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DeepSeek · Open weights

DeepSeek V4.1 Flash Uncensored

Added Oct 1, 2026Open weights

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Use in the app

A lower-refusal finetune of DeepSeek V4.1 Flash with text input, optional reasoning, and tool calling. Supports a context window of up to 1M tokens.

  • Reasoning
  • Tools
Input
Text
Output
Text
Reasoning effort
none · low · medium · high
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.33
Output
$1.32
Cache read
$0.0083

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K
Average output (7 days)
643 tokens
Longer than 58% of 468 models

Side by side

DeepSeek V4.1 Flash Uncensored compared

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

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DeepSeek V4.1 Flash UncensoredDeepSeekThis modelMuse Glimmer 30BMetaRemove
ProviderDeepSeekMeta
Discovery tierOpen weightsOpen weights
AddedOct 1, 2026Aug 11, 2026
Limits
Context window1.05MBest131.07K
Max output65.54K—
Average output643 tokens682 tokens
Pricing, USD per 1M tokens
Input$0.33Best$0.35
Output$1.32Best$1.50
Cache read$0.0083Best$0.04
Performance
Throughput294.5 tok/s—
Time to first token4.8 s—
Request success (24h)84.6%100.0%Best
Benchmark indexes
Intelligence Index—17.5
Coding Index—49.0
Capabilities
ReasoningYesYes
ToolsYesYes
VisionNoYes
Structured outputNoYes
Reasoning effortnone, low, medium, highminimal, low, medium, high, xhigh

Public evaluations

Benchmarks

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

  • DeepSeek V4.1 Flash Uncensored
  • Muse Glimmer 30B

Intelligence Index

  • DeepSeek V4.1 Flash Uncensored—
  • Muse Glimmer 30B17.5
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 49.0

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 6.8%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 0.8%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 477 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 783 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 10.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 83.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 22.0%

  • GPQA Diamond

    Graduate-level science questions

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 83.5%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 0.5%

  • SciCode

    Scientific computing in Python

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 44.9%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • DeepSeek V4.1 Flash Uncensored: —
    • Muse Glimmer 30B: 83.3%

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
294.5 tok/s
Faster than 94% of 254 models
Time to first token
4.8 s
Quicker than 37% of 254 models
Prompt cache hits
94.4%
About $0.0262 per 1M input tokens with caching
Request success (24h)
84.9%
Unstable

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 11.2%
  • 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-uncensored",
    "reasoning_effort": "medium",
    "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-uncensored",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

DeepSeek

Other DeepSeek models, starting with the same family.