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DeepSeek · Open weights

DeepSeek V4.1 Flash

Added Sep 8, 2026Open weights

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Use in the app

DeepSeek V4.1 Flash supports text and image input, reasoning, tool calling, and structured output with a 1M-token context window. This is a rate-limited beta with limited capacity, intended for testing rather than production use.

  • Reasoning
  • Tools
  • Vision
  • Structured output
Input
Text, Images
Output
Text
Reasoning effort
none · low · high · max
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.09
Output
$0.25
Cache read
$0.006

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
384K
Average output (7 days)
376 tokens
Longer than 38% of 465 models

Side by side

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TryClaude Sonnet 4.6Ling 3.0 Flash VLInklingAll 3

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

Intelligence Index

24.7

Better than 60% of 326 scored models

3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    47.8%

    Workflow automation, penalized for guardrail violations

    Better than 61% of 173 scored models

  • AutomationBench-AA tasks completed

    14.2%

    Workflows finished end to end without a guardrail violation

    Better than 58% of 173 scored models

  • AA-Briefcasev1.1

    1,118 Elo

    Agentic knowledge work, rated head to head

    Better than 54% of 166 scored models

  • GDPval-AAv2.1

    1,340 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 58% of 187 scored models

Document reasoning

  • GDP.pdf

    3.8%

    Professional reasoning over PDF documents, all-pass rate

    Better than 14% of 171 scored models

  • AA-LCRv1.1

    55.3%

    Reasoning across long documents

    Better than 33% of 309 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    10.8%

    Expert-level questions across academic fields

    Better than 33% of 323 scored models

Coding

  • Terminal-Benchv4.0

    5.6%

    Practical software engineering in a terminal

    Better than 54% of 171 scored models

  • SciCode

    35.5%

    Scientific computing in Python

    Better than 11% of 174 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    55.3%

    Long-context reasoning, earlier grading

    Better than 33% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Throughput
157.4 tok/s
Faster than 78% of 250 models
Time to first token
1.8 s
Quicker than 81% of 250 models
Prompt cache hits
83.8%
About $0.0196 per 1M input tokens with caching
Request success (24h)
99.8%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 98.6%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek/deepseek-v4.1-flash",
    "reasoning_effort": "none",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="deepseek/deepseek-v4.1-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

DeepSeek

Other DeepSeek models, starting with the same family.