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Migration guide · 10 minutes

AWS Bedrock → QuickSilver Pro

Unlike the reseller migrations, this one swaps SDKs: you drop the AWS SDK + SigV4 signing and use the plain OpenAI SDK with a Bearer key. The payoff is ~9% cheaper output on DeepSeek R1 (input is at parity), plus access to the V4 wave Bedrock doesn't carry. For the full side-by-side analysis, see /vs/bedrock.

The steps

  1. 1

    Get a QuickSilver Pro API key

    Sign up at quicksilverpro.io/dashboard. Launch bonus: top up between $5 and $50 and we match it 100% — pay $5, get $10; pay $50, get $100.

  2. 2

    Replace the AWS SDK with the OpenAI SDK

    Bedrock requires the AWS SDK (boto3 / aws-sdk) and SigV4 request signing. QuickSilver Pro serves the OpenAI chat-completions shape directly, so you drop that plumbing entirely and use the official openai client with a Bearer API key.

    Bedrock's Converse API maps cleanly to OpenAI chat completions — streaming, tool calling, and structured output behavior carry over. See the full before/after below.

  3. 3

    Rename model IDs

    Bedrock uses region-qualified inference-profile IDs. QuickSilver Pro uses short model names. Bedrock does not carry the DeepSeek V4 wave, Qwen 3.6, or Kimi K2.6 — those become newly available on QuickSilver Pro.

    AWS BedrockQuickSilver Pro
    us.deepseek.r1-v1:0deepseek-r1
    (not on Bedrock)deepseek-v3
    (not on Bedrock)deepseek-v4-pro
  4. 4

    Test your core flows end-to-end

    Run one representative request for each feature you use — chat, streaming, tool / function calling, and json_schema strict mode. Any behavioral difference is a bug — report it.

Full before/after

Before · AWS Bedrock (boto3)
import boto3, json

client = boto3.client("bedrock-runtime", region_name="us-east-1")

resp = client.converse(
    modelId="us.deepseek.r1-v1:0",
    messages=[{"role": "user", "content": [{"text": "Hi"}]}],
)
text = resp["output"]["message"]["content"][0]["text"]
After · QuickSilver Pro
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-r1",
    messages=[{"role": "user", "content": "Hi"}],
)
text = r.choices[0].message.content

What you'll pay after switching

Per 1M tokens, input / output. QuickSilver Pro rates vs AWS Bedrock's published per-token pricing.

ModelQuickSilver ProAWS BedrockSavings
DeepSeek R1$0.56 / $2.00$0.55 / $2.19~9% output

Common migration pitfalls

You lose AWS-native plumbing
IAM-scoped access, VPC endpoints, Bedrock Guardrails, and Knowledge Bases have no QuickSilver Pro equivalent. If any of these are load-bearing for your compliance story, keep that traffic on Bedrock — or move only the cost-sensitive subset.
Auth model changes from SigV4 to Bearer
Bedrock signs every request with SigV4 derived from AWS credentials. QuickSilver Pro uses a static Bearer API key. Update your secrets management accordingly and treat the key like any other credential.
Not every Bedrock model exists on QuickSilver Pro
Claude, Nova, Llama, and Mistral are not in the QuickSilver Pro catalog. Only DeepSeek R1 maps directly today. Keep multi-model Bedrock workloads on Bedrock for the closed models.
Region pinning differs
Bedrock inference is region-locked to your AWS region. QuickSilver Pro runs on dedicated bare-metal in Europe with US edge. If data residency is a contractual requirement, evaluate this before moving.

Migrating from AWS Bedrock — FAQ

How much cheaper than Bedrock?
On DeepSeek R1: input is roughly at parity ($0.56 on QSP vs $0.55 on Bedrock — QSP is marginally higher) while output is ~9% cheaper ($2.00 on QSP vs $2.19 on Bedrock). On the V4 wave (V4 Flash + Pro), Qwen 3.6, and Kimi K2.6 the comparison is irrelevant because Bedrock doesn't carry those weights yet — QSP is the only managed provider for the latest DeepSeek and Qwen releases.
When should I stay on Bedrock?
If IAM / VPC endpoints / Guardrails / Knowledge Bases / BYO-VPC are load-bearing for your compliance story, or if you need Claude / Nova / closed models in the same provider. The Bedrock premium pays for AWS-native integration; QuickSilver Pro is for teams who don't need that and would rather not pay the markup.
How do I migrate?
Drop the AWS SDK / SigV4 plumbing and use the openai SDK directly: base_url="https://api.quicksilverpro.io/v1", api_key="$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.
Does QSP have Guardrails or Knowledge Bases?
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 3.5/3.6 let you skip the vector store entirely on small-to-mid corpora.

Other migration guides

Need help?

Email hello@quicksilverpro.io — a human replies usually within 4 hours. For the broader analysis, see QuickSilver Pro vs AWS Bedrock.

Start saving in 10 minutes

Launch bonus: first deposit matched 100%, up to $50 free. Swap the AWS SDK and SigV4 signing for the OpenAI SDK — then it's a base URL and a Bearer key.

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