DeepSeek V4.1 Flash 1017

Text

DeepSeek documents the official direct API as DeepSeek-V4.1-Flash-1017, updated on 2026-10-17. Third-party service options may use older versions; their 1017 status is unverified. DeepSeek officially lists image input, a 1M-token context and up to 384K output tokens for V4.1 Flash. On RunAPI, use deepseek-flash; image input and these context and output limits have not been tested across all service options.

Input $0.30 / 1M tokens | Output $1.20 / 1M tokens DeepSeek V4.1 Flash 1017 API reference →

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runapi.ai

# Base URL
https://runapi.ai

# Endpoints
POST /v1/chat/completions
POST /v1/responses
POST /v1/messages
POST /v1beta/models/deepseek-flash:generateContent
POST /v1beta/models/deepseek-flash:streamGenerateContent

curl https://runapi.ai/v1/chat/completions \
  -H "Authorization: Bearer $RUNAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "deepseek-flash",
  "messages": [
    {
      "role": "user",
      "content": "Refactor this Python module for readability, explain each change, then add unit tests for the edge cases."
    }
  ]
}'

from openai import OpenAI

client = OpenAI(
    base_url="https://runapi.ai/v1",
    api_key="your-runapi-key"
)

response = client.chat.completions.create(
    model="deepseek-flash",
    messages=[{"role": "user", "content": "Refactor this Python module for readability, explain each change, then add unit tests for the edge cases."}]
)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://runapi.ai/v1",
  apiKey: "your-runapi-key"
});

const response = await client.chat.completions.create({
  model: "deepseek-flash",
  messages: [{ role: "user", content: "Refactor this Python module for readability, explain each change, then add unit tests for the edge cases." }]
});

https://runapi.ai 5 endpoints

4 versions available

Full model reference: endpoints, parameters and pricing →

OVERVIEW

What changed in DeepSeek V4.1 Flash 1017

DeepSeek put V4.1 Flash on its API on September 10, 2026. It is the smallest model in a new architecture family: a 552B-parameter Mixture-of-Experts built as a causal encoder-decoder, with 8B parameters active while it reads input and 16B while it writes output. V4 Flash kept the V4 Preview architecture through its July update, and image input needed a separate experimental model. DeepSeek documents the official direct API as DeepSeek-V4.1-Flash-1017, updated on 2026-10-17. Third-party service options may use older versions; their 1017 status is unverified. DeepSeek officially lists image input, a 1M-token context and up to 384K output tokens for V4.1 Flash. On RunAPI, use deepseek-flash; image input and these context and output limits have not been tested across all service options.

The KV cache also got smaller. DeepSeek says it needs a quarter of the HBM and an eighth of the SSD storage of the previous generation, and links that to lower cache-hit charges in agent workloads. DeepSeek credits new pre-training methods and larger-scale RL post-training for benchmark scores above its own V4-Pro.

The release kept the old model name. DeepSeek serves V4.1 Flash as deepseek-flash, an ID that moves to each new Flash release, and there is no deepseek-v4.1-flash ID. RunAPI uses the same ID on its OpenAI-compatible and Anthropic-compatible endpoints.

Released

September 10, 2026

Architecture

552B MoE, causal encoder-decoder

Active parameters

8B for input, 16B for output

Context window

1M tokens. DeepSeek official specification; not tested across all RunAPI service options

Max output

384K tokens. DeepSeek official specification; not tested across all RunAPI service options

Thinking

On by default, non-thinking mode available

API model ID

deepseek-flash

Playground

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Specifications

Provider	DeepSeek
Model ID	deepseek-flash
Modality	Text
Task types	Synchronous
API endpoint	/v1/chat/completions
	/v1/responses

	/v1/messages
	/v1beta/models/deepseek-flash:generateContent
	/v1beta/models/deepseek-flash:streamGenerateContent
Billing unit	1K tokens
Catalog status	Operational

HOW IT WORKS

Use This Model in 3 Steps

Get Your Key

Sign up for free and create an API key for deepseek-flash from the dashboard.
Send a Request

POST to /v1/chat/completions with the deepseek-flash model slug and your parameters.
Get Results

Read the completed deepseek-flash response directly from the endpoint.

What this model offers

Endpoint coverage

Exposes 2 public endpoint(s): chat_completion, message.

Usage-based billing

Metered by 1K tokens with no subscription requirement.

DeepSeek V4.1 Flash 1017 Pricing

Endpoint

Price

chat_completion

Input: $0.30 / 1M tokens Output: $1.20 / 1M tokens

Cache read: $0.01 / 1M tokens

message

Input: $0.30 / 1M tokens Output: $1.20 / 1M tokens

Cache read: $0.01 / 1M tokens

API REFERENCE

Endpoint Specification

Endpoint: POST /v1/chat/completions
Model ID: deepseek-flash
Task Types: chat_completion, message

Request parameters

No request parameters are published for this endpoint.

USE CASES

Customer support

Answer customer questions from a private knowledge base, reducing ticket volume.

Document analysis

Draft contract summaries and flag key clauses for attorney review.

Code generation

Auto-generate unit tests, code reviews, and refactoring suggestions in CI.

Trusted by developers

API Calls / Day

0.0%

Success Rate

Unavailable

Avg Generation

Verified customer feedback is not available for this model yet.

FAQ

Frequently asked questions about DeepSeek V4.1 Flash 1017

Is DeepSeek V4.1 Flash a new model or a retrained V4 Flash?

It is a new model. DeepSeek built it on a new causal encoder-decoder architecture with 552B total parameters, then trained it with new pre-training methods and larger-scale RL. The July 2026 V4 Flash update had kept the earlier architecture and was only post-trained again.

How does V4.1 Flash score against V4 Flash?

On DeepSeek's published numbers, Terminal-Bench 2.1 went from 82.7 to 90.6, CyberGym from 76.7 to 88.1, and Agents' Last Exam from 25.2 to 31.8. All three figures are DeepSeek's own, taken from its change log.

What context window and output limit does V4.1 Flash have?

Does V4.1 Flash support tool calling and JSON output?

Yes. DeepSeek's model table for V4.1 Flash marks tool calls and JSON output as supported.

Do requests to deepseek-v4-flash still work?

Use deepseek-flash for new code. DeepSeek documents that its official direct API serves the retired names deepseek-v4-flash and deepseek-v4-flash-vision-exp with DeepSeek-V4.1-Flash-1017 at the Flash price. Third-party mappings to 1017 remain unconfirmed.

How do I select deepseek-flash?

Pass the model ID shown in the quickstart.

What's the rate limit on this variant?

Per-key rate limits scale with your usage tier. The pricing page shows current limits. If you need higher throughput, contact support to discuss tier upgrades.

Can I switch variants later?

Yes. Variant is a parameter in the request. Switch by changing the model ID — no code changes, no re-authentication, no separate billing setup. All variants share the same API key and request shape.

Does it stream?

Where streaming is available, RunAPI streams end-to-end. LLM models support token-level streaming. Media models use async task polling or webhook callbacks for result delivery.

Where do I report quality issues?

Open an issue on the public GitHub repo or email support at [email protected]. Include the task ID and model ID so the team can investigate the specific generation.

Do I need a separate provider account?

No. Your RunAPI API key is enough to access this variant and every other model in the catalog. You do not need accounts with the underlying provider.

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