OPT
Meta's open-source language model with fully released training code and logbook — complete transparency.
Overview
OPT (Open Pre-trained Transformer) is a suite of decoder-only language models released by Meta AI Research in May 2022, ranging from 125M to 175B parameters. OPT was significant as one of the first near-GPT-3-scale models released publicly, enabling research that had previously been impossible without access to proprietary commercial models.
Uniquely, Meta released not just the model weights but the complete training codebase and a detailed training logbook documenting every decision, setback, and modification made during the training process. This level of transparency was unprecedented for a large model and provided the research community with valuable insights into the practical challenges of training very large language models.
OPT-175B matched GPT-3 on many benchmarks while being fully open for research use. The model enabled research into large model behaviour, few-shot learning, and factual knowledge that required full access to model internals. While OPT has been substantially surpassed by more recent models like Llama 3, it remains historically significant as a transparent large model research artefact.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 8 May 2026 and may be out of date or incomplete.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
OPT 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).
OPT (Open Pre-trained Transformer) was Meta's 2022 effort to give researchers access to a GPT-3-scale model, releasing weights up to 175B along with training logs — an important transparency milestone at the time. It is historically significant for opening up large-model research.
For practical use in 2026 it is obsolete: the original OPT carried a research-only, non-commercial license, its quality is far behind modern Llama, Qwen, Mistral and even small current open models, and it is largely superseded by Meta's own later releases. It suits historians of the field and reproducibility studies, not production. It is a model on Hugging Face, not a service, so there is no first-party API. Free for research; we score it low on current capability and value accordingly.
Notable facts
- OPT-175B was the first near-GPT-3-scale model released publicly with full training transparency including a day-by-day training logbook.
- The training logbook candidly described hardware failures, training instabilities, and engineering workarounds — a valuable resource for any team attempting to train large models.
- OPT was trained on 992 A100 80GB GPUs for approximately 33 days, with the full training run costing an estimated $2 million in compute.
Frequently asked questions
About this listing
This entry was compiled from publicly available data including OPT's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with OPT 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.
For the latest details, please refer to OPT directly →
Spotted something out of date? Suggest an update →
Alternatives to OPT
More in LLMs & Chat
