Family DBRX · 132B parameters

DBRX Instruct

MoE with 132B/36B active parameters. 12T tokens. Databricks license (conditionally permissive). HF gated.

🇺🇸 Databricks·License Databricks Open Model License·Context 32k tokens·Output March 2024·Fits within the 128 GB of the GIGABYTE AI TOP ATOM← Catalog

01What it can do

Strengths
  • State-of-the-art quality in March 2024
  • Strong at coding and math
  • Databricks Open Model License
Limitations to know
  • —76 GB VRAM Q4 — multi-GPU required
  • —Far surpassed by DeepSeek V3/R1 in 2025
Architecture
MoE · 132B total / 36B active · 16 experts, 4 active per token
Training
Databricks — 12T high-quality tokens, strong at code and science.
Ideal for
Enterprise MoEPro chat

05Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$ollama run dbrx
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
76 GB
Q5_K_M
Good quality/size compromise
94 GB
Q8_0
Nearly indistinguishable from FP16
140 GB
FP16
Full precision — server use
264 GB
Fallback CPU · If you don't have a GPU, allow 112 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for DBRX Instruct?

To run DBRX Instruct locally with Q4 quantization, you need about 76 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.

Current offer: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395)
AmazonSee price →

Why this choice? Our complete guide on BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) →

Affiliate links — commission possible at no extra cost to you; independent recommendations. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

This model in your private ChatGPT, without the cloud

Too large for your machine? The kit gives you the model that fits in your VRAM

  • Lifetime online access
  • PDF + files
  • Lifetime updates

03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~2t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~8t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~22t/s
RTX 4090, M4 Max, Radeon 7900

04Public benchmarks

Scores reproduced from model cards or MMLU-Pro / community sources. Unit: % correct answers.

MMLU
73.7
HumanEval
70.1