QuickSilver Pro vs Azure OpenAI Service
Azure OpenAI Service runs the closed OpenAI catalog (GPT-4o, o1, o3-mini) on Microsoft infrastructure with Azure-native compliance, Private Link, and Entra ID auth. For workloads where an open-source model is quality-equivalent, QuickSilver Pro serves the DeepSeek V4 wave (V4 Flash + Pro) at 6x–30x lower output cost and exposes them through the same OpenAI SDK — no resource group provisioning, no AAD setup, no Cognitive Services quota requests.
At a glance
| Feature | QuickSilver Pro | azure-openai |
|---|---|---|
| Model catalog | Open-source LLMs (DeepSeek V4 Flash + Pro, Qwen 3.7 Max + 3.6 Plus + 3.6, Kimi K2.6) | GPT-4o, o1, o3-mini, GPT-4o-mini (closed) |
| Model weights | Open (MIT / Apache) | Closed |
| Low-cost chat output (GPT-4o-mini / V4 Flash) | $0.224 / 1M | $0.60 / 1M |
| Premium reasoning output (o3-mini / V4 Pro) | $0.87 / 1M | $4.40 / 1M |
| API setup | Sign up, paste key | Provision resource, request quota, AAD |
| Private Link / Entra ID / Sentinel | No | Yes |
Pricing (per million tokens, USD)
Competitor list prices as published by each provider.
| Model | QSP input | QSP output | azure-openai input | azure-openai output | vs. list |
|---|---|---|---|---|---|
| deepseek-v4-flash vs gpt-4o-mini | $0.112 | $0.224 | $0.14 | $0.60 | ~63% |
| deepseek-v4-pro vs o3-mini | $0.435 | $0.87 | $1.10 | $4.40 | ~84% |
| qwen3.6-35b vs gpt-4o | $0.112 | $0.80 | $2.50 | $10.00 | ~92% |
Migration - two lines
import os
from openai import OpenAI
# Was: AzureOpenAI(azure_endpoint=..., api_version=..., api_key=...)
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key=os.environ["QSP_KEY"],
)
r = client.chat.completions.create(
model="deepseek-v4-pro", # or deepseek-v4-flash, qwen3.6-35b, ...
messages=[{"role": "user", "content": "Hi"}],
)FAQ
Yes — the OpenAI SDK is the same shape Azure exposes. Change `azure_endpoint` to a plain `base_url=https://api.quicksilverpro.io/v1`, drop the deployment-name indirection (use the model ID directly: deepseek-v4-flash, deepseek-v4-pro, etc.), and supply your QSP key. Streaming, tool calling, JSON schema strict mode, and usage accounting all work.
When AAD auth, Private Link, Sentinel logging, or Microsoft Compliance Manager mappings are non-negotiable. Also when you need closed-model capabilities (real-time audio, DALL-E, the Assistants API) or when GPT-4 measurably beats DeepSeek V4 on your evals. QuickSilver Pro is for the chat / coding / RAG slice where open-source matches.
On the direct quality maps: GPT-4o-mini→V4 Flash is ~63% lower on output. o3-mini→V4 Pro is ~6× lower on output. Real-world bills typically land at 10–20% of Azure OpenAI for traffic that re-routes cleanly to open-source.
QuickSilver Pro infrastructure is hosted on dedicated bare-metal in Europe (OVH) with US edge. Region pinning is available on teams plans for data-residency requirements. For full Azure-region-locked inference with sovereign-cloud controls, Azure OpenAI is the right tool.