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LLMS • CURATED • UPDATED FEB 5, 2026

DBRX

Databricks' high-performance open-source LLM

DBRX is a mixture-of-experts transformer model developed by Databricks and Mosaic ML. Released on March 27, 2024, with 132 billion total parameters (36B active parameters per token). Available in base and instruction-tuned (dbrx-instruct) variants. Outperforms other open-source models in various benchmarks including language understanding, programming, and mathematics. Uses fine-grained mixture-of-experts (MoE) architecture with 16 experts and 4 active per token for efficient inference. Trained at approximately $10 million cost. Released under Databricks Open Model License (permissive for research and commercial use). Available through Databricks Foundation Models API, Hugging Face, and open-source model weights.

QUICK FACTS

Pricing Enterprise
Platforms api, local
API Yes
Open Source Yes
Modalities LLMs
Best For Best for Performance
Date Added 2026-02-05

WHY WE PICKED IT

Databricks' high-performance open-source LLM with strong benchmark results, efficient MoE architecture, and permissive licensing.

STRENGTHS

LIMITATIONS

GETTING STARTED

Visit Databricks' DBRX blog post for documentation. Download model weights from Hugging Face or GitHub. For API access, use Databricks Foundation Models API. Deploy locally using vLLM, TensorRT-LLM, or compatible frameworks. Follow Databricks' documentation for optimal deployment and fine-tuning. Free tier includes limited API access.

QUICK TIPS

1 Leverage MoE architecture for efficient inference
2 Use for high-performance code generation tasks
3 Take advantage of strong mathematical reasoning
4 Explore fine-tuning for domain-specific applications
5 Use Databricks platform for managed deployment

OFFICIAL LINKS

Website↗ Documentation↗ Hugging Face↗ GitHub↗ API↗

SIMILAR TOOLS

Claude Fable 5 NotebookLM Claude Opus 5 GPT-5.6 Sol Kimi K3

USE CASE EXAMPLES

High-Performance Code Generation

Use DBRX for advanced code generation, refactoring, and software development tasks.

STEPS:
  1. Access DBRX through API or local deployment
  2. Provide detailed code requirements
  3. Generate high-quality code solutions
  4. Review and test generated code

Mathematical Problem Solving

Leverage DBRX's strong mathematical reasoning for complex problem-solving tasks.

STEPS:
  1. Input mathematical problems or equations
  2. Use DBRX's reasoning capabilities
  3. Get step-by-step solutions
  4. Validate mathematical accuracy

PRICING

Enterprise

Enterprise pricing — contact DBRX for a custom quote and contract terms.

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FEATURED IN GUIDES

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Which LLMs Actually Deliver in 2026?

Comprehensive comparison of the best large language models in 2026 including ChatGPT, Claude, Gemini...

EXPLORE ALTERNATIVES

View DBRX Alternatives (2026) →

Compare DBRX with 5+ similar llms AI tools.

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FREQUENTLY ASKED QUESTIONS

Q

Is DBRX free?

A

DBRX is offered as an enterprise solution; contact the provider for pricing.

Q

Does DBRX have an API?

A

Yes, DBRX offers an API for programmatic integration.

Q

What is DBRX best for?

A

DBRX is best for Performance. DBRX is a mixture-of-experts transformer model developed by Databricks and Mosaic ML. Databricks' high-performance open-source LLM with strong benchmark results, efficient MoE architecture, and permissive licensing.

Q

What platforms does DBRX support?

A

DBRX supports api, local.

Q

Is DBRX open source?

A

Yes, DBRX is open source. You can access the source code on GitHub at https://github.com/databricks/dbrx.

Q

How do I get started with DBRX?

A

Visit Databricks' DBRX blog post for documentation. Download model weights from Hugging Face or GitHub. For API access, use Databricks Foundation Models API. Deploy locally using vLLM, TensorRT-LLM, or compatible frameworks. Follow Databricks' documentation for optimal deployment and fine-tuning. Fr...

Q

How do I use DBRX?

A

DBRX is a large language model for text generation, analysis, and conversation. Use the API for programmatic access. Enter prompts or questions to get responses. It excels at strong benchmark performance (outperforms llama 3 70b, mixtral).

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FEATURED ON CURATEDAI

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Featured on CuratedAI