A 4-bit reasoning model with frontier-level performance
Alpie Core is a 32B reasoning model trained, fine-tuned, and served entirely at 4-bit precision. Built with a reasoning-first design, it delivers strong performance in multi-step reasoning and coding while using a fraction of the compute of full-precision models. Alpie Core is open source, OpenAI-compatible, supports long context, and is available via Hugging Face, Ollama, and a hosted API for real-world use.
Modern AI keeps getting better, but only if you can afford massive GPUs and memory. We didn’t think that was sustainable or accessible for most builders, so we took a different path.
Alpie Core is a 32B reasoning model trained, fine-tuned, and served entirely at 4-bit precision. It delivers strong multi-step reasoning, coding, and analytical performance while dramatically reducing memory footprint and inference cost, without relying on brute-force scaling.
It supports 65K context, is open source (Apache 2.0), OpenAI-compatible, and runs efficiently on practical, lower-end GPUs. You can use it today via Hugging Face, Ollama, our hosted API, or the 169Pi Playground.
To keep you building over Christmas and the New Year, we’re offering 5 million free tokens on your first API usage, so you can test, benchmark, and ship without friction.
This launch brings the model, benchmarks, api access, and infrastructure together in one place, and we’d love feedback from builders, researchers, and infra teams. Questions, critiques, and comparisons are all welcome as we shape v2.
About Alpie Core on Product Hunt
“A 4-bit reasoning model with frontier-level performance”
Alpie Core launched on Product Hunt on December 27th, 2025 and earned 177 upvotes and 12 comments, placing #4 on the daily leaderboard. Alpie Core is a 32B reasoning model trained, fine-tuned, and served entirely at 4-bit precision. Built with a reasoning-first design, it delivers strong performance in multi-step reasoning and coding while using a fraction of the compute of full-precision models. Alpie Core is open source, OpenAI-compatible, supports long context, and is available via Hugging Face, Ollama, and a hosted API for real-world use.
On the analytics side, Alpie Core competes within API, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Alpie Core performed against the three products that launched closest to it on the same day.
Who hunted Alpie Core?
Alpie Core was hunted by Chirag Arya. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Alpie Core including community comment highlights and product details, visit the product overview.
Chirag Arya
Hey builders
Modern AI keeps getting better, but only if you can afford massive GPUs and memory. We didn’t think that was sustainable or accessible for most builders, so we took a different path.
Alpie Core is a 32B reasoning model trained, fine-tuned, and served entirely at 4-bit precision. It delivers strong multi-step reasoning, coding, and analytical performance while dramatically reducing memory footprint and inference cost, without relying on brute-force scaling.
It supports 65K context, is open source (Apache 2.0), OpenAI-compatible, and runs efficiently on practical, lower-end GPUs. You can use it today via Hugging Face, Ollama, our hosted API, or the 169Pi Playground.
To keep you building over Christmas and the New Year, we’re offering 5 million free tokens on your first API usage, so you can test, benchmark, and ship without friction.
This launch brings the model, benchmarks, api access, and infrastructure together in one place, and we’d love feedback from builders, researchers, and infra teams. Questions, critiques, and comparisons are all welcome as we shape v2.