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Migration guide · 5 minutes

Fireworks AI → QuickSilver Pro

Both APIs are OpenAI-compatible, so the move is a base-URL swap. On DeepSeek R1 that swap is worth ~75% on output ($2.00 vs $8.00 per 1M tokens); on V3, ~32%. For the full side-by-side analysis, see /vs/fireworks.

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

    Change the base URL

    In your OpenAI SDK init, swap the base_url.

    - base_url="https://api.fireworks.ai/inference/v1"
    + base_url="https://api.quicksilverpro.io/v1"
  3. 3

    Swap the API key

    Replace your Fireworks key with a QuickSilver Pro key.

    - api_key=os.environ["FIREWORKS_API_KEY"],
    + api_key=os.environ["QSP_KEY"],
  4. 4

    Rename model IDs

    Fireworks uses fully-qualified account paths for model IDs. Drop the accounts/fireworks/models/ prefix.

    Fireworks AIQuickSilver Pro
    accounts/fireworks/models/deepseek-v3deepseek-v3
    accounts/fireworks/models/deepseek-r1deepseek-r1
  5. 5

    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 · Fireworks AI
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.fireworks.ai/inference/v1",
    api_key=os.environ["FIREWORKS_API_KEY"],
)

r = client.chat.completions.create(
    model="accounts/fireworks/models/deepseek-r1",
    messages=[{"role": "user", "content": "Hi"}],
)
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"}],
)

What you'll pay after switching

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

ModelQuickSilver ProFireworks AISavings
DeepSeek V3$0.16 / $0.616$0.30 / $0.90~32%
DeepSeek R1$0.56 / $2.00$3.00 / $8.00~75%

Common migration pitfalls

FireFunction V2 has no equivalent
FireFunction V2 is Fireworks' proprietary fine-tuned tool-calling model and is not in the QuickSilver Pro catalog. For tool calling, deepseek-v3 and qwen3.5-35b both support the standard OpenAI tools / function calling API.
Dedicated deployments and fine-tunes don't move
QuickSilver Pro serves shared models only. Keep Fireworks dedicated deployments and fine-tuned models on Fireworks; the two SDKs coexist fine in one codebase.
Model revision may differ
Fireworks pins its own DeepSeek revisions. QuickSilver Pro routes deepseek-r1 / deepseek-v3 to its own pinned revisions — re-run evals if your prompts are sensitive to output style.
Rate limits work differently
QuickSilver Pro applies per-key throughput caps (default 600 req/min, 1M tok/min, 8 parallel). For bursty traffic, enable retry-on-429 and request a higher limit if needed.

Migrating from Fireworks AI — FAQ

How much cheaper on DeepSeek R1?
~81% on input, ~75% on output. Fireworks charges $3.00/$8.00 per 1M tokens for R1; QuickSilver Pro charges $0.56/$2.00.
How do I migrate?
Two lines: change base_url to api.quicksilverpro.io/v1, swap API key, drop the accounts/fireworks/models/ prefix from model IDs.
Is latency comparable?
Within 10% on p50 for V3 and Qwen; slightly higher on R1. Live per-model latency is at quicksilverpro.io/status.
Do you support FireFunction V2?
No. FireFunction V2 is Fireworks' proprietary fine-tuned model; it is not in the QuickSilver Pro catalog. For tool calling, DeepSeek V3 and Qwen3.5-35B-A3B both support the OpenAI tools / function calling API.

Other migration guides

Need help?

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

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