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  1. Models
  2. Text
  3. Mlabonne

Neural Daredevil 8B abliterated

The best performing 8B abliterated model according to most benchmarks.

Pricing

Auto routing · per 1M tokens
Input
$0.44
Output
$0.44
Cache read
$0.22
Compare provider prices

Specifications

Context window
8.2K
Max output
8.2K
Parameters
8B

Benchmarks

Leaderboard results

BenchmarkScoreRank on NanoGPT
UGI Leaderboard

UGI Leaderboard data, Apache-2.0 · Updated Oct 16, 2026

UGI Score

33.2

#96 of 149

UGI Willingness

6.5

#22 of 149

UGI Writing

24.9

#137 of 149

Filtered and ranked to models on NanoGPT.

Providers

Choose or restrict providers with the API. Provider-selection prices include the selection markup. Provider selection guide · Pricing API (JSON, USD per 1K tokens)

Auto
Auto
Recommended
$0.44$0.44$0.22N/AN/A
Kitani
Kitani
INT4
GLB
$0.441$0.441$0.221N/AN/A
Privacy:ZDR, prompts not retained
Batch API
ProviderInputOutputCached input
Auto
Automlabonne/NeuralDaredevil-8B-abliterated
$0.44/M$0.44/M$0.22/M

Batch rows for this model use normal routing and cost the same as standard API requests. Set provider in a row to choose a provider.

Related text models

Compare Neural Daredevil 8B abliterated with similar models from the same provider or model family.

Llama 3.3 70B Instruct abliterated

huihui-ai/Llama-3.3-70B-Instruct-abliterated

An abliterated (removed restrictions and censorship) version of Llama 3.3 70b.

Llama 3 70B abliterated

failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5

An abliterated (removed restrictions and censorship) version of Llama 3.1 70b.

Muse Ember

meta/muse-ember

Meta's Muse Ember is the smallest and most efficient Muse model, built for the work agents repeat all day: tool calls, coding-agent subtasks, routing, and extraction. It accepts text, images, audio, video, and PDF documents across a one-million-token context window, supports tool calling and structured output, and always reasons before answering.

Muse Spark Open

meta/muse-spark-open

Built with Muse Spark Open. Meta's open-weight 816B-A42B model for coding and agentic workflows. Text and image input, text output, tool calling and structured output. Always reasons at low, medium, high, or xhigh effort. Custom Muse Model License and Usage Policy apply.

Muse Wonder

meta/muse-wonder

Meta's Muse Wonder is a frontier reasoning model designed for complex personal and professional agentic tasks. It accepts text, images, audio, video, and PDF documents across a one-million-token context window, supports tool calling and structured output, and always reasons before answering.

Muse Spark 1.3

meta/muse-spark-1.3

Meta's Muse Spark 1.3 is a frontier multimodal reasoning model for long-horizon coding and agentic workflows, with strong gains in computer use, browsing, professional tool use, codebase understanding, instruction following, and million-token retrieval. It accepts text, images, audio, video, and files, supports tool calling and structured output, and always reasons before answering.