Alternatives
Products that do what VantaCore does
Compress AI sessions by 98.87% in 0.19 seconds
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
27d ago · cactuscompute.com
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Hello HN, I don't post on here much, but wanted to get some eyes on a new project I'm just launching. I think we definitely need one more AI code agent.. I'm a long-term C++ dev, and over 30+ years I've created some successful audio dev tools (JUCE, the Tracktion DAW, the Cmajor DSP language). All of these came from me getting annoyed with something I had to use, and deciding to have a go at my own take on whatever it was. So Juggler is my attempt at an AI code agent, after spending too many hours loving what the models could do, but hating the CLI experience, and having some opinions of…
Jul 2026 · github.com
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2023 · github.com
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The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.
Mar 2026 · github.com
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I’m a former Systems Architect (Cisco/VMware) turned builder in Thailand. TheAuditor v2.0 is a complete architectural rewrite (800+ commits) of the prototype I posted three months ago. The "A-ha" moment for me didn't come from a success; it came from a massive failure. I was trying to use AI to refactor a complex schema change (a foundation change from "Products" to "ProductsVariants"), and due to the scope of it, it failed spectacularly. I realized two things: * Context Collapse: The AI couldn't keep enough files in its context window to understand the full scope of the refactor, so it…
Dec 2025 · github.com
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I wanted to know how fast a 26B mixture-of-experts model could run on a desktop CPU with no GPU. Got ~40 tok/s single-stream (lossless) and ~124 batched. The surprising part was the byte budget: for this model you compress the output head (32% of per-token bytes), not the experts (16%). The writeup has the bandwidth roofline and the dead-ends; the repo has the reproducible recipe. Happy to answer questions. Repo: https://github.com/arun-prasath2005/gemma4-cpu-moe
Jun 2026 · apeg.dev
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An agent that remembers across sessions can keep its memory as curated markdown files, as an auto-mined structured store, or as trained experience.
22d ago · pinglin.tw
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Hey guys, I made a VS Code extension, within which you can use the Mixtral 8x7B AI model for free. Mixtral 8x7B is a new AI model from the Mistral family, which outperforms GPT-3 in many benchmarks, a fact that I have personally confirmed in daily coding tasks, where Mistral 8x7B was the clear winner. You can use all the AI features, such as AI Lens with custom instructions and similar. I'm pretty sure some of features will be useful to you. I'd appreciate both, positive and negative feedback!
2023 · marketplace.visualstudio.com
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Cut AI API bills by 40% with local prompt compression.
May 2026 · rajashekar41.gumroad.com
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We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…
2025 · github.com
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Hi HN! Since the launch of JigsawStack.com, we've been trying to dive deeper into fully managed AI APIs built and fine tuned for specific use cases. Audio/video transcription was one of the more basic things and we wanted the best open source model at this point it is OpenAI's whisper large v3 model based on the number of languages it supports and its accuracy. The thing is, the model is huge and requires tons of GPU power for it to run efficiently at scale. Even OpenAI doesn't provide an API for their best transcription model while only providing whisper v2 at a pretty high price. I…
2024 · github.com
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Hello HN, new user here, so please let me know if I break some rules. Currently I've been working on training reinforcement learning agents, and OpenAI gym, while is great, runs only one agent at a time. Hence I decided to extend it. I built a wrapper around OpenAI gym, such that it now runs several environments concurrently. All while (mostly) having the same call signature as OpenAI gym. And it is published to PyPI for anyone interested. For more details, please visit: https://github.com/Chimpan-Z/agymc Feedback really appreciated! Have a good day everyone!
2020
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Hey HN, I'm Josiah. We love voice dictation, but wanted an open source version for transparency, privacy, and something that everyone could contribute to. So we built Voquill, an open source alternative to WisprFlow, Monologue, and Willow. It lets you dictate into any desktop app. Press a hotkey, talk, text gets inserted. You can run Whisper locally, use our server, or wire up any provider you want (OpenAI, Claude, Groq, OpenRouter, whatever). You have full control over where your data goes. Runs on Windows, macOS, and Linux. Open source, AGPLv3, built with Tauri and Rust. We're working on a…
Feb 2026 · github.com
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