Using Drex v1.5 on DeepInfra

Implementation guide · Drex · Nace.AI

Serverless
Open Weights

DeepInfra exposes Drex v1.5 through model ID nace-ai/drex-v1.5. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-10-22. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at DeepInfra and generate an API key.
  2. 2
    Use the DeepInfra SDK or REST API to call nace-ai/drex-v1.5 — see the documentation for request format.
  3. 3
    You'll be billed $0.04/1M input, Free/1M output tokens. See full pricing.
API PortalDocumentationPricingModel Card

Code Examples

Install
pip install openai
API key
DEEPINFRA_API_KEY
Model ID
nace-ai/drex-v1.5

DeepInfra uses "organization/model-name" format, e.g. "meta-llama/Meta-Llama-3-8B-Instruct" or "mistralai/Mistral-7B-Instruct-v0.3". See the DeepInfra model catalog for exact IDs.

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["DEEPINFRA_API_KEY"],
    base_url="https://api.deepinfra.com/v1/openai"
)
response = client.chat.completions.create(
    model="nace-ai/drex-v1.5",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on DeepInfra

TypePrice (per 1M)
Input tokens$0.04
Output tokensFree

Capabilities

No model capability flags are currently sourced.

About Drex v1.5

Drex v1.5 is Nace.AI's ~9B open-weight decision model (MiMo-V2.6-Distill-Qwen-9B backbone): it returns a probability for each option of typed questions in one forward pass; #1 under 10B on the public Decision Index 0.3.1. Nace.AI Open RAIL-M license.

Full model details →

Model Specs

Released2026-09-28
Parameters9B
Context128K

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Provider

DeepInfra

San Francisco, California, United States