I would like to share my latest open source local LLM inference tool implemented in C#. It supports models like Gemma4, Qwen3.6 with multi-modal (image, vision, audio), reasoning and function tool. It can run on Windows/MacOS/Linux and fully leverage GPU's capability. The API is completely compatible with OpenAI and Ollama interface.

Really appreciated if you can try it and give me some feedback. If you like it, it will be a big thank you if you can star it. Thank you very much!

I spent the last few months building a new sparse fine-tuning method for MoE models called USAF.

The goal was simple: if your GPU can run inference on an MoE model, it should also be able to fine-tune it.

On my AMD RX 6750 XT (12 GB), I can fine-tune Qwen3-30B-A3B by training sparse expert weights and the router instead of adapters.

The project is completely open source under the Apache 2.0 license. I'm not trying to build a business, sell anything, or monetize it in any way—I just wanted to share something I built that I think is genuinely interesting.

GitHub: https://github.com/tsuyu122/usaf

https://x.com/KanikaBK/status/2072606006971081213

https://github.com/alibaba/page-agent

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100+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://x.com/hasantoxr/status/2071519541851717838

https://github.com/allenai/olmocr

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https://x.com/sharbel/status/2070568492022079922

https://github.com/tashfeenahmed/freellmapi

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https://x.com/coinbureau/status/2071330294452666695

The concern seems to be that once powerful models are released openly, access cannot really be revoked, safety layers can be removed, and misuse becomes much harder to control.

But the counterargument is obvious: open source also improves transparency, research, competition, and trust.

What do you think and why?

https://x.com/HowToPrompt__/status/2071547896458358866

https://github.com/vas3k/TaxHacker

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È solo uno scenario irreale e puramente di fantasia ma...

① I big tech (Meta, Google, Microsoft) acquistano HBM3e in volumi enormi con potere contrattuale brutale → i produttori DRAM comprimono i margini HBM3e per aggiudicarsi i contratti.

② Il margine compresso viene recuperato sul segmento consumer DDR5, dove l'acquirente è frammentato, disinformato e senza alternativa → i prezzi DDR5 vengono gonfiati oltre il giustificabile dal costo di produzione.

③ Il consumatore che vuole inferenza locale è costretto ad acquistare quantità elevate di RAM costosa per ottenere prestazioni appena accettabili → il costo dell'hardware locale supera rapidamente anni di abbonamento.

④ L'alternativa "conveniente" è già pronta, scalabile e profittevole → abbonamento mensile all'AI del big tech che ha pagato la HBM3e a prezzo scontato grazie all'obolo nascosto versato al punto ②.

Nessun patto è necessario. Il mercato oligopolistico lo fa da solo. Il risultato è identico a una collusione, con il vantaggio dell'immunità legale.

https://x.com/israfill/status/2070915206130413737

https://github.com/Panniantong/Agent-Reach

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"OpenHands Agent Canvas turns your coding agents into a self-hosted, always-on engineering team. It's a developer control center for starting conversations and automating everyday tasks — like generating reports that publish to Slack or automatically decomposing GitHub issues into tasks.

It runs locally on your machine by default, but can connect to multiple “agent backends”, e.g. running agents in Docker containers, on VMs, or within your company infrastructure. You can optionally choose to run agents on OpenHands Cloud or OpenHands Enterprise infrastructure."

https://github.com/OpenHands/OpenHands

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https://x.com/sharbel/status/2063369348828610886

https://github.com/mvanhorn/last30days-skill

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https://x.com/ornith_/status/2070148887067963854

https://huggingface.co/collections/deepreinforce-ai/ornith-10

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https://x.com/liquidai/status/2070148140368318884

https://huggingface.co/LiquidAI/LFM2.5-230M

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https://x.com/Alibaba_Qwen/status/2069720365442719867

https://github.com/QwenLM/Qwen-AgentWorld

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https://x.com/HowToPrompt__/status/2065007846866161906

https://github.com/apple/coreai-models

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https://x.com/nanobot_project/status/2069253447644590122

https://github.com/HKUDS/nanobot

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https://x.com/BaiduAI_News/status/2069322806748410291

https://github.com/baidu/Unlimited-OCR

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Hi everyone, we at Sentient Foundation are launching an Open Source AGI Grant and Investment Program, a $42M commitment for developers, researchers, open-source maintainers, public-goods builders, and startups building or leveraging AI in the open.

Our thesis is simple: the most important technology being built right now should not end up controlled by a handful of closed platforms. A few companies are moving toward metered, revocable access to intelligence. We want to help make sure open builders have the resources to compete.

The program has two tracks:

1. Grants for public goods

For open-source maintainers, independent researchers, developers, and public-goods projects.

No equity. No lockups. No claim on your work. You keep what you build.

2. Investments for companies built to scale

For startups and teams building commercial companies around open AI technologies, using founder-friendly structures.

We’re especially interested in projects that make AI genuinely useful and accessible to people who are often skipped by the market. Examples include:

• Local and privacy focused AI tools built for phones, laptops, and other low-cost personal devices
• Medical, education, agriculture, elder-care, and anti-scam tools for underserved communities
• Trust infrastructure for open models, agents, identity, verification, privacy, and decentralized compute
• Products that are private by default and empowering rather than extractive

Projects do not need to open-source every part of their stack to qualify. What matters is that at least one essential component is open and meaningfully contributes to the project’s value and adoption.

Applications are reviewed on a rolling basis, with no cohorts and no fixed deadline.

We’re launching alongside ecosystem partners including Alibaba Cloud and Princeton University.

• More details: https://sentient.foundation/grants
• Apply here: https://form.typeform.com/to/IRj7WaKH

Happy to answer questions here. We’d especially love to hear from builders working on open models, local AI, agent infrastructure, privacy-preserving AI, evaluation, multilingual tools, and applications for communities that are usually overlooked.

https://huggingface.co/nvidia/Nemotron-3.5-Content-Safety

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https://x.com/Zai_org/status/2066938937344495629

https://huggingface.co/zai-org/GLM-5.2

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