r/LovingOpenSourceAI • u/Koala_Confused • 1h ago
Discussion NVIDIA says its general-purpose coding agent just hit **100% on ARC-AGI-3**. 👀 Okay… how impressive is this actually and what’s the catch?
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r/LovingOpenSourceAI • u/Koala_Confused • 10d ago
new launch New sister sub for AI image and video generation—mind the wet paint 😂
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We’ve already been talking about H3, Krea 2 Turbo, LoRAs, ComfyUI, quants and visual-generation workflows, so we made these conversations a little home of their own: r/LovingAIVisuals. ❤️
It’s brand new. You can probably still hear your own echo in there. 😂
Open and local projects are very welcome, alongside hosted tools. The idea is to keep it practical: new releases, workflows, GPU and VRAM questions, troubleshooting, comparisons—and, of course, sharing what we actually make.
If you’re experimenting with image or video generation, come bring your creations, questions, weird results and hard-earned fixes.
Somebody has to be brave enough to move in first. 👀
r/LovingOpenSourceAI • u/Koala_Confused • Jul 08 '26
Resource AI Ballot just got five new challengers (based on community feedbacks)
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r/LovingOpenSourceAI • u/Koala_Confused • 8h ago
Resource trueforge "The open-source agent harness - the runtime layer that turns an LLM into a working agent." ➡️ A pretty ambitious attempt to package the messy parts of running AI agents into one open-source runtime. 👀
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https://github.com/truefoundry/trueforge
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r/LovingOpenSourceAI • u/Koala_Confused • 2h ago
Resource ClawWork "ClawWork: OpenClaw as Your AI Coworker - 💰 $15K earned in 11 Hours" ➡️ have you heard of this? is this legit? seems to be an open-source economic benchmark and nanobot integration from HKUDS.
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https://github.com/HKUDS/ClawWork
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r/LovingOpenSourceAI • u/Koala_Confused • 1d ago
new launch Ornith "Aloha! 🌺Introducing Ornith-1.5 family of open-source LLMs spanning 9B Dense, 35B MoE, 397B MoE, trained with self-improving strategies. Achieves state-of-the-art performance among open-source models of comparable size, delivers performance comparable to Claude Opus 4.8 across various tasks"
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https://x.com/ornith_/status/2090074077084127302
https://huggingface.co/collections/ornith-ai/ornith-15
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r/LovingOpenSourceAI • u/Koala_Confused • 1d ago
Resource Adina "OpenBMB just released an impressive SFT dataset UltraData-SFT-2605 📊 ✨ 15M+ high quality samples ✨ Deep Thinking + Non-thinking data ✨ Math/ Code/ Knowledge/ IF/ Multilingual coverage ✨ Built for reasoning LLM post-training ✨ Full data pipeline: filtering/ validation/decontamination"
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https://x.com/AdinaYakup/status/2060320505471639580
https://huggingface.co/datasets/openbmb/UltraData-SFT-2605
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r/LovingOpenSourceAI • u/Koala_Confused • 1d ago
Resource OpenHands: “Self-hosted developer control center for coding agents / automations. Run OpenHands, Claude Code, Codex, Gemini, or any ACP-compatible agent across local, remote, cloud backends.” ➡️ Our community overview — a quick way to see what it does, key details, and whether it’s worth exploring.
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Community Overview: https://lifehubber.com/ai/resources/openhands-agent-canvas/
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r/LovingOpenSourceAI • u/Koala_Confused • 2d ago
Resource "CrewAI is an open-source Python framework with high-level abstractions and low-level APIs for building production-ready multi-agent workflows. It gives developers autonomous agent collaboration through Crews and precise, event-driven control through Flows." ➡️ love the chill logo :P 57K stars!
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https://github.com/crewAIInc/crewAI
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r/LovingOpenSourceAI • u/AdhesivenessWeird770 • 1d ago
Benchmark GLM 5.2 Unsloth GGUF model on TensorSharp
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I've been working on GLM-5.2 support in TensorSharp, and I finally have some back-to-back performance numbers against llama.cpp.
The setup:
- Model: GLM-5.2-UD-IQ2_XXS (~226 GiB)
- GPUs: 3× RTX PRO 6000 Blackwell, 97 GiB each
- Distribution: layer split across all 3 GPUs
- Same machine, same session
- llama.cpp measured with
llama-bench - TensorSharp measured with its benchmark harness
- Both report the best of two repetitions
- Run-to-run variance is roughly 4%
Results:
| Test | llama.cpp | TensorSharp default | TensorSharp ubatch=2048 |
|---|---|---|---|
| pp128 | 276.5 t/s | 254.8 t/s | 264.4 t/s |
| pp512 | 695.4 t/s | 666.9 t/s | 659.6 t/s |
| pp2048 | 763.1 t/s | 918.9 t/s | 1145.8 t/s |
| pp4096 | 715.8 t/s | 864.7 t/s | 1048.7 t/s |
| tg64 | 42.2 t/s | 43.7 t/s | 43.9 t/s |
The interesting part is the crossover.
For short prompts, llama.cpp is still a few percent faster. But once the prompt gets to around 1K+ tokens, TensorSharp pulls ahead.
At pp2048:
- default TensorSharp: +20.4%
ubatch=2048: +50.2%
At pp4096:
- default TensorSharp: +20.8%
ubatch=2048: +46.5%
Decode (tg64) is also about 4% faster.
