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Ollaya launches as local runtime for open-source decision models, mimics TypeSafe API

read original get NVIDIA GeForce RTX 4090 GPU → more articles
GoKawiil Brief

Ollaya is a new local server for running open-source 'decision models' like Laya, gliclass and NLI, designed to answer structured questions in a single forward pass rather than generating text token by token. It implements the same /v1/systemone and /v1/models endpoints as TypeSafe's hosted API, so the official TypeSafe Python SDK can point at a local Ollaya server without code changes.

Why It Matters

GoKawiil's interpretation of the reporting above, not reported fact.

By reproducing TypeSafe's request and response shapes, Ollaya could let developers switch from a hosted decision-model API to local, self-hosted inference with minimal code changes, keeping sensitive data like tickets and user messages on their own infrastructure. The published benchmarks, comparing an RTX 4090 setup against third-party measurements of TypeSafe's hosted API, suggest large latency gains, though the project itself cautions that the two setups differ enough that the comparison is only order-of-magnitude.

Key Takeaways
Worth a Look

NVIDIA GeForce RTX 4090 GPU — This benchmark's impressive 8-10ms inference times were measured on an RTX 4090, making it a great reference point for anyone wanting to run local decision models like Laya at similar speeds. Its large VRAM and compute power make it well suited for hosting fp16/fp32 inference workloads locally instead of relying on hosted APIs.

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Source: ollaya.dev, 2026-09-25

Published there as: “Ollaya – Ollama for open-source, Jev-style decision models”

Read the original report → The summary and analysis above are GoKawiil's own, written from reporting by the source above. Facts and quotes belong to the original publisher.