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 lists the same DeepSeek and Qwen weights at competitive per-token rates and exposes them through the OpenAI-compatible API your stack already speaks. On DeepSeek R1, input is roughly at parity (QSP $0.56 vs Bedrock $0.55) while output is ~9% cheaper; ~3x cheaper on Llama 70B-class output.
At a glance
| Feature | QuickSilver Pro | bedrock |
|---|---|---|
| Open-source LLM catalog | 9 (DeepSeek V4 Flash + Pro, V3, R1, Qwen 3.7 Max + 3.6 Plus + 3.6 + 3.5, Kimi K2.6) | DeepSeek R1, Llama 3.x, Mistral, Nova, Anthropic Claude |
| DeepSeek R1 output price | $2.00 / 1M | $2.19 / 1M |
| API surface | OpenAI-compatible (drop-in) | Bedrock Runtime (AWS SDK) or Converse API |
| AWS IAM / VPC / Guardrails | No | Yes |
| Closed models (Claude, Nova) | No | Yes |
| Minimum top-up | $5 | AWS billing |
| Auth | API key (Bearer) | SigV4 signed requests |
Pricing (per million tokens, USD)
Public list prices as of May 2026.
| Model | QSP input | QSP output | bedrock input | bedrock output | Savings |
|---|---|---|---|---|---|
| DeepSeek R1 | $0.56 | $2.00 | $0.55 | $2.19 | ~9% output |
| Llama 70B-class (R1 alt.) | $0.56 | $2.00 | $0.72 | $0.72 | vs R1 |
| DeepSeek V3 | $0.16 | $0.616 | — | — | 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-r1",
messages=[{"role": "user", "content": "Hi"}],
)FAQ
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 $2.19 on Bedrock). On the V4 wave (V4 Flash + Pro), Qwen 3.6, and Kimi K2.6 the comparison is irrelevant because Bedrock doesn't carry those weights yet — QSP is the only managed provider for the latest DeepSeek and Qwen releases.
If IAM / VPC endpoints / Guardrails / Knowledge Bases / BYO-VPC are load-bearing for your compliance story, or if you need Claude / Nova / closed models in the same provider. The Bedrock premium pays for AWS-native integration; QuickSilver Pro is for teams who don't need that and would rather not pay the markup.
Drop the AWS SDK / SigV4 plumbing and use the openai SDK directly: base_url="https://api.quicksilverpro.io/v1", api_key="$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 3.5/3.6 let you skip the vector store entirely on small-to-mid corpora.