DeepInfra exposes Drex v2.0 through model ID nace-ai/drex-v2.0. 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
- 2Use the DeepInfra SDK or REST API to call
nace-ai/drex-v2.0— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
DEEPINFRA_API_KEYModel ID
nace-ai/drex-v2.0DeepInfra 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-v2.0",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on DeepInfra
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.06 |
| Output tokens | Free |
Capabilities
No model capability flags are currently sourced.
About Drex v2.0
Drex v2.0 is Nace.AI's open-weight decision model on Qwen3.6-35B-A3B with a Kev pointer head: it answers typed questions about a state with a probability per option in one forward pass. Runs locally via Python, llama.cpp or Ollama; Nace.AI Open RAIL-M license.
Model Specs
Released2026-10-06
Parameters35B total, 3B active
Context128K
ArchitectureMixture of Experts