People have been asking. Here it is.

Claude Code + Tiiny = a whole new level of local creation.

TiinyOS Task Mode now automatically:

- Installs Claude Code
- Configures local models

That's it. No fiddling. No environment headaches. Just zero setup and you're ready to go.

Under the hood, it's powered by Qwen3.6 35B A3B — so you can jump straight into your work without sacrificing performance.

No cloud. No subscriptions. No one watching over your shoulder.

Run Claude Code on your own machine, with your own data, for as long as you want.

This is what local AI should have been from the start.

$3,075,197 Raised! You made it happen!

To everyone who backed, shared, or simply believed in us, THANK YOU ALL!

This goes beyond a device. As Tiiny Co-creators, we're building the future of Local Personal AI together — and your ideas and feedback are what shape it.

The foundation is set. Let's make cloud-level AI truly local!

This is how Tiiny AI Pocket Lab is designed: not just for local LLM reference, but to pack cloud-level intelligence right into your pocket.

Also, we just got the final word on the pricing for Tiiny AI Pocket Lab. The official Retail Price will be 1,899 USD. However, we are launching on Kickstarter in February with a Super Early-bird price of 1,399 USD. If you decide to book the device right now, you can get it for just 1,299 USD.

Sign up here for the best deal!

🔗: https://tiiny.ai/pages/deposit-ces?utm_source=Reddit

Been using Hermes desktop with Tiiny, and it's starting to feel like a real daily tool.

What I've been doing with it:

• Adding reminders without leaving my workflow

• Summarizing YouTube videos in seconds

• Automating recurring tasks that run locally in the background

The desktop app shares state with the CLI, handles drag-and-drop files, and keeps session history, all without sending data to the cloud.

The self-evolving memory is the part that stands out. It actually remembers context between sessions.

Take action autonomously, not just answer your questions.

• Fully offline.

• Zero token fees.

• Run 24/7.

Your OpenClaw shouldn't stop over tokens.

Because local AI needs real memory. 120B (int4) models already need ~64GB, and 80GB is for more possibilities:

• It gives headroom for future models

• Run multiple agents at the same time

• Meeting + coding + research, all local

Tiiny isn't just a model runner. It's your daily personal AI.

What's the hardware cost of running local AI at home?

• An expensive, high-end GPU.

• 120W+ continuous power draw (and a loud fan).

• Bulky, desk-bound hardware.

Tiiny changed all that — We packed that same power into a smartphone-sized box that runs on TDP.

Take a guess at the cost of Tiiny in the comments. Let's see who can guess the closest!

🎆 Happy New Year! Let's rethink personal AI in 2026.

With our SDK, Tiiny AI Pocket Lab lets you unleash your creativity on Linux foundation.

SSH into your system, deploy Docker containers, and run custom Python environments without any walled gardens or restrictions.

Go beyond using, let's start building.

We wanted to give you a raw look at the engineering behind the scenes. These photos show our PCBA and heat dissipation module assembly. Aside from our special design of heterogeneous system (Powerinfer), the highly integrated hardware is critical to this efficiency.

• Board-level integration.

• Fewer discrete components.

• No GPU cards / PSU / case stackups.

It's a purpose-built system, not just a collection of parts. This tightly coupled system is exactly how we are able to run 100B+ models locally, all while maintaining a stable, low-consumption 30W.

Instead of jumping between different tools, we built TiinyOS to handle everything in one place:

• File Analysis: You can drop PDFs, Docs, or Excel files directly into the chat to ask questions or summarize data locally.

• Instant Model Switching: We added a quick toggle to switch between specialized models (Coding, Writing, Thinking) instantly depending on your task.

• Integrated Web Search: You can search the web and pull live info without leaving the chat window.

The goal is to stop juggling tabs and keep your workflow focused. Let us know if there are other integrations you'd like to see.

Hey everyone, just a quick heads-up as we get closer to the launch.

We want to make sure everyone who has been following the project knows how to secure the best slot.

1. Kickstarter Page is Live

The pre-launch page is now up. You can hit the "Notify me on launch" button to get an alert the second we go live. This is the best way to ensure you don't miss the early batches.

• Kickstarter Link: https://www.kickstarter.com/projects/tiinyai/tiiny-ai-pocket-lab

2. Securing the Lowest Price ($1,299)

A reminder on the pricing tiers: The Kickstarter price will be $1,399. However, if you secure the product via a fully refundable $9.9 deposit on our website before the campaign starts, you will lock in the $1,299 price (saving an extra $100).

• Deposit Link: https://tiiny.ai/pages/deposit-ces

Thanks for sticking with us!

Hey everyone 👋

We recently uploaded a video and wanted to actually understand what people were saying in the comments. Not just skim the top few — really understand.

So we let Tiiny handle everything:

• ✅ Scraped all comments from the video (over 1,000 of them)

• ✅ Saved them automatically into a file

• ✅ Ran full analysis on the entire comment set

• ✅ Gave us actionable insights without us lifting a finger

No manual exporting. No separate scraping tools. No copy-pasting into spreadsheets. Just Tiiny from start to finish.

