Abliterated Large V2

Abliterated Large V2

Abliteration.ai
MiniMax M3

MiniMax M3

MiniMax
+
+

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About

Abliterated Large V2 is a large language model developed by Abliteration AI for advanced reasoning, cybersecurity research, AI red teaming, and autonomous agent workflows. Based on Z.ai's GLM 5.3 architecture, the model uses weight-level modifications designed to reduce refusal behavior while preserving coding and reasoning capabilities. It supports a one-million-token context window, enabling analysis of extensive source code repositories, technical documentation, and lengthy task histories. The model is optimized for security research, vulnerability analysis, exploit testing, and complex software engineering tasks. Its capabilities include tool calling, structured outputs, configurable reasoning, and integration with external applications through compatible APIs. Abliterated Large V2 is available as a hosted text-only model through Abliteration AI and supported third-party AI inference providers.

About

MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Cybersecurity researchers, penetration testers, red teams, security engineers, AI safety researchers, software developers, autonomous agent builders, vulnerability researchers, and organizations seeking advanced reasoning, security testing, reduced-refusal AI models, and tool-integrated technical automation

Audience

MiniMax M3 is best suited for developers, AI engineers, coding assistant builders, enterprise automation teams, research teams, data teams, agent developers, and organizations that need open-weight AI for coding, long-context reasoning, multimodal understanding, tool use, repository analysis, and autonomous workflows

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$3 per 1M tokens (input)
$3.00 per 1 million input tokens, $5.00 per 1 million output tokens, and $0.30 per 1 million cached input tokens
Free Version Not Supported
Free Trial Not Supported

Pricing

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 4.0 / 5
features 4.0 / 5

Pros & Cons from Real Users

Pros

  • The multimodal side also makes it more flexible than a code-only model. Being able to work across text, images, video-style understanding, and code gives it more room to support real workflows instead of being boxed into one narrow use case. For agent builders, the best part is that M3 is clearly designed around tool use and multi-step execution. MiniMax specifically calls out autonomous task decomposition and tool invocation, which is exactly what matters when a model is powering coding assistants, workflow agents, or automated dev tools.

Cons

  • The main catch is infrastructure and trust. Even with sparse attention and MoE efficiency, this is still a large model, so deployment is not casual. I would also want to benchmark it on my own repos before depending on it for production work.

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Abliteration.ai
Founded: 2025
United States
abliteration.ai/

Company Information

MiniMax
Founded: 2021
Singapore
www.minimax.io

Alternatives

Alternatives

MiniMax M3

MiniMax M3

MiniMax
Beam

Beam

Reflection
Sarvam-M

Sarvam-M

Sarvam
MiniMax

MiniMax

MiniMax AI

Categories

AI Models Supported

Categories

Integrations

Abliteration.ai Supported
Alibaba AI Coding Plan Not Supported
BLACKBOX AI Not Supported
Cline Not Supported
ClinePass Not Supported
Factory Droid Not Supported
Fireworks AI Not Supported
Kilo Code Not Supported
MaxHermes Not Supported
MiniMax Agent Not Supported
MiniMax Code Not Supported
Ollama Not Supported
OpenClaw Not Supported
OpenCode Go Not Supported
OpenCode Zen Not Supported
OpenTag Not Supported
Pi Agent Not Supported
Tabbit Browser Not Supported
Together AI Not Supported
Venice.ai Supported

Integrations

Abliteration.ai Not Supported
Alibaba AI Coding Plan Supported
BLACKBOX AI Supported
Cline Supported
ClinePass Supported
Factory Droid Supported
Fireworks AI Supported
Kilo Code Supported
MaxHermes Supported
MiniMax Agent Supported
MiniMax Code Supported
Ollama Supported
OpenClaw Supported
OpenCode Go Supported
OpenCode Zen Supported
OpenTag Supported
Pi Agent Supported
Tabbit Browser Supported
Together AI Supported
Venice.ai Not Supported
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