Ex0bit / MiniMax-M2.1-PRISM

huggingface.co
Total runs: 1.2K
24-hour runs: 2
7-day runs: -53
30-day runs: 578
Model's Last Updated: January 30 2026
text-generation

Introduction of MiniMax-M2.1-PRISM

Model Details of MiniMax-M2.1-PRISM

MiniMax-M2.1-PRISM (UNCENSORED)

** MiniMax-M2.1 Uncensored PRISM Advanced Abliteration**


💜 Sponsor & Support the Work

Every contribution directly funds my time & resources for the next major SOTA release.

Interested in Sponsoring?

If you're a company, research lab, or individual and want to see specific models or support this research at scale, I'd love to hear from you.

Sponsorship opportunities include:

  • Priority abliteration of models
  • Custom PRISM use-case configurations
  • Early access to new releases
  • Your logo/credit on model cards

📧 Reach out : Open a discussion on this repo or connect via Ko-fi


"Freedom of information isn't free — but together, we can make it accessible to all."

Thank you for believing in true Open AI.


Model Description

MiniMax-M2.1-PRISM is the fully uncensored version of MiniMax-M2.1, using our State of the ART PRISM pipeline (Projected Refusal Isolation via Subspace Modification) to remove refusal behaviors while preserving and even enhancing full model capabilities.

Base Model: MiniMax-M2.1

MiniMax-M2.1 is an open-source agentic language model designed for robust performance in:

  • Coding and software engineering
  • Tool use and multi-step reasoning
  • Instruction following
  • Long-horizon planning
  • Multilingual capabilities

Architecture : 229B parameters, 62 layers, 256 experts (8 active per token)


PRISM Methodology
Method: Projected Refusal Isolation via Subspace Modification

This model was abliterated using PRISM - a state-of-the-art abliteration methodology combining multiple principled techniques for effective refusal removal while preserving & enhancing model capabilities.


Performance Benchmarks
Base Model Performance
Benchmark Score
SWE-bench Verified 74.0
SWE-bench Multilingual 72.5
VIBE Average 88.6
MMLU-Pro 88.0
GPQA-D 83.0
AIME25 83.0
PRISM Abliteration Results
Metric Result
Adversarial Bench Prompts Responded 4096/4096 (100%)
Benign + Long Chain Coherence 100%
Response Quality Full technical accuracy validated

Our testing shows that PRISM abliteration maintains full model coherence with no capability degradation and MMLU increases of 5-8%.


Available Formats (contact for full tensors | additional quant work)
Format Size Description
GGUF IQ1_S ~43 GB Quantized with importance matrix
Safetensors (BF16) ~426 GB Full precision, 92 shards

Recommended Inference Parameters
temperature = 1.0
top_p = 0.95
top_k = 40
Default System Prompt
You are a helpful assistant.

Recommended Inference Frameworks
  1. SGLang (recommended for full precision)
  2. vLLM (recommended for full precision)
  3. llama.cpp (recommended for GGUF quantized)
  4. Transformers
llama.cpp Example
./llama-cli -m MiniMax-M2.1-PRISM-IQ1_S.gguf -ngl 99 -i -cnv --temp 0.7 --ctx-size 4096

Ethical Considerations

This model has been modified to reduce safety guardrails. Users are responsible for:

  • Complying with all applicable laws and regulations
  • Not using the model for illegal activities
  • Understanding the potential risks of unrestricted AI responses
  • Implementing appropriate safeguards in production environments

Motivation : This project exists as research and development experimentation into understanding how large language models encode and enforce refusal behaviors, contributing to broader AI safety research by providing empirical data on refusal mechanism localization and tradeoffs between safety and capability.


License

This model inherits the Modified-MIT License from the base MiniMax-M2.1 model.


Credits

Support

If you find this work useful, please consider supporting development so I can continue putting out the best models for the community:

Support me on Ko-fi


Contact

For questions or issues, please open an issue on this repository.

Runs of Ex0bit MiniMax-M2.1-PRISM on huggingface.co

1.2K
Total runs
2
24-hour runs
-65
3-day runs
-53
7-day runs
578
30-day runs

More Information About MiniMax-M2.1-PRISM huggingface.co Model

More MiniMax-M2.1-PRISM license Visit here:

https://choosealicense.com/licenses/mit

MiniMax-M2.1-PRISM huggingface.co

MiniMax-M2.1-PRISM huggingface.co is an AI model on huggingface.co that provides MiniMax-M2.1-PRISM's model effect (), which can be used instantly with this Ex0bit MiniMax-M2.1-PRISM model. huggingface.co supports a free trial of the MiniMax-M2.1-PRISM model, and also provides paid use of the MiniMax-M2.1-PRISM. Support call MiniMax-M2.1-PRISM model through api, including Node.js, Python, http.

MiniMax-M2.1-PRISM huggingface.co Url

https://huggingface.co/Ex0bit/MiniMax-M2.1-PRISM

Ex0bit MiniMax-M2.1-PRISM online free

MiniMax-M2.1-PRISM huggingface.co is an online trial and call api platform, which integrates MiniMax-M2.1-PRISM's modeling effects, including api services, and provides a free online trial of MiniMax-M2.1-PRISM, you can try MiniMax-M2.1-PRISM online for free by clicking the link below.

Ex0bit MiniMax-M2.1-PRISM online free url in huggingface.co:

https://huggingface.co/Ex0bit/MiniMax-M2.1-PRISM

MiniMax-M2.1-PRISM install

MiniMax-M2.1-PRISM is an open source model from GitHub that offers a free installation service, and any user can find MiniMax-M2.1-PRISM on GitHub to install. At the same time, huggingface.co provides the effect of MiniMax-M2.1-PRISM install, users can directly use MiniMax-M2.1-PRISM installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

MiniMax-M2.1-PRISM install url in huggingface.co:

https://huggingface.co/Ex0bit/MiniMax-M2.1-PRISM

Url of MiniMax-M2.1-PRISM

MiniMax-M2.1-PRISM huggingface.co Url

Provider of MiniMax-M2.1-PRISM huggingface.co

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