DeepSeek

Available Coding Agents Vision

DeepSeek V4.1 Flash

The right balance of capability and cost for coding and agents, with a 1M-token context window.

Start building Try in Playground Playground takes text only Read the docs
Tokens of context
1M
in, text out
Text + image
Input / output per 1M tokens
$0.15 / $0.60
Cached input per 1M tokens
$0.006

About the model

DeepSeek V4.1 Flash is the cost-efficient tier of DeepSeek's V4.1 family, and this release, 1017, is its October 2026 update. It's a 552B-parameter Mixture-of-Experts model that activates 8B parameters while reading input and 16B while generating output, which keeps costs low for input-heavy work like agents. It has a 1M-token context window and native image understanding.

Start building

OpenAI compatible: point your code or coding agent at Verda Inference with your API key and the model ID deepseek-4-1-flash-1017 .

curl -X POST "https://inference.verda.com/v1/chat/completions" \
  -H "Authorization: Bearer ${VERDA_INFERENCE_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-4-1-flash-1017",
    "messages": [
      {
        "role": "user",
        "content": "What is the best viewpoint in Helsinki?"
      }
    ],
    "max_tokens": 2048
  }'

Supports thinking and non-thinking modes, chosen with reasoning_effort .

Docs: default settings

What it's good at

Capable, everyday coding

Quick fixes, code reviews and test generation, with the capability for most coding work.

Use it for: reviewing every pull request and generating tests on every commit.

Let your agents run

Run it on every agent step, pull request and support ticket, without rationing requests.

Use it for: multi-step agent workflows and automation.

Long context, kept affordable

It keeps a small memory of everything it reads, so long sessions, up to 1M tokens, stay light.

Use it for: working across whole codebases and long documents.

Speed or depth, your choice

Switch thinking off for quick answers, or on for harder problems.

Use it for: chat assistants, and harder reasoning when it counts.

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Input
$2.00
Cache read
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Output
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Context
1M tokens
Input
Text & image
Tool calling
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Context
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Tool calling
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Available now

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