Model release

DBRX Instruct

DBRX Instruct is a model release from Databricks1, version Instruct, released Mar 27, 2024. Its weights are not public1 6 5.

DBRX Instruct is the finetuned version of DBRX Base, a mixture-of-experts language model with 132B total and 36B active parameters (16 experts, 4 active per input) pretrained on 12T tokens of text and code with a 32K-token context.1 5

Release notes: Announcement: Introducing DBRX (external site: databricks.com)
License: Databricks Open Model License (external site: databricks.com)
License: Databricks Open Model Acceptable Use Policy (external site: databricks.com)
Documentation: DBRX in Hugging Face Transformers (external site: huggingface.co)

Last reviewedSep 29, 2026Entry updated Sep 29, 2026Documented release Mar 27, 2024

Availability and license

Overall availability

Not public

Weights were published on Hugging Face at release in March 2024. As of this review Databricks' Hugging Face organization lists no public models, Hugging Face's Transformers documentation states the original DBRX Instruct checkpoint was closed, and Databricks retired DBRX from its hosted Foundation Model APIs and fine-tuning service during 2025.1 6 5 7 8

Availability fact review: not separately recorded

Availability is separate from permission: read the license before using or redistributing.

Databricks Open Model License (external site: databricks.com)3
Applies to: Weights and code · custom license (no SPDX identifier) · fact-level rights review not recorded

Custom license dated March 27, 2024 covering the DBRX models, weights, and code identified at the databricks/dbrx GitHub repository. It grants a royalty-free limited license to use, modify, and distribute DBRX, but prohibits using DBRX, its derivatives, or its outputs to improve other large language models; requires a separate license from Databricks for licensees whose products had more than 700 million monthly active users on the release date; and requires compliance with the Databricks Open Model Acceptable Use Policy.3 4

Component reuse rights

A readable or downloadable component is not automatically reusable. These indicators concern recorded license evidence, not system certification.

weights: Unknown — no complete fact-level rights review
code: Unknown — no complete fact-level rights review
data: Unknown — no complete fact-level rights review
documentation: Unknown — no complete fact-level rights review

No complete system-rights review is recorded for this release.

Model-disclosure tier

Computed from the checklist below using USASI rubric v0.2. An editorial category, not a certification.

Weights not public

The weights for this release are documented as not publicly available.

How tiers are computed

Public materials checklist

Items for a model under USASI rubric v0.2. Unknown means unassessed or insufficient evidence.

Public materials checklist for DBRX Instruct
Item	Status	Notes and evidence
WeightsCan the general public download the model parameters for this release?	Not public	Published on Hugging Face at release (March 2024). Hugging Face's Transformers documentation states the original databricks/dbrx-instruct checkpoint was closed, and Databricks' Hugging Face organization lists no public models.1 6 5
Inference codeIs code for running the model published?	Public	Hugging Face Transformers includes a DBRX model implementation (DbrxForCausalLM). The databricks/dbrx GitHub repository referenced at release returned HTTP 404 when checked on 2026-09-29.5
Training codeIs the code used to train the model published?	Unknown	The announcement says DBRX was trained with optimized versions of Databricks' open-source libraries MegaBlocks, LLM Foundry, Composer, and Streaming; the exact training code used for DBRX was not located.1
Training-data informationDoes the information cover provenance, scope, acquisition, selection, labeling, processing, and where data or alternatives can be obtained? Access alone does not establish completeness.	Unknown	Not assessed.
Training-data accessCan the training data be obtained? This is independent of information completeness and reuse rights; original unshareable data need not be downloadable.	Unknown	Not assessed.
Complete training pipelineIs the complete base-training and preprocessing pipeline published, including configuration? Fine-tuning code or an inference SDK alone is insufficient.	Unknown	Not assessed.
Legacy data assessment (v0.1)Historical assessment combining download access and disclosure. Preserved for traceability; excluded from the v0.2 tier calculation. See the new separate assessments above.	Unknown	The announcement gives only a high-level description (12T tokens of curated text and code, processed with Databricks tools) and does not list data sources.1
Training recipeAre the training configuration and procedure documented in enough detail to follow?	Partial	The announcement describes the architecture, curriculum learning over the data mix, and the training cluster (3,072 NVIDIA H100 GPUs) at a high level, without a full training configuration.1
Evaluation materialsPublic = evaluation code or prompts that let others re-run the evaluations are published. Partial = results only.	Partial	Benchmark results were published in the announcement; evaluation code specific to this release was not assessed.1

Organization context

Databricks

Provenance and derivatives

Databricks' release announcement presents DBRX Instruct as the finetuned counterpart of its DBRX Base model; the finetuning data is not described.1

Derived from: DBRX Base — Databricks base model

What this catalog does not know

Unknown means the sources reviewed for this record do not document it. It is not evidence that something does not exist.

Training code: unknown.
Training-data information: unknown.
Training-data access: unknown.
Complete training pipeline: unknown.
Legacy data assessment (v0.1): unknown.

Have a primary source? How to report a correction.

U.S. eligibility

Project eligibility rests on documented governing or maintaining entities, not on contributors.

Eligible · basis: U.S. headquarters

DBRX Instruct was developed and released by Databricks, which states on its About page that it is headquartered in San Francisco, California.1 2

Assessed Sep 29, 2026

Sources

1.
Introducing DBRX: A New State-of-the-Art Open LLM (external site: databricks.com)
Databricks · Announcement · published Mar 27, 2024 · accessed Sep 29, 2026
2.
About Databricks: The data and AI company (external site: databricks.com)
Databricks · Official page · accessed Sep 29, 2026
3.
Databricks Open Model License (external site: databricks.com)
Databricks · License · published Mar 27, 2024 · accessed Sep 29, 2026
4.
Databricks Open Model Acceptable Use Policy (external site: databricks.com)
Databricks · License · published Mar 27, 2024 · accessed Sep 29, 2026
5.
DBRX (Hugging Face Transformers documentation) (external site: huggingface.co)
Hugging Face · Documentation · accessed Sep 29, 2026
6.
Databricks organization on Hugging Face (external site: huggingface.co)
Hugging Face · Other · accessed Sep 29, 2026
7.
AI models maintenance policy | Databricks on AWS (external site: docs.databricks.com)
Databricks · Documentation · accessed Sep 29, 2026
8.
April 2025 | Databricks on AWS (external site: docs.databricks.com)
Databricks · Release notes · published Apr 2025 · accessed Sep 29, 2026

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This listing is not an endorsement, a safety assessment, or a federal approval.

Cite this page

APA style

USASI. (2026, September 29). DBRX Instruct. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/dbrx-instruct/

BibTeX

@misc{usasi_dbrx_instruct,
  author = {{USASI}},
  title = {DBRX Instruct},
  year = {2026},
  month = sep,
  howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/dbrx-instruct/}},
  note = {United States of America Superintelligence. Last updated 2026-09-29}
}

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