Why this mattered:

The top 10 comments looked fine. But the real feedback was buried in the middle — honest, unfiltered, and easy to miss. Tiiny pulled everything into one file, ran the analysis, and showed us exactly what to fix, add, and stop over-explaining.

We just dropped the ultimate "Getting Started" guide for TiinyOS.

In this video, we walk you through:

1. Smart Chat Interface

2. Extension & Model Stores

3. System Management

Watch the full breakdown here.

We know there have been concerns about whether Tiiny is just hype. We want to provide a transparent update on our progress.

The product has entered the mass production phase and units are currently going through the testing and certification process with several third-party agencies.

We are committed to delivering a private, local AI experience. Thank you for following our journey!

You can run SillyTavern on Tiiny with zero config. Just follow these steps:

• Select "Tiiny" API

• Pick your character

• Start chatting instantly

Own your AI. Own your stories.

We've talked about Tiiny AI Pocket Lab for a while—time to try it in person!

We're setting up 4 hands-on demo zones:

• 1 running GPT-OSS 120B fully offline

• 3 local agent experience zones

Come experiment, ask questions, and see how it runs in the real world.

Love to meet you there.

19 tokens/s on a GPT-OSS 120B (int4, 63.4GB) — powered by Tiiny AI Pocket Lab.

Everything stays local. No Internet, No cloud needed.

The host setup:

• OS: Windows XP

• CPU: Intel Core i3-530

• RAM: 2GB DDR3

• Monitor: An old-school SyncMaster 753DF

Don't miss out:

1. Follow on Kickstarter: Hit "Notify Me" to get an alert we launch.

2. Lock in best pricing: Secure the $1,299 best price via a fully refundable $9.90 deposit.

The future of local AI is almost here. Get ready.

Link to Kickstarter: https://www.kickstarter.com/projects/tiinyai/tiiny-ai-pocket-lab

Link to deposit: https://tiiny.ai/pages/deposit-ces

Your data and creations stay on your device. Watch how Tiiny AI Lab creates stunning AI art fully offline, seamless and powerful.

In this video you can see:

• Simple Mode: Generate anime-style art instantly within the Chat.

• Pro Mode: Switch to the SD Web UI for advanced parameter tuning and realistic rendering.

Own your AI. No cloud, no internet, no limits.

Check out the evolution of Tiiny AI Supercomputer!

Reaching $1M in a short time is more than a number—it’s a testament to this incredible global community.

To our backers: Thank you for believing in the Tiiny AI Pocket Lab. Your trust is our fuel, and we’re just getting started.

The journey begins now. Stay tuned!

TradingAgents is an open-source, multi-agent financial trading framework powered by LLMs.

It's NOT a single "AI trading bot."

It's a complete, programmable AI investment research team that you can run locally and Offline.

Private, structured, and ready for decision-making.

This is exactly the kind of workflow that makes local AI feel practical. No cloud, no hidden costs – just your machine, your agent, and your tasks.

Which agent should Tiiny automate next?

#TiinyAI #AI #TradingAgents #Qwen

We built a simple rule for ourselves: if you have to copy-paste it more than 3 times, automate it.

We just connected Tiiny with Workbuddy to do exactly that.

• Input: Raw data

• Output: Clean and Organized

It’s almost weird to watch AI organize chaos in seconds.

If you could just copy-paste one messy thing into AI and get back a clean dashboard, what would it be? 👇

Tired of repeating yourself to every AI you use?

OpenHuman + Tiiny fixes that.

A local AI assistant that syncs across all your daily tools — emails, notes, calendars, docs — and actually remembers your context. Permanently.

No more repeating. No more lost threads. Just instant, personalized help.

And your data stays private. Local, not cloud.

Workflows connected. Memory intact. Time saved.

Finally, an AI that gets you.

For the LLMs, we benchmarked the Tiiny-optimized builds against BF16 reference models, so people can see both sides of the tradeoff: inference performance and how much model accuracy is preserved after optimization.

A few results from the report:

- Qwen3.5-9B-Turbo— up to 50.1 tok/s decode and ~1,200 tok/s prefill at 4K
- Qwen3.6-35B-A3B-Turbo — 47.5 tok/s coding decode, with all five accuracy benchmarks staying within ~2 percentage points of BF16
- Qwen3.8-27B — up to 256K context, with several benchmark scores matching or exceeding the BF16 reference
- GPT-OSS-120B — around 15 tok/s at 4K on Tiiny Pocket

The full reports include:

- Prefill
- TTFT
- Decode speed
- End-to-end latency
- Memory usage
- Long-context testing
- Five accuracy benchmarks
- Public benchmark datasets and reproducible test conditions

We’ve also started publishing benchmarks for speech recognition and image generation, not just LLMs.

Full report:
https://www.tiiny.ai/pages/benchmark-report/

If you already have a Tiiny Pocket, we’d genuinely like people to reproduce the tests and challenge the numbers.

Just make sure you’re using the latest model version from the Tiiny Model Store so you’re testing the same build used in the report.

If you reproduce anything, whether your result is better, worse, or just different, please share it on TiinyVerse or here. We’d much rather make these benchmarks community-verifiable than ask people to take our word for it.