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DeepSeek · Open weights

DeepSeek V4 Flash 0423 (Thinking)

Added Oct 7, 2026Open weights

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Use in the app

The original 0423 checkpoint of DeepSeek V4 Flash, with a 1M-token context window, text input, tool calling, structured output, and optional reasoning.

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

Pricing

USD per 1M tokens
Input
$0.14
Output
$0.28
Cache read
$0.028

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
—
Average output (7 days)
1.1K tokens
Longer than 72% of 465 models

Side by side

DeepSeek V4 Flash 0423 (Thinking) compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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DeepSeek V4 Flash 0423 (Thinking)DeepSeekThis modelDeepSeek V4.1 Flash 1017 ThinkingDeepSeekRemove
ProviderDeepSeekDeepSeek
Discovery tierOpen weightsOpen weights
AddedOct 7, 2026Oct 17, 2026
Limits
Context window1.05M1.05M
Max output—393.22K
Average output1.1K tokens1.2K tokens
Pricing, USD per 1M tokens
Input$0.14$0.10Best
Output$0.28Best$0.60
Cache read$0.028$0.003Best
Performance
Throughput102.8 tok/s230.5 tok/sBest
Time to first token1.8 sBest2.6 s
Request success (24h)96.8%99.8%Best
Benchmark indexes
Intelligence Index24.445.1Best
Coding Index52.0—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionNoYes
Structured outputYesYes
Reasoning effortnone, low, high, maxnone, low, high, max

Public evaluations

Benchmarks

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

  • DeepSeek V4 Flash 0423 (Thinking)
  • DeepSeek V4.1 Flash 1017 Thinking

Intelligence Index

  • DeepSeek V4 Flash 0423 (Thinking)24.4
  • DeepSeek V4.1 Flash 1017 Thinking45.1

DeepSeek V4 Flash 0423 (Thinking) tested at high reasoning effort

DeepSeek V4 Flash 0423 (Thinking): Better than 59% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • DeepSeek V4 Flash 0423 (Thinking): 52.0
    • DeepSeek V4.1 Flash 1017 Thinking: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • DeepSeek V4 Flash 0423 (Thinking): 28.5%
    • DeepSeek V4.1 Flash 1017 Thinking: 66.6%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • DeepSeek V4 Flash 0423 (Thinking): 8.7%
    • DeepSeek V4.1 Flash 1017 Thinking: 36.7%Top

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • DeepSeek V4 Flash 0423 (Thinking): 1,041 Elo
    • DeepSeek V4.1 Flash 1017 Thinking: 1,570 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • DeepSeek V4 Flash 0423 (Thinking): 1,000 Elo
    • DeepSeek V4.1 Flash 1017 Thinking: 1,746 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • DeepSeek V4 Flash 0423 (Thinking): 10.4%
    • DeepSeek V4.1 Flash 1017 Thinking: 17.2%Top

  • AA-LCRv1.1

    Reasoning across long documents

    • DeepSeek V4 Flash 0423 (Thinking): 72.0%
    • DeepSeek V4.1 Flash 1017 Thinking: 82.7%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • DeepSeek V4 Flash 0423 (Thinking): —
    • DeepSeek V4.1 Flash 1017 Thinking: 26.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • DeepSeek V4 Flash 0423 (Thinking): 30.3%
    • DeepSeek V4.1 Flash 1017 Thinking: 43.3%Top

  • GPQA Diamond

    Graduate-level science questions

    • DeepSeek V4 Flash 0423 (Thinking): 86.7%
    • DeepSeek V4.1 Flash 1017 Thinking: —

  • IFBench

    Following precise output instructions

    • DeepSeek V4 Flash 0423 (Thinking): 73.5%
    • DeepSeek V4.1 Flash 1017 Thinking: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • DeepSeek V4 Flash 0423 (Thinking): 3.0%
    • DeepSeek V4.1 Flash 1017 Thinking: 33.8%Top

  • SciCode

    Scientific computing in Python

    • DeepSeek V4 Flash 0423 (Thinking): 40.2%
    • DeepSeek V4.1 Flash 1017 Thinking: 55.9%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • DeepSeek V4 Flash 0423 (Thinking): 38.6%
    • DeepSeek V4.1 Flash 1017 Thinking: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • DeepSeek V4 Flash 0423 (Thinking): 95.6%
    • DeepSeek V4.1 Flash 1017 Thinking: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • DeepSeek V4 Flash 0423 (Thinking): 72.0%
    • DeepSeek V4.1 Flash 1017 Thinking: 82.7%Top

Scores from Artificial Analysis, updated Oct 26, 2026. DeepSeek V4 Flash 0423 (Thinking) was tested at high reasoning effort; compare scores measured at the same effort.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
102.8 tok/s
Faster than 64% of 250 models
Time to first token
1.8 s
Quicker than 81% of 250 models
Prompt cache hits
72.6%
About $0.0586 per 1M input tokens with caching
Request success (24h)
96.8%
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 80.0%
  • 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-flash-0423:thinking",
    "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-flash-0423:thinking",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

DeepSeek

Other DeepSeek models, starting with the same family.