Thomas Gatt 🇲🇹

35-year old from Malta 🇲🇹. Passionate about #web dev, #data #science and #AI. Deputy Director / Institute of ICT at @MCASTmt. Master of Science in #AI.

[Nous Research @NousResearch]

Hermes Agent is now #1 on the Global @OpenRouter token rankings.

While our journey together has just begun, we'd like to take this opportunity to thank our contributors, supporters, and users for all they have done to get us this far.

[Qwen @Alibaba_Qwen]

🚀 Meet Qwen3.6-27B, our latest dense, open-source model, packing flagship-level coding power!

Yes, 27B, and Qwen3.6-27B punches way above its weight. 👇

What's new:
🧠 Outstanding agentic coding — surpasses Qwen3.5-397B-A17B across all major coding benchmarks
💡 Strong reasoning across text & multimodal tasks
🔄 Supports thinking & non-thinking modes
✅ Apache 2.0 — fully open, fully yours

Smaller model. Bigger results. Community's favorite. ❤️
We can't wait to see what you build with Qwen3.6-27B! 👀

🔗👇
Blog: https://t.co/P2Zx7FwMxB
Qwen Studio: https://t.co/c4vm4LuZrU
Github: https://t.co/zKDEbv0R4U
Hugging Face:
https://t.co/N67hyzxvfr
https://t.co/SSdtbWRDap
ModelScope:
https://t.co/xODf1pj9kw
https://t.co/xXhoqlJ2AB

[Thomas Gatt 🇲🇹 @thomasgatt]

@prof_jpe Agreed!

[Thomas Gatt 🇲🇹 @thomasgatt]

@sudoingX How is the output of this model when compared to sonnet or gemini 3?

[Thomas Gatt 🇲🇹 @thomasgatt]

@AlexFinn Please stop misleading people with your posts.

[Google AI Developers @googleaidevs]

3.1 Pro can generate website-ready, animated SVGs from a simple text prompt. Since these are built in pure code and not pixels, they stay crisp at any scale with incredibly small file sizes. Check out the difference:

[Logan Kilpatrick @OfficialLoganK]

Introducing Gemini 3.1 Pro, our new SOTA model across most reasoning, coding, and stem use cases!

[Thomas Gatt 🇲🇹 @thomasgatt]

@AlexFinn What local models are you planning to use?

[Thomas Gatt 🇲🇹 @thomasgatt]

Gemini 3 is out! https://t.co/CSMvXvKAty

[Thomas Gatt 🇲🇹 @thomasgatt]

@GoogleAI @alexanderchen @GoogleLabs Wow!

[Thomas Gatt 🇲🇹 @thomasgatt]

@DenisJeliazkov Get your facts right. The least you can do is compare like with like and latest with latest.

[Google Gemini @GeminiApp]

Today, we’re making big upgrades to the performance and availability of our most popular Gemini features, and adding a new feature that will make Gemini even more personal and helpful: https://t.co/kc685gizg6

Let’s break down today’s updates 🧵⬇️

[ollama @ollama]

ollama run llama3.3

🤯🤯🤯 llama 3.3 70B has similar performance as the 405B model

https://t.co/Q4Va7JHmGr

[Thomas Gatt 🇲🇹 @thomasgatt]

@Ashcryptoreal You call that pumping hard?

[Thomas Gatt 🇲🇹 @thomasgatt]

Meta just released Llama 3.1, their most advanced open-source #AI model yet! https://t.co/RF01uxQ0Ju

[Thomas Gatt 🇲🇹 @thomasgatt]

@dylanseychell @UMmalta @TheTimesofMalta @IEEEorg @IEEEXplore @ieeecis Interesting!

[Jeff Dean @JeffDean]

Gemini 1.5 Pro - A highly capable multimodal model with a 10M token context length

Today we are releasing the first demonstrations of the capabilities of the Gemini 1.5 series, with the Gemini 1.5 Pro model. One of the key differentiators of this model is its incredibly long context capabilities, supporting millions of tokens of multimodal input. The multimodal capabilities of the model means you can interact in sophisticated ways with entire books, very long document collections, codebases of hundreds of thousands of lines across hundreds of files, full movies, entire podcast series, and more.

Gemini 1.5 was built by an amazing team of people from @GoogleDeepMind, @GoogleResearch, and elsewhere at @Google. @OriolVinyals (my co-technical lead for the project) and I are incredibly proud of the whole team, and we’re so excited to be sharing this work and what long context and in-context learning can mean for you today!

There’s lots of material about this, some of which are linked to below.

Main blog post:
https://t.co/QAsDKXBdao

Technical report:
“Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context”
https://t.co/CTzTHNDCdo

Videos of interactions with the model that highlight its long context abilities:
Understanding the three.js codebase: https://t.co/yq7d6OSD6c
Analyzing a 45 minute Buster Keaton movie: https://t.co/adyMgDYHoK
Apollo 11 transcript interaction: https://t.co/Pqvq3Eac1R

Starting today, we’re offering a limited preview of 1.5 Pro to developers and enterprise customers via AI Studio and Vertex AI. Read more about this on these blogs:
Google for Developers blog:
https://t.co/x73Vun0kVS
Google Cloud blog:
https://t.co/OlaTW6PYGn

We’ll also introduce 1.5 Pro with a standard 128,000 token context window when the model is ready for a wider release. Coming soon, we plan to introduce pricing tiers that start at the standard 128,000 context window and scale up to 1 million tokens, as we improve the model.

Early testers can try the 1 million token context window at no cost during the testing period. We’re excited to see what developer’s creativity unlocks with a very long context window.

Let me walk you through the capabilities of the model and what I’m excited about!

[Martin Nebelong @MartinNebelong]

As you know, my explorations of the Gen AI space is ultimately all about creative control. You should be able to shape the generative matter using all your artistic sensibilities and your aesthetic sense.

OpenAI's Sora is a huge technological leap, but what excites me the most about it is the modalities where it depends on input other than text alone. Such as video to video. Here's an example of how Sora can change an input video.

Base video🧵

[Matthew Berman @MatthewBerman]

Google Deep Mind researchers just dropped a HUGE advancement in robotics 🤖

It is truly mind-blowing.

A "robot in every household" is closer than we think.

Here's everything you need to know about the Mobile Aloha robot (& more demo videos):

👇

[Thomas Gatt 🇲🇹 @thomasgatt]

Hands-on with Gemini: Interacting with multimodal AI https://t.co/CbpQ99SC0F