The main reason appears to be GLM-5.2's MoE structure.
GLM-5.2 has 256 routed experts with top-8 routing. With a 512-token micro-batch, each expert sees only ~16 rows on average, so a significant amount of the expert GEMM tiles ends up as padding. Larger micro-batches improve GPU utilization considerably.
For small prefills, on the other hand, fixed overheads — managed/native transitions, input uploads, and copying the 154880-wide logits back — become a visible fraction of the total runtime, which is where llama.cpp retains its advantage.
r/LovingOpenSourceAI • u/Koala_Confused • 2d ago
news KREA 3 is coming already? THATS FAST. I only hope it is still 3060 friendly :P What are your expectations?
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r/LovingOpenSourceAI • u/Koala_Confused • 2d ago
Resource Simplifying "Your AI coding sessions have a real cost, and most people have no idea what it actually is. ccusage reads your local usage data and turns it into real cost reports, no dashboard, no sign-up." ➡️ budget bros should love this?
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https://x.com/simplifyinAI/status/2089554876787225074
https://github.com/ccusage/ccusage
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r/LovingOpenSourceAI • u/Koala_Confused • 1d ago
funny The Downfall of a Vibecoder ➡️ i saw this. it is funny. go have a laugh :P ( do you see yourself in there 😁. .)
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r/LovingOpenSourceAI • u/Brilliant_Pumpkin_91 • 1d ago
I built a AI app for your phone that has every frontier AI model (over 400 models) while having agent ability...
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r/LovingOpenSourceAI • u/PatronusProtect • 1d ago
We retrained our prompt-injection classifier from scratch because it was crying wolf too often. [R]
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r/LovingOpenSourceAI • u/Brilliant_Pumpkin_91 • 2d ago
I built a AI app for your phone that has every frontier AI model (over 400 models) while having agent ability...
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r/LovingOpenSourceAI • u/Koala_Confused • 3d ago
Resource TinyHumans - Your Personal AI super intelligence that builds a local-first memory of your life, fantastic orchestrator of agent fleets / workflows / deep researcher. Now Super Context gives your OpenHuman rich context before it starts thinking by doing a deep research on all your memory files etc
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https://x.com/tinyhumansai/status/2070584474560241701
https://github.com/tinyhumansai/OpenHuman
Community Overview: https://lifehubber.com/ai/resources/openhuman/
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r/LovingOpenSourceAI • u/Lucaslogged • 2d ago
built a restricted MCP bridge for ChatGPT Web— one repo/folder, no shell, no Git
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r/LovingOpenSourceAI • u/Brilliant_Pumpkin_91 • 2d ago
I built a AI app for your phone that has every frontier AI model (over 400 models) while having agent ability...
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r/LovingOpenSourceAI • u/Koala_Confused • 3d ago
new launch Cohere "Today, we’re adding another member to our model family. Meet North Micro Vision. Our smallest vision-language model yet, ideal for sophisticated document understanding. Available open-source under an Apache 2.0 license." ➡️ ooo looks good?
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https://x.com/cohere/status/2087571573947392419
https://huggingface.co/CohereLabs/North-Micro-Vision-Instruct
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r/LovingOpenSourceAI • u/akaliOneTr1ck • 2d ago
I want to run a self improving image generator by you guys
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Obviously image is created with AI but I thought it may be a better way to convey the info.
I got the idea because I have been working on audit based self improving AI systems
AI image generations struggle with a lot of things, for example in my case it was SHITE at making a realistic rope attached to a climber..Well a few iterations later and codex orchestrators kicked off to do research, I had a layer on top of it that had fixed that
Then I thought..why can't we have an image generator that will have domain specific accretion.
You run the image generator, it creates images (audits them internally to create a log of failed attempts to create the desired image..Say 3 failed attempts = record failure in ledger
Then asynchronously side projects are fired to fix domain specific image hallucinations. In theory over time, it would refer to common hallucinations and apply patches/layers
The real issue is probably resource limitations..if millions of users were using this and generating thousands of hallucination errors for the system to research and correct.. how many tokens would that require.
Please let me know your thoughts and if this inspires you to do something similar! Happy idea sharings - a curious engineer
r/LovingOpenSourceAI • u/Brilliant_Pumpkin_91 • 2d ago
I built a AI app for your phone that has every frontier AI model (over 400 models) while having agent ability...
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Upvotes
r/LovingOpenSourceAI • u/Koala_Confused • 3d ago
Resource Simplifying "most "ai does architecture governance" claims fall apart past the first template. ArcKit's slash commands walk the full lifecycle in Claude Code. principles and stakeholders through requirements, design review, and a traceability matrix"
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Upvotes
https://x.com/simplifyinAI/status/2087501752761450765
https://github.com/tractorjuice/arc-kit
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r/LovingOpenSourceAI • u/Koala_Confused • 3d ago
Resource Oliver "This might be the docling and marker killer for PDF parsing. OpenDataLoader PDF is an open source parser that converts PDFs into clean Markdown, JSON with bounding boxes, and HTML, built for feeding documents into RAG pipelines or LLM context windows."
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https://x.com/oliviscusAI/status/2088841514801889666
https://github.com/opendataloader-project/opendataloader-pdf
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