Dolly
Databricks' open-source instruction-following model — trained on human-generated data, commercial use permitted.
Overview
Dolly 2.0 is Databricks' April 2023 instruction-tuned Pythia-12B model, billed as the first open-source instruction LLM cleared for commercial use because all 15,000 training examples were written by Databricks employees. The databricks-dolly-15k dataset has outlived the model itself.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 11 Jul 2026 and may be out of date or incomplete.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
Dolly 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).
Dolly v2 was a landmark in 2023 — one of the first instruction-tuned LLMs released under a fully open, commercially usable licence, trained on a human-generated dataset (databricks-dolly-15k). It mattered as proof that open, non-restrictive instruction models were possible, and it remains a reasonable teaching artifact for understanding fine-tuning. As a tool to actually deploy in 2026 it is obsolete: a 12B model from early 2023 is far behind Llama 3.x, Qwen, Mistral and other modern open weights on every benchmark and on efficiency. There is no hosted product, no API and no ongoing development — it lives on Hugging Face as weights you self-host. Treat it as historically significant, not as a current option.
What people say
Nobody deploys Dolly in 2026, and even Databricks never claimed you should — the launch blog conceded the model wasn't state-of-the-art, and early users found it hallucinated freely and trailed GPT-3.5 by a wide margin. What earns Dolly its place in the record books is a licensing manoeuvre, not a benchmark.
In early 2023, every open instruction model worth using (Alpaca, Vicuna and friends) was tuned on GPT output, which OpenAI's terms made legally murky for commercial products. Databricks' answer was to turn dataset creation into an internal contest: over 5,000 employees wrote 15,000 instruction–response pairs across eight task categories. Fine-tune EleutherAI's Pythia-12B on that, release everything under CC-BY-SA, and you get Dolly 2.0 — shipped in April 2023 as the first instruction-tuned LLM anyone could legally build a business on.
The dataset outlived the model by a wide margin. databricks-dolly-15k is still cited, still downloaded, and still shows up in fine-tuning tutorials and as seed data for other corpora; the model itself sits dormant on Hugging Face, and the GitHub repo has been essentially untouched since mid-2023. Databricks moved on to MPT via the MosaicML acquisition, then to DBRX.
The 3.5 score is about right — arguably generous for the model, fair for the contribution. If you need a clean, human-written instruction dataset for a class project or a reproduction study, dolly-15k remains genuinely useful. If you want a model that answers questions well, any modern open-weight release does better.
Summary of public user & expert reviews, compiled by RECATOOLS.
Notable facts
- Dolly 2.0 was the first open-source LLM where ALL training data was generated by human employees — allowing commercial use with complete legal clarity.
- The 15,000 training examples were written by Databricks staff in their spare time across 3 weeks, making it one of the most unusual crowdsourced datasets in AI history.
- Dolly was named after Dolly the sheep, the first cloned mammal — symbolising the replication of ChatGPT's instruction-following behaviour at low cost.
Frequently asked questions
About this listing
This entry was compiled from publicly available data including Dolly's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Dolly 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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