Open Source VS Open Weight
🚀 Introducing DeepInfer, our in-house inference framework, now fully open source!
Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable.
🔗 github.com/deepseek-ai/DeepI…
1/4
Wait, it's happening?
Muse Spark Open -- weights releasing today -- runs great on new Mac Studios thanks to work with @johnternus and Apple.
882 tests so far.
I think AI unit tests are not all bad. They force AI to build a working LSP.
A static Kotlin LSP is coming.
Powered by Rust and completely JVM-free.
It's fast and will be faster. It takes 1.3s to index 900 kt files and 2.3k dependency jars on M4 (no cache).
It supports:
- Basic type inference
- Auto completion
- Auto import
- Find references
and more
No Anthropic.
So you start to think why Anthropic is now leading the AI race...
SynthID Detector is now available to everyone. 🌐
Check whether online content was generated using @GoogleAI, or with tools from our industry partners – including @OpenAI, @NVIDIA, Kakao and coming soon, @Apple.
Try it out → synthid.com
What?
Meet Mistral Large 4, aka Le Chonk.
• 1T parameters, natively multimodal. 49B active.
It is the best open weights model from US or Europe on aggregated benchmarks.
• State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding.
• Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure.
• Available to all via API today. Working with cybersecurity partners privately.
Open weights release end of October.
What? No... 3.7 Flash is better than 3.8 Flash


















