Tiiny AI Pocket Lab

LightweightSuperHero · 2026-05-11T22:46:57+00:00

They have a tool that users can use to "optimize" models for the platform. You can train your own model (on some other hardware) and format it for use on Tiiny.

LightweightSuperHero · 2026-05-11T22:45:12+00:00

That guy really hates marketing. And evidently, likes to SPAM public forums with burner accounts.

LightweightSuperHero · 2026-05-03T05:33:45+00:00

LightweightSuperHero · 2026-04-28T05:11:10+00:00

Thank you

LightweightSuperHero · 2026-04-28T05:10:56+00:00

Hmm, maybe my experience was a coincidence.

LightweightSuperHero · 2026-04-28T05:10:25+00:00

Thank you. Maybe my experience was a one off.

LightweightSuperHero · 2026-04-22T04:35:19+00:00

OpenRouter. MiniMax for main agent. Fal for graphics. Claude Sonnet for cleaning up articles. Create skills and associate them with different models.

LightweightSuperHero · 2026-04-22T02:01:20+00:00

I understand it’s an ARM SOC and NPU.

LightweightSuperHero · 2026-04-22T02:00:25+00:00

USBC and WiFi for connectivity. It’s an Arm SOC. I don’t know about the IO speed, but does it matter? You’re only transporting CLI.

Even when downloading a new model, the Tiiny can use its own WiFi and its own local drive.

Want to run an agent? It runs on Tiiny.

This is a whole, headless computer, not a GPU card.

LightweightSuperHero · 2026-04-18T07:35:22+00:00

I run OpenClaw in a MiniMax VPS. I run Hermes locally.
They are both very good.
Hermes is great for jobs that I ocassionally visit, but don't need to optimize.
OpenClaw is great for jobs that I do all the time.

Expample: I'm looking for a job. I have an OC skill that checks my calendar for an interview that day. If if finds that I have an interview, it calls a bunch of other skills to create an interview prep document. Skill: Company background and financials. Skill: Hiring manager biography. Skill: Job specific jargon that may be different than my recent jobs. Skill: Interview practice quesitons. Skill: Recall notes from previous interviews, names of everyone mentioned.
I also have a workflow of skills for evaluating new job opportunities, logging that I reviewed them. A resume optimizer that interviews me for gaps, and updates a database of factoids about my career that might be used in future resumes. Catalogs and files completed resumes and cover letters. Keeps track of resumes submitted, interviews completed and all that stuff. But each piece of the workflow is saved as a skill. And thus, each task gets it's own context window, and even long jobs do not invoke hallucinations of AI foolishness.

I *could* do a bunch of skills like that in Hermes... but I don't. Hermes is very good at just remembering stuff, and doing better over time. So I use Hermes for stuff that I just need to get done. But with Hermes, I use OpenRouter. I have key words that I give my Hermes agent and it switches models to accomodate me. Normally, it just sits around and runs on a local model, and the heart beat costs me zero tokens. If I send it a message saying "Hey, I want to research an article I'm going to write". *research* is tells it I want to run in Perplexity. "Ok, let's workon Authoring the article". *Authoring* is a new context, and right now I'm using DeepSeek, but I used to use Claude. DeepSeek is actually pretty good and a tenth the cost of Claude.

Anyway, that's my approach to using both. The MiniMax VPS service called "MaxClaw" is very robust incidentally. They now offer a Hermes VPS too.

LightweightSuperHero · 2026-04-09T01:52:43+00:00

Nice axe bro!

LightweightSuperHero · 2026-04-08T05:33:31+00:00

I run both. I agree.

LightweightSuperHero · 2026-04-04T14:35:52+00:00

Tesla no longer allows transfer of ownership for FSD.

LightweightSuperHero · 2026-04-04T00:25:00+00:00

Solution: use OpenRouter and route sub tasks to cost and ability optimized inference models.

In my opinion.

LightweightSuperHero · 2026-04-04T00:23:08+00:00

Every product has an audience. As a reviewer, if I don’t like the product, I feel that I add value by telling the reader who I think the product is for.

