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DeepSeek V4 · 1M context

DeepSeek V4 API, OpenAI-compatible

Both official DeepSeek V4 releases — deepseek-v4-flash and deepseek-v4-pro — with a 1,048,576-token context window, served on Cloudflare Workers AI infrastructure through one OpenAI-compatible endpoint. Prepaid USD credits, per-token billing you can audit, and 40% off the list price for the launch period.

What you get

Context window
1,048,576 tokens (input + max_tokens)
Function calling
Yes — verified in our contract tests on both models
Reasoning
Yes — streamed as reasoning_content, billed once at output rate
Streaming
SSE, flushed chunk by chunk
Upstream IDs (public)
@cf/deepseek-ai/deepseek-v4-flash-0731 · @cf/deepseek-ai/deepseek-v4-pro-0813
Privacy
Runs on Cloudflare infrastructure; we log metadata only — never prompt or response content

Pricing (40% off list, applied automatically)

deepseek-v4-flash40% off
Input
$0.44$0.264
Output
$1.32$0.792

@cf/deepseek-ai/deepseek-v4-flash-0731

deepseek-v4-pro40% off
Input
$1.32$0.792
Output
$3.96$2.376

@cf/deepseek-ai/deepseek-v4-pro-0813

Struck price = list. Cached-input rates and live prices for all seven models are on the models page; prices shown here are kept in sync with the billing database.

Measured, not quoted

Our own measurements, 2026-08-16. Live status and per-model numbers stay on the models page.

~1.0 s

time to first token, deepseek-v4-flash (p50, 5 streams)

~102 tok/s

streaming throughput, deepseek-v4-flash (p50)

~45 ms / 1K tokens

prefill rate at 100K–300K input on flash

76.5 s

first token on a real 600K-token prompt (pro) — use streaming for large jobs

Ship in two lines of config

If your code already talks to the OpenAI API — or to DeepSeek’s own OpenAI-style endpoint — you only change base_url and the key. Model IDs match DeepSeek’s official naming.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.clfaigateway.dev/v1",
    api_key="sk-gw-...",  # app.clfaigateway.dev
)

resp = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Summarize this repository..."}],
    stream=True,
)
for chunk in resp:
    print(chunk.choices[0].delta.content or "", end="")

DeepSeek V4 API — common questions

Yes — the official open-weight releases DeepSeek-V4-Flash-0731 and DeepSeek-V4-Pro-0813, served on Cloudflare Workers AI. We publish the exact upstream IDs on every response, so you can verify what is answering.

See upstream IDs →

No. Inference runs on Cloudflare’s hosted deployment of the open-weight models. On our side we log request metadata only (tokens, latency, cost) — never prompt or completion content.

Data policy →

The window is 1,048,576 tokens counting input plus your max_tokens. Prefill is real work at this size — roughly 45 ms per 1,000 input tokens in our tests — so use streaming for large requests, and expect retryable no_capacity errors at peak on very large prompts.

Context & caching docs →

Prepaid credits, per real token, at the current per-model price — 40% off the list price during the launch period, applied automatically. Every request returns its exact cost, and a failed request that produced nothing costs $0.

Billing docs →

deepseek-v4-flash is the value pick: fast (about 1 s to first token, ~100 tok/s measured) and a third of Pro’s price. deepseek-v4-pro is the flagship for the hardest reasoning over huge context, and queues longer under load.