Hicap
One API for every model. Faster, cheaper inference.
What it does
Spend Up to 25% Less, Run AI Smarter and Secure, enterprise-ready access to top models from OpenAI, Gemini & Anthropic with up to 25% lower inference costs. Built for Speed, Savings, and Scale. For teams that need to move fast, cut costs, and grow without limits. Get Started in Under 5 Minutes No provisioning queues, no…
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- NTNCompass Technologies – yet another AI Inference API, but hear us out2024 · ncompass.tech · ▲37
Hello HackerNews! I’m excited to share what we’ve been working on at nCompass Technologies: an AI inference* platform that gives you a scalable and reliable API to access any open-source AI model — with no rate limits. We don't have rate limits as optimizations we made to our AI model serving software enable us to support a high number of concurrent requests without degrading quality of service for you as a user. If you’re thinking, well aren’t there a bunch of these already? So were we when we started nCompass. When using other APIs, we found that they weren’t reliable enough to be able to…
- GAGradient – a web API for fine-tuning and deploying Llama22023 · gradient.ai · ▲26
We’ve just launched Gradient — an API that helps you build private LLMs that you own. We simplify inference and fine-tuning on open-source LLMs such as llama2, and you only pay by the token. Our API platform makes it possible for you to create private models with a single API call. Run inference on your fine tuned model instantly with no cold boot (and no need to pay for compute costs). The product is truly on demand - when you run fine tuning and inference on our platform, there's nearly 0 startup latency for these API calls. And you're not paying for the compute, you just pay for the…
- FTFree tool to find and compare AI models for your project2024 · app.elementera.ca · ▲13
Hey HN! When implementing an AI-powered feature for a project, we—and many people we've talked to—often reach a point where we have to choose an AI model but aren’t sure which one best fits our constraints or where to even start. Unfortunately, the advice to "just use chatgpt" is not always a good one. What if I want an open-source model? What languages does it support? What about context window size or the number of parameters? There are thousands of AI models already out there and many of them are perfect for certain problems. That’s why we’ve carved out this part of our product as a free…
- BOBhumi–OSS Python Library w Rust Underhead for 2.5x Faster LLM Inference2025 · bhumi.trilok.ai · ▲8
Read the full blogpost at https://rach.codes/blog/Introducing-Bhumi (click on reader to see the technical breakdown!) AI inference should be fast, but in practice it’s painfully slow. Inference bottlenecks slow down LLM-powered chatbots and AI workflows everywhere. I built Bhumi to fix that. Bhumi is a Python library designed for developers, yet its performance-critical core is implemented in Rust (via PyO3) for near-native speed. This hybrid approach delivers up to 2.5x faster response times across providers like OpenAI, Anthropic, and Gemini—without changing the…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
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AI · 18d ago · company-app.joinastute.com
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…
AI · 27d ago · cactuscompute.com
