Last refreshed 2026-11-05. Next refresh: weekly.
Why use Fireworks DBRX-Instruct on Fireworks AI?
Fireworks AI offers Fireworks DBRX-Instruct. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Input / 1M
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Output / 1M
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Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install openaiAuth
export FIREWORKS_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],Model ID
accounts/fireworks/models/dbrx-instructRequest example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/dbrx-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/dbrx-instruct", not the LLMReference slug "fireworks-dbrx-instruct".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Capabilities
No model capability flags are currently sourced.
About Fireworks DBRX-Instruct
Fireworks DBRX-Instruct is Databricks Mosaic's DBRX model. It offers a 32K-token context window.
Get Started
Model Specs
Released2024-03-12
Parameters132B
Context32K
ArchitectureDecoder Only
Knowledge cutoff2023-12