QuickSilver Pro vs DeepInfra
DeepInfra is the budget-friendly option among DeepSeek resellers. QuickSilver Pro serves the latest DeepSeek V4 wave — V4 Flash at $0.112 / $0.224 for low-cost chat and V4 Pro at $0.435 / $0.87 for premium reasoning — with per-token cache pricing. Same OpenAI-compatible API, two-line migration.
At a glance
| Feature | QuickSilver Pro | deepinfra |
|---|---|---|
| Catalog focus | Curated frontier + open models; 23 accept image input | 60+ open models, vision, audio |
| Official V4 Flash 0731 | $0.112 / $0.224 | Different undated build |
| DeepSeek V4 Pro output | $0.87 / 1M | $2.60 / 1M |
| Cached input discount | Yes (V4 wave, Qwen, Kimi) | Yes |
| Embeddings / audio | No | Yes |
| Image generation | Gemini 3 Pro Image and FLUX.2 Pro | Yes |
| Dedicated deployments | No | Yes |
| OpenAI-compatible chat | Yes | Yes |
| Minimum top-up | $5 | $20 |
Pricing (per million tokens, USD)
Competitor list prices as published by each provider.
| Model | QSP input | QSP output | deepinfra input | deepinfra output | vs. list |
|---|---|---|---|---|---|
| DeepSeek V4 Flash 0731 | $0.112 | $0.224 | $0.09* | $0.18* | *different build |
| DeepSeek V4 Pro | $0.435 | $0.87 | $1.30 | $2.60 | ~73% |
| Qwen3.6-35B-A3B | $0.112 | $0.80 | Comparable | Comparable | — |
Migration - two lines
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-flash",
messages=[{"role": "user", "content": "Hi"}],
)FAQ
On the same V4 Pro model, QuickSilver Pro is $0.435 / $0.87 per 1M tokens versus DeepInfra's current $1.30/$2.60 rate, about 73% lower. DeepInfra's lower V4 Flash listing is an undated build, while QSP pins the official 0731 agent revision, so those rows are not a like-for-like price comparison.
Two lines: swap base_url to api.quicksilverpro.io/v1, use a new API key, and rename DeepInfra's current V4 model IDs to deepseek-v4-flash or deepseek-v4-pro.
Yes — cached-input tokens bill at a separate, lower cache-read rate on the DeepSeek V4 wave and the Qwen/Kimi models, so repeat prompts cost less than fresh input. Both providers discount cached input; benchmark effective per-request cost if cache-hit ratio is material for your workload.
Embeddings and audio transcription are not offered. Image generation is: Gemini 3 Pro Image and FLUX.2 Pro. And 23 of our 40 models accept image input.