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 DeepSeek V3 / R1 / V4 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 | 9 open-source LLMs (V4 Flash + Pro, V3, R1, Qwen 3.7 Max + 3.6 Plus + 3.6 + 3.5, Kimi K2.6) | GPT-4o, o1, o3-mini, GPT-4o-mini (closed) |
| Model weights | Open (MIT / Apache) | Closed |
| Cheap chat output (GPT-4o-mini / V4 Flash) | $0.16 / 1M | $0.60 / 1M |
| General chat output (GPT-4o / V3) | $0.616 / 1M | $10.00 / 1M |
| Top reasoning output (o1 / R1) | $2.00 / 1M | $60.00 / 1M |
| API setup | Sign up, paste key | Provision resource, request quota, AAD |
| Private Link / Entra ID / Sentinel | No | Yes |
Pricing (per million tokens, USD)
Public list prices as of May 2026.
| Model | QSP input | QSP output | azure-openai input | azure-openai output | Savings |
|---|---|---|---|---|---|
| deepseek-v4-flash vs gpt-4o-mini | $0.08 | $0.16 | $0.15 | $0.60 | ~73% |
| deepseek-v3 vs gpt-4o | $0.16 | $0.616 | $2.50 | $10.00 | ~94% |
| deepseek-v4-pro vs o3-mini | $0.348 | $0.696 | $1.10 | $4.40 | ~84% |
| deepseek-r1 vs o1 | $0.56 | $2.00 | $15.00 | $60.00 | ~97% |
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-v3", # or deepseek-v4-pro, deepseek-r1, ...
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-r1, 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 (vision, real-time audio, DALL-E, the Assistants API) or when GPT-4 measurably beats DeepSeek V3 on your evals. QuickSilver Pro is for the chat / coding / RAG slice where open-source matches.
On the four direct quality maps: GPT-4o-mini→V4 Flash is ~73% cheaper on output. GPT-4o→V3 is ~16x cheaper on output. o3-mini→V4 Pro is ~6x cheaper on output. o1→R1 is ~30x cheaper 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.