Tülu by AllenAI
Open instruction-tuned LLM family
Overview
Tülu is AllenAI's instruction-tuned and RLHF-trained LLM family built on OLMo and Llama base models. Tülu 3 was a key 2024 release demonstrating open methods could match closed-source post-training quality.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 20 May 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
Use cases
ASEAN Perspective
Tülu by AllenAI in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Tülu is the Allen Institute for AI's family of openly released, post-trained language models, notable not just for the weights but for fully published training data, recipes (SFT, DPO/RLVR) and evaluation, making it a reference point for open, reproducible alignment research. For the research community it is one of the most transparent model families available.
It suits researchers, academics and engineers who want open weights and a documented post-training pipeline to study or build on, not end users wanting a polished chat product. Caveats: it trails frontier proprietary models on raw capability, there is no managed hosted service or commercial SLA (you self-host or use third-party endpoints), and it is research-oriented. Permissive openness and global availability make it ASEAN-accessible for those with the infrastructure.
About this listing
This entry was compiled from publicly available data including Tülu by AllenAI's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Tülu by AllenAI unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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