- 1M context
- Reasoning
- Responses API
DeepSeek V4 Flash on QuickSilver Pro
DeepSeek V4 Flash 0731 is the official public-beta agent model: 1M-token context, stronger coding and tool use, and a native Responses API adapted for Codex. QuickSilver Pro serves the official DeepSeek build at FP8 precision or better for $0.06 / $0.18 per million tokens.
- 1M context
- Tools
- Reasoning · on by default
- Streaming
- JSON Schema output
You pay · input / output per 1M
$0.06 / $0.18
At list price
same rates as OpenRouter
Pricing comparison ($/1M tokens)
Bar length = price relative to the highest price shown
| Provider | Input | Output | vs QSP |
|---|---|---|---|
| QuickSilver Pro | $0.06 | $0.18 | — |
| OpenRouter(deepseek/deepseek-v4-flash-0731) | $0.06 | $0.18 | same |
| OpenAI (GPT-4o-mini) | $0.15 | $0.60 | 70% lower |
OpenRouter list source: openrouter.ai/api/v1/models/deepseek/deepseek-v4-flash-0731/endpoints
At a glance
- Context
- 1M tokens
- Input / 1M
- $0.06
- Output / 1M
- $0.18
- Thinks by default
- Yes
- Latency · live
- —
- AA Intelligence Index
- 41
Codex, agentic coding, tool use, and long-context automation.
When is DeepSeek V4 Flash the right call?
Curated from catalog capabilities and published prices, not a benchmark.
When to use
Default to V4 Flash for Codex and agentic coding, multi-step tool use, code generation, structured output, and long-context automation. The official 0731 build supports both OpenAI Chat Completions and Responses API clients while keeping the stable QSP model ID.
- Long documents and codebases, up to 1M tokens of context
- Agents that call tools, with strict JSON Schema output
- Multi-step reasoning, on by default
- Responses API clients as well as Chat Completions
When to use something else
For genuinely hard reasoning (competitive programming, multi-step proofs, complex math), escalate to V4 Pro. For Opus-class agentic / long-horizon planning, Kimi K2.6 is the better fit. For audio or GPT-4-class creative writing, stay on OpenAI. V4 Flash itself is text-only — if you need image input, 45 of our 91 models accept it.
Quickstart (curl)
Get an API key →curl https://api.quicksilverpro.io/v1/chat/completions \
-H "Authorization: Bearer $QSP_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-flash",
"messages": [{"role": "user", "content": "Hello!"}]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key=os.environ["QSP_KEY"],
)
response = client.chat.completions.create(
model="deepseek-v4-flash",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.quicksilverpro.io/v1",
apiKey: process.env.QSP_KEY,
});
const response = await client.chat.completions.create({
model: "deepseek-v4-flash",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);curl https://api.quicksilverpro.io/v1/responses \
-H "Authorization: Bearer $QSP_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-flash",
"input": "Hello!"
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key=os.environ["QSP_KEY"],
)
response = client.chat.completions.create(
model="deepseek-v4-flash",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)OpenAI-compatible. One-line migration via base_url.
Gateway behavior
Compatibility notes for this model.
prompt- Prompts up to 1M tokens.
- /v1/chat/completions: Supported
- /v1/responses: Supported
- streaming: Supported
- tools: Supported
- image input: Not listed for this model
- JSON Schema: Supported
- reasoning: Supported
Where the price comes from
- Provider reference
- $0.06 / $0.18openrouter.ai/api/v1/models/deepseek/deepseek-v4-flash-0731/endpoints
- Catalog verified
- Prompt cache · not compared
- $0.015 read
usage.cost = prompt_tokens × $0.06/1M + completion_tokens × $0.18/1M
FAQ
Common questions
Yes — V4 Flash thinks by default. For direct non-thinking chat through Chat Completions, pass reasoning: { enabled: false }; Responses API clients can set reasoning.effort to control depth.
$0.06 input / $0.18 output and $0.015 cache read per million tokens, matching the route-selected OpenRouter endpoint (deepinfra fp8) with no markup or discount. The route uses its pinned provider order or the cheapest eligible endpoint under sort: price and its quantization filters; the /models headline can differ. More expensive fallback hosts do not change your price. Use base_url=https://api.quicksilverpro.io/v1 and model="deepseek-v4-flash".
Yes. Use base_url=https://api.quicksilverpro.io/v1 with model="deepseek-v4-flash". QSP exposes both /v1/chat/completions and /v1/responses; Codex should use wire_api = "responses".