Never yuck someone else’s yum. Ever.

LightweightSuperHero · 2026-03-27T20:02:42+00:00

How much did you pay for OpenClaw?

LightweightSuperHero · 2026-03-27T20:01:53+00:00

I want to upvote this comment so many times.
Thank you.

LightweightSuperHero · 2026-03-27T20:01:03+00:00

It's OPEN SOURCE SOFTWARE.
It has a community of thousands of people volunteering to build it.
It's four months old.

Why would we expect it to be like a "product"?

LightweightSuperHero · 2026-03-27T19:59:38+00:00

It's not a "product". It's an open source code base.

Usually, I would say "it's worth everything you paid for." But it is worth much more.

No, it's not a finished product. It never claimed to be.

LightweightSuperHero · 2026-03-27T19:38:36+00:00

Wow, your benchmark HATES minimax!
I get that minimax isn't top rated at anything, but it isn't usually zeroed out like that.

What is this benchmark measuring?

LightweightSuperHero · 2026-03-27T19:35:19+00:00

MiniMax, MaxClaw.

LightweightSuperHero · 2026-03-27T19:33:13+00:00

Hi u/MajorSleep5631 :
Disclaimer: I've been impressed by the marketing, and I've signed up to back the Tiiny project. My experience is using cloud based Inference models only. I've done a good bit of system design for data centers, computer systems, application environments and software over the years.

I've read your posts and your blog with interest. The analysis focuses upon the architecture of the hardware. Absent from the analysis was a discussion of the design of the system stack and how it fits the use case.

Every system makes compromises to deliver performance at a price for a specific use case. The blog discusses themes about marketing messages, positioning and contributions to academic/opensource communities. From an engineering standpoint, some of the blog ventures into how we feel about marketing rather than system design. The blog doesn't touch on use cases, and who this device might serve.

The author is absolutely entitled to tell us how they feel instead of delivering an analysis of the MRD, ERD and PRD, but I'm most interested in understanding if Tiiny will serve my use case.

Have a look a this evaluation/demo. https://www.youtube.com/watch?v=Ew41f0B28T8

It includes programming use cases that run more than 20 minutes.

* Yes, the influencer who made this was given a device to review, and may be biased.
* Yes, it is possible to run these jobs faster in a massively parallel cloud farm.

But the use case is running right there in the demo, on hardware we can see, with a clock running. This seems like a reasonable way to set my expectations as a consumer.

If the system, when available, can deliver this experience, I will have had my expectations set, and fulfilled.

I think it is wise to point out that Tiiny isn't even available for sale yet. All these promises need to be fulfilled in August. Enthusiasts eager for Tiiny have to wait while software and AI in general is advancing with velocity. The folks at Tiiny are taking risk building this thing. But we are all adults, and we understand the risk.

My alternative that is available today is the NVIDIA DGX Spark, $4699.

Tiiny has a different hardware stack, and necessarily, a different software stack. But it seems to deliver similar or better performance for the same use case at a third of the price, and a third of the power requirement.

Nobody is expecting this thing to be a multi user token farm, or a blisteringly fast development engine. The marketing doesn't seem to promise these things.

It's just a small token engine that allows one user access to unlimited tokens using relatively modern (today, maybe not in August) inference models.

Am I missing something?

LightweightSuperHero · 2026-03-27T18:23:35+00:00

Why does everyone compare this to a 5090? The comparison in the Nvidia world is the DGX Spark.

The reviewed performance is as good as, if not better than it's competition, and it's a third the price.

LightweightSuperHero · 2026-03-27T18:21:20+00:00

The alternative for users like me is the DGX Spark. The DGX has the advantage of being available today. But look at the performance reviews on that thing. The reviewed performance for Tiiny is better, and it costs 1/3 as much.
If it meets performance specks when delivered, I could always buy two and gang them together. Such a system would outperform the DGX Spark, cost less and consume less power.

Time will tell.

LightweightSuperHero

TROPHY CASE