QuickSilver Pro vs Fireworks AI
Fireworks AI runs its own GPU fleet and sets premium prices for DeepSeek — $3.00 / $8.00 per 1M tokens on R1. QuickSilver Pro serves the same model at $0.56 / $2.00. On DeepSeek V3 we're ~32% cheaper on output; on R1, ~75% cheaper on output. Same OpenAI-compatible surface, two-line migration.
At a glance
| Feature | QuickSilver Pro | fireworks |
|---|---|---|
| Catalog focus | 9 open-source models | Many open models + vision + fine-tuning |
| DeepSeek R1 output price | $2.00 / 1M | $8.00 / 1M |
| DeepSeek V3 output price | $0.616 / 1M | $0.90 / 1M |
| Fine-tuning / deployments | No | Yes |
| FireFunction V2 (tool calling model) | No | Yes |
| Image / audio models | No | Yes |
| OpenAI-compatible chat | Yes | Yes |
| Minimum top-up | $5 | Varies |
Pricing (per million tokens, USD)
Public list prices as of May 2026.
| Model | QSP input | QSP output | fireworks input | fireworks output | Savings |
|---|---|---|---|---|---|
| DeepSeek V3 | $0.16 | $0.616 | $0.30 | $0.90 | ~32% |
| DeepSeek R1 | $0.56 | $2.00 | $3.00 | $8.00 | ~75% |
| Qwen3.5-35B-A3B | $0.111 | $0.80 | Comparable | Comparable | — |
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
~81% on input, ~75% on output. Fireworks charges $3.00/$8.00 per 1M tokens for R1; QuickSilver Pro charges $0.56/$2.00.
Two lines: change base_url to api.quicksilverpro.io/v1, swap API key, drop the accounts/fireworks/models/ prefix from model IDs.
Within 10% on p50 for V3 and Qwen; slightly higher on R1. Live per-model latency is at quicksilverpro.io/status.
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.