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Models get commoditized.
The harness compounds.
Thanks @SarahPerezTC for the writeup.
Osaurus brings both local and cloud AI models to your Mac techcrunch.com/2026/05/15/os…
We built the investigative journalist agent to test one thing: can a tiny model do real work on sensitive files?
LFM3 did it on day 0, with the Wi-Fi off.
Journalists can't upload a leak to the cloud.
So we turned off the Wi-Fi.
A 1.7B model read the whole case file, followed the money, and cited its sources.
LFM3. Day 0 on Osaurus.
Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence.
> 6 model instances, across text, audio, vision, and omni modalities, generative and decision models.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding
> 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages.
> 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language.
> 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input.
> fine-tune on 1 GPU.
> a new tri-hybrid architecture
> architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒
Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device.
1/ 🧵
What it read:
Contracts. Council minutes. Interviews. Emails. Campaign finance. A leaked ledger.
What it found:
Donations from the winning bidder's staff to the council. A scoring sheet revised before the vote. Lead levels above the federal limit.
30+ steps. 91 seconds. Zero network.
LFM3 1.7B on MLX, native Swift on Apple Silicon.
Small enough to run anywhere. Good enough to do the work. Thanks @liquidai.
github.com/osaurus-ai/osauru…
Osaurus retweeted
Get Osaurus on your phone now! Use your Mac/PC to do all the heavy lifting and inference, while on the go with your iPhone or ipad.
Also, dinos.
I call my agent more than I call my friends now.
Huge work by @RaajeevCn on this one.
Call your agents by voice. Chat on the go. Generate images.
Chats are end-to-end encrypted. Speech recognition and dictation run fully on-device.
Join the TestFlight beta: osaurus.ai/ios
Built by @RaajeevCn
github.com/osaurus-ai/osauru…
Come build with us.
Osaurus retweeted
Nanbeige actually lived up to its expectations, with reasoning on it tended to over reason (not in a way of thinking about things that didn't matter too much like the Qwen series, but much more in a "plans out all the specifics even in a simple job" kind of way), and while I had it turned off for the demo, I know just from the tests I did that it lives up to the claims and competes with Qwen 3.8 27b as a heavy coding capable model.
While cache may be larger due to older arch, Osaurus' efficient cache handling allows for smooth turn by turn usage without your RAM usage going higher than the model's ~20gb.
Nanbeige4.3-33B, day 1 on Osaurus.
Neoclouds are dying. It made a game about it. On a Mac.
🚀Excited to announce Nanbeige4.3-33B!
To push the performance ceiling of small agents, our strategy in Nanbeige4.3 starts with building a powerful teacher first.
Nanbeige4.3-33B delivers SOTA agentic performance among open models at ~30B parameters:
* Strong results on agentic coding and cowork benchmarks.
* When integrated into mainstream agent harnesses, it tackles real-world tasks with cost-efficient inference.
* It will serve as a teacher for upcoming smaller Nanbeige models, starting with Nanbeige4.3-3B.
huggingface.co/Nanbeige/Nanb…
huggingface.co/Nanbeige/Nanb…
#LLM #Agent
Nanbeige4.3-33B JANG_4D
33B dense, 5.24 bits avg, 21.7 GB
Needs Osaurus 0.25.27+
huggingface.co/OsaurusAI/Nan…
Quantized by @dealignai
github.com/osaurus-ai/osauru…
Come build with us.
Local-first is antifragile by default. When agents run on your own hardware, there’s no central endpoint to breach and no single outage that takes everyone down.
We need an "Antifragile Internet" built for the agentic era.
The hacks over the past few days (PHP, Railway, eMudhra, LiteLLM etc) show how fragile the existing Internet has become. AI agents are challenging the Internet's structure in 3 distinct ways:
1/ On the offense side, agents are a weapon - AI finds and exploits bugs on a scale not seen before, and the cost of attack asymptotes to 0. Bugs that used to take human experts weeks and months are easily found, adapted, and exploited by AI agents. Decades of legacy code that ran on "security by obscurity" no longer holds against agents.
2/ On the defense side, agents are a target - AI generated code is often bug-prone. AI agents themselves, as machines of unconstrained output are liable to prompt injections and other types of attacks that can leak keys, PII, and other pieces of information.
3/ On the identity side, agents are dominating Internet activity - this year, machine traffic has already passed human traffic, and may continue to grow 1000x over the next few years. Content and webpages used to human requests and behavior are breaking with agents, and it is increasingly difficult to tell human content from AI content.
All this means we will need to see a ground-up redesigning of the Internet, one with more cryptographic verifiability, identity protocols, rule-enforcement, and other security primitives that eliminate bug categories rather than simply patch them - an "Antifragile Internet" that gets stronger and more secure as more agents participate in it.
This is an emerging thesis area for us at @usv, if you're building in the space please reach out!
More thoughts soon.
Osaurus retweeted
Excited for this. From what I can tell the scores alone show it rivals models like glm53flash. Osaurus users were having good results with Nanbeige 4b so hoping to see how this does even though I know the whole looped thing will make it dirty slow
Replying to @nanbeige
@nanbeige new 33B model beats qwen 3.8 27b
Also, supports a CTX length up to ~524k!
huggingface.co/Nanbeige/Nanb…













