QuickSilver Pro vs OpenRouter
For DeepSeek V3, DeepSeek R1, and Qwen3.5-35B-A3B, QuickSilver Pro lists the same models at 20% below OpenRouter's public per-token rates — same OpenAI-compatible API, two-line migration. For closed models (GPT-4, Claude) or the long tail, OpenRouter is still the right tool.
At a glance
| Feature | QuickSilver Pro | OpenRouter |
|---|---|---|
| Models in catalog | 3 (DeepSeek V3, R1, Qwen3.5-35B-A3B) | 300+ |
| Pricing on shared models | 20% below OpenRouter | Baseline |
| OpenAI-compatible surface | Yes | Yes |
| Streaming · tools · json_schema | Yes | Yes |
usage.cost on responses | Yes (synthetic) | Yes |
| Per-key monthly spend limits | Yes | Yes |
| Closed models (GPT-4, Claude) | No | Yes |
| Free tier | $1 on signup | Limited free models |
| Minimum top-up | $5 | $10 |
Pricing (per million tokens, USD)
Public list prices as of April 2026. OpenRouter rates reflect their default (non-promotional) tier on the same underlying open-source weights.
| Model | QSP input | QSP output | OR input | OR output | Savings |
|---|---|---|---|---|---|
| DeepSeek V3 | $0.24 | $0.70 | $0.30 | $0.88 | ~20% |
| DeepSeek R1 | $0.40 | $1.70 | $0.50 | $2.15 | ~20% |
| Qwen3.5-35B-A3B | $0.13 | $1.00 | Compare at OpenRouter | — | |
A typical DeepSeek V3 workload — 1M input + 300k output tokens per day — costs $0.45/day on QuickSilver Pro vs $0.56/day on OpenRouter. Over a month, that's $3.30 saved on $16.80 of spend. Bigger workloads scale linearly.
Migration — two lines
If your code already uses the official OpenAI SDK pointed at OpenRouter, migration is a base URL swap and an API key swap. Model IDs drop the provider/ prefix.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=os.environ["OPENROUTER_KEY"],
)
r = client.chat.completions.create(
model="deepseek/deepseek-chat",
messages=[{"role": "user", "content": "Hi"}],
)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-v3",
messages=[{"role": "user", "content": "Hi"}],
)deepseek/deepseek-chat → deepseek-v3deepseek/deepseek-r1 → deepseek-r1qwen/qwen3.5-35b-a3b → qwen3.5-35bHonest tradeoffs
- ›You use only DeepSeek V3, DeepSeek R1, or Qwen3.5-35B-A3B and want the lowest per-token price.
- ›You want pay-as-you-go with a $5 minimum top-up and no subscription.
- ›You prefer per-request cost accounting via
usage.costwithout hitting a separate billing endpoint.
- ›You need closed models — GPT-4, Claude, Gemini — or the long tail of community models.
- ›You rely on OpenRouter's per-model routing across multiple independent upstream providers.
- ›Your agent framework is pre-configured for the
provider/modelID format. - ›You actively evaluate more than the three models we carry — OpenRouter's 150+ model catalog is the right tool for bake-offs.
- ›You use bring-your-own-key routing to bill through an existing Anthropic, Google, or Azure contract while keeping one API surface.
- ›You top up in crypto — OpenRouter accepts prepaid BYO crypto balances; we take card + wire only.
We're not trying to replace OpenRouter across the board — their 300+ model catalog is a different tool. For teams whose DeepSeek or Qwen spend dominates the bill, though, 20% at the per-token level compounds.
FAQ
Is QuickSilver Pro cheaper than OpenRouter?
Yes, on the shared open-source models: 20% below OpenRouter's public per-token rates for DeepSeek V3, R1, and Qwen3.5-35B-A3B. See the pricing table above for exact numbers.
How do I migrate from OpenRouter?
Two lines in your OpenAI SDK setup: change base_url from openrouter.ai/api/v1 to api.quicksilverpro.io/v1, swap the API key. Drop the provider/ prefix from model IDs.
When should I stay on OpenRouter?
If your workload needs closed models (GPT-4, Claude, Gemini), Llama, Mistral, or the long tail. QuickSilver Pro only serves three open-source models; OpenRouter serves 300+.
Same OpenAI features (streaming, tools, JSON schema)?
Yes for the shared models. Streaming, tool / function calling, json_schema strict mode, and standard usage accounting all work through the official OpenAI SDK. Each response also returns a synthetic usage.cost computed from the public per-token rate.
Monthly cost walkthrough
A concrete example — a small coding agent in steady use, running DeepSeek V3 for plan / diff / review loops. Typical monthly footprint: 30M input tokens (repo context, file reads, tool responses) and 5M output tokens (generated code, explanations).
30M × $0.24 = $7.20
5M × $0.70 = $3.50
————————————————
Total = $10.70/mo
30M × $0.30 = $9.00 5M × $0.88 = $4.40 ———————————————— Total = $13.40/mo
That's $2.70 saved each month, ~20% off. A single developer agent won't move the needle, but a 10-engineer team running parallel agents on the same per-seat profile sees the gap become ~$324/year — without changing a line of application code.
Uptime & reliability
QuickSilver Pro is in a bridge phase: requests are routed across multiple upstream inference providers serving the same open-source weights. If one upstream has an outage or hits capacity, the router falls back to the next. This gives us provider-diversity redundancy today while we stand up our own GPU capacity (target: Q2 2026, tracked on the public status page). Per-model availability, p50 / p95 latency, and incident history are all published there.
OpenRouter publishes a real-time provider health dashboard at status.openrouter.ai, which shows per-upstream latency and error rates across the providers it routes to. They don't advertise a contractual SLA on the free / default tier; for uptime guarantees with penalties, their enterprise plan is the documented option. Both of us rely on the same underlying upstream network — the differentiator is pricing, not fundamentally different infrastructure at this phase.
Also worth checking
Try it on $1 free credits
Create an account, point your OpenAI SDK at api.quicksilverpro.io/v1, ship.