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DeepSeek V4.1 Flash

DeepSeek · OpenAI-compatible API

deepseek/deepseek-v4.1-flash

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USD / 1M tokens

Input$0.17

Cache Read$0.005

Cache Write—

Output$0.7

Context: 1M
Max Output: 384K
Tool Calling: ✓
Reasoning: ✓
Vision: ✗
Streaming: ✓

OpenAI-compatible API

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.iteracompute.com/v1",
    api_key=os.environ["ITERACOMPUTE_API_KEY"],
)
response = client.chat.completions.create(
    model="deepseek/deepseek-v4.1-flash",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.iteracompute.com/v1",
  apiKey: process.env.ITERACOMPUTE_API_KEY,
});
const response = await client.chat.completions.create({
  model: "deepseek/deepseek-v4.1-flash",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

curl https://api.iteracompute.com/v1/chat/completions \
  -H "Authorization: Bearer $ITERACOMPUTE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek/deepseek-v4.1-flash",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

deepseek/deepseek-v4.1-flashView Docs →

Catalog updated: 2026-10-19.

Overview

Text input, streaming and structured outputs; up to 393,216 output tokens.

Tasks and selection tradeoffs

Frequent small code edits

Use focused source context, review each diff and run fast unit tests.

Repeated-prefix text workflows

Reuse stable instructions and inspect reported cached tokens rather than assuming a hit.

Task suggestions based on catalog features and price, not model quality benchmarks.

Choose your tool

OpenAI SDKCall from Python or JavaScript Vercel AI SDKBuild a TypeScript application

Choose a model and tool for your task →

Pricing

Prices in USD per 1M tokens.

Input$0.17

Cache Read$0.005

Cache Write—

Output$0.7

Example task: Apply and verify a focused patch

Assume 20,000 aggregate input tokens and 2,000 billable output tokens across all calls. No cache hit.

20,000 × $0.17 / 1M + 2,000 × $0.7 / 1M = $0.004800

If usage actually reports 15,000 of those input tokens as cached, replace that portion at the cached-input rate ($0.005/1M): $0.002325. Cached tokens are part of total input, never added on top.

Illustrative calculation using the 2026-10-19 catalog snapshot. Include every agent call and retry, repeated history and billable reasoning output; settle against actual usage and current Console prices.

Estimate your monthly cost

Uses the 2026-10-19 catalog snapshot, independently of the live prices above. USD per 1M tokens; an estimate, not a bill.

Estimate includes standard text input, cache reads and text output only. Long-context premiums, service tiers, cache writes, image output and tool fees are excluded.

Model

Input tokens / request

Billable output tokens / request

Cached share of input (%)

Requests / month

Input includes cached tokens; output includes billable reasoning. Count every API request, including agent steps and retries.

Estimated monthly cost

—USD / month

DeepSeek V4.1 Flash

Uncached input: —
Cache read: —
Billable output: —

Connect this model →

Calculation and billing basis

Monthly cost = requests × [input × (1 − cached share) × input rate + input × cached share × cache-read rate + output × output rate] / 1,000,000.

Cached tokens are part of total input, never added on top. Use actual cache-read hits from usage; repeating a prompt does not guarantee a hit. Missing rates are unconfirmed, not $0. Separate cache-write, storage and other additional fees are excluded. Settle against actual usage and current Console prices.

Enable JavaScript to use the calculator. The worked example above remains available.

Usage limits

Text-only. A repeated prompt is not a guaranteed cache hit; inspect the cached tokens reported in usage.
See the current context and maximum output in the model specifications above. Input and requested output share the context budget.
The context and capability flags describe the public catalog. They do not establish a particular tool workflow or a quality score.
Start with one representative task. Check correctness, actual usage and response time before increasing traffic.
Use the integration examples to connect your application and handle tool results.

API parameters

Parameter / protocol field	Usage
`model / messages`	Use the exact model ID and chat message list
`tools / tool_calls / tool messages`	Use tools to define functions and role=tool to return their results
`stream / stream_options.include_usage`	Use SSE streaming with final usage
`max_tokens`	Set an output budget within the model and account limits

Parameters vary by model. Keep model-specific controls separate from shared OpenAI-compatible fields.

API

Base URL: https://api.iteracompute.com/v1
Endpoint: POST /v1/chat/completions
Model ID: deepseek/deepseek-v4.1-flash
Authentication: Authorization: Bearer ITERACOMPUTE_API_KEY

View Docs

FAQ

How do I use DeepSeek V4.1 Flash with the OpenAI SDK?

Set base_url to https://api.iteracompute.com/v1 and model to deepseek/deepseek-v4.1-flash. Authenticate with your IteraCompute API key.

What does DeepSeek V4.1 Flash cost?

See the pricing section for current input, cached-input and output rates in USD per 1M tokens. Check the refresh time before use.

What context length is available?

See the model specifications above for the current context and maximum output. Input and requested maximum output share the context budget.

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Create your key, choose a tool and get a non-empty first reply.

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