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Qwen · Open weights

Qwen 2.5 32B Abliterated

Added Jan 6, 2025Open weights

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Use in the app

Uncensored version of Qwen 2.5 32B Instruct with restrictions removed.

Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.70
Output
$0.70

Reference prices as published by the model provider. API example

Specifications

Context window
32.8K
Max output
8.2K
Average output (7 days)
806 tokens
Longer than 65% of 465 models

Side by side

Qwen 2.5 32B Abliterated compared

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

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Qwen 2.5 32B AbliteratedQwenThis modelDeepSeek V4 ProDeepSeekRemove
ProviderQwenDeepSeek
Discovery tierOpen weightsOpen weights
AddedJan 6, 2025Apr 24, 2026
Limits
Context window32.77K1.05MBest
Max output8.19K384KBest
Average output806 tokens416 tokens
Pricing, USD per 1M tokens
Input$0.70$0.70
Output$0.70Best$1.40
Cache read—$0.07
Performance
Throughput19.6 tok/s49.9 tok/sBest
Time to first token2.1 sBest2.9 s
Request success (24h)60.4%99.7%Best
Benchmark indexes
Intelligence Index—36.0
Coding Index—68.8
Capabilities
ReasoningNoYes
ToolsNoYes
Structured outputNoYes
Reasoning effort—none, high, max

Public evaluations

Benchmarks

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

  • Qwen 2.5 32B Abliterated
  • DeepSeek V4 Pro

Intelligence Index

  • Qwen 2.5 32B Abliterated—
  • DeepSeek V4 Pro36.0
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 68.8

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 56.7%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 25.9%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 1,256 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 1,449 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 11.4%

  • AA-LCRv1.1

    Reasoning across long documents

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 80.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 41.0%

  • GPQA Diamond

    Graduate-level science questions

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 92.8%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 14.1%

  • SciCode

    Scientific computing in Python

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 51.0%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Qwen 2.5 32B Abliterated: —
    • DeepSeek V4 Pro: 80.3%

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
19.6 tok/s
Faster than 12% of 250 models
Time to first token
2.1 s
Quicker than 73% of 250 models
Prompt cache hits
0.0%
Request success (24h)
60.4%

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.

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": "huihui-ai/Qwen2.5-32B-Instruct-abliterated",
    "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="huihui-ai/Qwen2.5-32B-Instruct-abliterated",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

Other Qwen models, starting with the same family.