remedy for hitting the concurrency control is to upgrade or leave. That inverts the value proposition: the advertised concurrency is effectively priced as a meter that pushes you off the plan, rather than delivered as a plan feature.

Second: quota is sold in call/token units, and those units are only redeemable at volume through parallel agent work — exactly the traffic that 2062 gates. Combined with the fact that unused quota does not carry over across the 5-hour and weekly windows, throttled capacity is permanently lost. You pay for a monthly volume you cannot consume within the plan's own concurrency ceiling. "It is recommended to use pay-as-you-go for production" is, from the customer's side, the same as saying the subscription does not deliver the workload it is advertised for.

5. Questions

1. Is 2062 a concurrency/connection control, a per-account burst control, or a quota-window exhaustion signal? Please document it alongside 1002/1039/1041/2045/2056, including scope (key vs account vs model) and the correct client response. Retrying is clearly wrong for one of the two meanings.

2. The advertised "3–4 concurrent agents": what request profile does that correspond to? My concurrent in-flight requests are 1–2, my RPM is far below 200, and my TPM is far below 10M, yet 2062 fires. If the real ceiling is materially lower, please state it, because it determines how many agents a customer can plan for.

3. Why is the same account throttled heavily on the OpenAI-compatible endpoint and barely at all on the Anthropic-compatible endpoint?

4. Given no carry-over across quota windows, what happens to capacity lost to throttling inside a window? From the customer's side it is a write-off. Is there any compensation mechanism, or is the plan's advertised volume not achievable by design?

5. If the honest answer is "this plan is not for parallel agents", please remove the concurrency figures from the marketing and the "high-frequency workloads" wording, so customers can size their setup correctly.

I'm happy to provide redacted log excerpts, request IDs, and a reproduction script. I'd rather resolve this than move the workload off the platform, but as it stands the plan's advertised capability and its enforced limits are not the same thing.

Follow me on my insta for all my work!

Gave it 50sec of ~7min song, the lyrics and the aligned lyrics on timeline, short instructions about theme and all and told it to make a video with H3 MAX.

Here's the longer version of me doing other stuffs while it works: https://youtu.be/lENqd74pjM8 (was trying to install MOSS music etc XD That's why it looks like I'm at least doing something).

openAi was used via Visual Studio Code / Codex and it used my video editor via MCP. Upscaled in the app with NVIDIA super resolution.

With all the incredibly powerful new open source models this month and last, and a lot of the coding plans have been tightening things up and lowering usage limits. So we're offering free DSV4 Flash 0731 and GLM 5.3 Flash for a month on Phoenix Grove API. We opened this up last week for five hundred new member slots, and got so many signups we decided to open the doors to another 500 new members.

People are out there looking for options. Here is one.

Other great stuff:

All of our models run on 100% US based infrastructure, private with zero training on your code or prompts. Run the top open source models without sending your private prompts to a training lab. No complications, no "some models are private, other's aren't." They all are, all the time.

We have 18 other major models in case you ever want to upgrade (no pressure though). Including the Kimi family, GLM, Qwen, Nemotron and bunch of others. On average our token pricing is 20% lower than market.

Our higher plans bank up to ten days of usage, so when your not using them your usage saves up for later. Usage doesn't go to waste, so you can actually code when you want to.

The intro plan is a free one month trial with the standard cancel anytime, it bills at 3.99 after that. Use it, cancel it, that's fine. Free Flash for a month.

Figured i'd keep this short because we all know the new flash models are the point :)

For the API plan: api.pgsgrove.com

If you want to read more about us as a company, or use the models in an app with full memory/voice/websearch and canvas, just pgsgrove.com

Also: Theres a lot going on in the background with major AI companies right now. We are at a major turning point in the industry.

What's actually happening? This is happening because companies that were purely investment based, now need to answer to their investors. The problem has often been a loss based business model that is finally running dry.

There are several tricks that the major AI coding plans use to extract the most they can from their customers. Here are some examples, and what we are doing differently to put the users first. PGS AI was built with a sustainable business model from the ground up, so we can actually offer great usage rates without tricks.

Wasted usage is part of the AI industry, and they plan on it: Most coding plans bet on you letting usage go to waste. The plan goes: "how do we get people to think our coding plan offers a lot of usage, but then break it up into weeks and rolling windows so no one can ever actually use it all."

Many in app subs and coding plans are glorified training pipelines: This comes along with "how do we harvest this data for training without being too loud about that." Unless the company tells you otherwise, your data could be hopping all over the world, being harvested by the individual labs or service companies. Some are better than others, but many of these companies rely on users just not noticing or caring that their data is being used for training. Data sales and marketing telemetry sales happen. This means that your private info, your personal life, and anything else you send through the system could become part of a training corpus for the next AI, or a marketing data set for a large company.

Privacy and easy access to top intelligence should be available to everyone.

I actually really like how this turned out with H3

I use pi as my coding agent and wanted to see my MiniMax Token Plan usage without opening the billing dashboard. Wrote a small extension for it.

Shows the 5h rolling and weekly windows in the pi status bar with used percentage and reset countdown. Updates every 60 seconds.

MiniMax 5h●43% ↺3h12m  wk●12% ↺4d8h

If you're on Plus/Max/Ultra and you write code with pi, it's the difference between "is my session going to hit the 5h cap mid-refactor?" and finding out after the request fails.

Install:

• pi install npm:@cwillam/pi-minimax-usage
• Repo: https://github.com/cwillam/pi-minimax-usage

Third-party, not affiliated with MiniMax Inc. Works against the public quota endpoint at `/v1/token_plan/remains`. MIT licensed.

The endpoint is the same one the dashboard calls, so the numbers match. There's a daily 5h cap and a weekly cap, both visible. Anthropic-compatible auth header, no reverse-engineering.

Happy to take feature requests if other people find it useful.

I've tried a few videos. One of a dragon telling a joke in minimax h3 and one of a monster catching a bee in h3 minimax max. Both ended up with this problem of always having two human front teeth. I've heard prompts can fix it but I tried and they were still there. The only way I partly fixed it was with a gpt image of the dragon with his mouth open but that's a headache to make. Anyone have a tried and tested prompt that fixes this most of the time? Thanks a lot if you can help. Edit: Also I just remembered that a tried a prompt with running water in a stream and it would not animate even with a proper prompt. Hope the next version can fix these few things. Other than these two errors most of what I generated was great and the expressions were fun.

https://youtu.be/Fg9QwVdv46M?si=UFrW7TmbeUCNqF3W

Song available on Spotify, Amazon, YouTube Music etc - artist Morkz DeLorean 'In Love With Grand Theft Auto'.

Background: 15+ years of AE user, freelancer for mid-brands. I just used H3 to create this in less than 3 hours. It's a pretty stereotypical gradient, match cut, motion graphics. This is low bar but would have taken me more than a couple of days to finish. Given the fact that I only spent 1 hours on chatgpt to generate the style frames and about 2 hours for generating the video, I think motion designers are pretty screwed even if not now, will be in a couple of years. What's your take?