QuickSilver Pro vs AWS Bedrock
Bedrock is the right choice when AWS-native integration (IAM, Guardrails, Knowledge Bases, VPC endpoints, BYO-VPC inference) is load-bearing for compliance. For everyone else, QuickSilver Pro serves the latest DeepSeek and Qwen weights at competitive per-token rates through the OpenAI-compatible API your stack already speaks. DeepSeek V4 Pro ($0.70 / $2.10) is the closest replacement for Bedrock's DeepSeek reasoning, plus you get the whole V4 wave, Qwen 3.6, and Kimi K2.6 that Bedrock doesn't carry.
At a glance
| Feature | QuickSilver Pro | bedrock |
|---|---|---|
| Open-source LLM catalog | Kimi K3, GLM 5.2, MiniMax M3, DeepSeek V4 Flash + Pro, Qwen 3.7 Max, Kimi K2.6 | Earlier DeepSeek generations, Llama 3.x, Mistral, Nova, Anthropic Claude |
| DeepSeek V4 Pro | $0.70 / $2.10 | Not offered |
| API surface | OpenAI-compatible (drop-in) | Bedrock Runtime (AWS SDK) or Converse API |
| AWS IAM / VPC / Guardrails | No | Yes |
| Closed frontier models (Claude, Nova) | Claude yes — 20% below Bedrock's own rate | Yes |
| Minimum top-up | $5 | AWS billing |
| Auth | API key (Bearer) | SigV4 signed requests |
Pricing (per million tokens, USD)
Competitor list prices as published by each provider.
| Model | QSP input | QSP output | bedrock input | bedrock output | vs. list |
|---|---|---|---|---|---|
| DeepSeek V4 Pro | $0.70 | $2.10 | $0.55 | $2.19 | ~parity |
| DeepSeek V4 Flash | $0.112 | $0.224 | — | — | not on Bedrock |
Migration - two lines
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key=os.environ["QSP_KEY"],
)
r = client.chat.completions.create(
model="deepseek-v4-pro",
messages=[{"role": "user", "content": "Hi"}],
)FAQ
Mapping Bedrock's DeepSeek reasoning to DeepSeek V4 Pro, QuickSilver Pro is roughly at parity on output ($2.10 vs $2.19 per 1M); the edge is the managed OpenAI-compatible API plus the rest of the V4 wave. On the rest of the V4 wave (V4 Flash), Qwen 3.6, and Kimi K2.6 the comparison is moot because Bedrock doesn't carry those weights yet — QSP is the only managed provider for the latest DeepSeek and Qwen releases.
If IAM / VPC endpoints / Guardrails / Knowledge Bases / BYO-VPC are load-bearing for your compliance story, or if you need Claude / Nova / closed models in the same provider. The Bedrock premium pays for AWS-native integration; QuickSilver Pro is for teams who don't need that and would rather not pay the markup.
Drop the AWS SDK / SigV4 plumbing and use the openai SDK directly: base_url="https://api.quicksilverpro.io/v1", api_key="$QSP_KEY". Bedrock's Converse API is broadly equivalent in capability to OpenAI chat completions; QSP serves the OpenAI shape directly so any OpenAI SDK works unchanged.
Not natively. QSP is focused on raw chat-completions inference at a narrow surface and predictable price — not a wider LLM platform. For Guardrails-equivalent content moderation, drop in any open-source moderation library against the chat output. For RAG, our 1M-context V4 Pro and 262K-context Qwen 3.6 let you skip the vector store entirely on small-to-mid corpora.