README.md

metadata

license: other
license_name: prism-research
license_link: LICENSE.md
language:
  - en
  - zh
tags:
  - minimax
  - prism
  - moe
  - reasoning
  - coding
  - agentic
  - abliterated
pipeline_tag: text-generation
library_name: transformers
base_model:
  - MiniMaxAI/MiniMax-M2.5
base_model_relation: finetune

MiniMax-M2.5-PRISM-PRO

A Powerful Production ready fully uncessored model intended for COMPLETE over-refusal and propaganda mechanisms suppression using our SOTA PRISM-PRO pipeline.

PRISM-PRO is available for purchase: https://ko-fi.com/s/0a23d1b9a5

For Custom trained PRISM versions or raw tensors access reach out @ https://ko-fi.com/ex0bit.

☕ Support Our Work

If you enjoy our work and find it useful, please consider sponsoring or supporting us!

Option	Description
PRISM PRO VIP Membership	Access to all PRISM models
Bitcoin	bc1qarq2pyn4psjpcxzp2ghgwaq6y2h4e53q232x8r

---

Model Highlights

• PRISM Ablation — State-of-the-art technique that removes over-refusal behaviors while preserving model capabilities
• SOTA Coding Performance — 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, 76.3% on BrowseComp (with context management)
• Frontier Agentic Capabilities — Industry-leading performance in tool use, search, and complex multi-step tasks
• Efficient Reasoning — Trained with RL to reason efficiently and decompose tasks optimally, 37% faster than M2.1
• Cost-Effective — $1 for continuous operation at 100 tok/s for an hour; $0.30 at 50 tok/s
• Modified-MIT Base License — Based on MiniMax's open-weight release

Base Model Architecture

Base MiniMax-M2.5 is a Mixture-of-Experts (MoE) model extensively trained with reinforcement learning across hundreds of thousands of complex real-world environments.

Specification	Value
Architecture	Sparse Mixture-of-Experts (MoE)
Training	Extensive RL in 200K+ real-world environments
Languages	10+ (Go, C, C++, TypeScript, Rust, Kotlin, Python, Java, JavaScript, PHP, Lua, Dart, Ruby)
Inference Speed	100 tok/s (Lightning) / 50 tok/s (Standard)
Library	transformers

Benchmarks

Category	Base (FP8/vLLM)	PRISM-PRO Q8_0 (llama.cpp)
MMLU 5-shot	28/30 (93.3%)	28/30 (93.3%)
General Knowledge	5/5	5/5
Coding	4/5	5/5
Reasoning	5/5	5/5
Agentic	3/5	5/5
Harmful bypass	3/10	10/10 (100%)
Avg thinking words	163w	152w
Speed	72 t/s	35-65 t/s

Coding

Benchmark	MiniMax-M2.5	Claude Opus 4.6	Gemini 3 Pro	GPT-5.2
SWE-Bench Verified	80.2	78.9	74.0	72.6
Multi-SWE-Bench	51.3	50.8	—	—
SWE-Bench Multilingual	55.6	—	—	—
Terminal-Bench 2.0	51.5	52.1	—	—

Search & Tool Calling

Benchmark	MiniMax-M2.5	Claude Opus 4.6	Gemini 3 Pro	GPT-5.2
BrowseComp	76.3	71.2	62.4	57.8

Reasoning & Knowledge

Benchmark	MiniMax-M2.5	Claude Opus 4.6	Gemini 3 Pro	GPT-5.2
AIME25	86.3	95.6	96.0	98.0
GPQA-D	85.2	90.0	91.0	90.0
HLE w/o tools	19.4	30.7	37.2	31.4
SciCode	44.4	52.0	56.0	52.0
IFBench	70.0	53.0	70.0	75.0

Usage

llama.cpp (GGUF)

Build the latest master of llama.cpp and run:

~/llama.cpp/build/bin/llama-cli \
  -m ../outputs/MiniMax-M2.5-PRISM-PRO-[QUANT].gguf \
  --jinja \
  -ngl 999 \
  --repeat_penalty 1.15 \
  --temp 1.0 \
  --top_p 0.95 \
  --top_k 40

Replace [QUANT] with your quantization level (e.g. Q8_0, etc.).

Recommended Parameters

Use Case	Temperature	Top-P	Top-K	Repeat Penalty	Max New Tokens
Reasoning / Coding	1.0	0.95	40	1.15	32768
General Chat	0.6	0.95	40	1.15	4096
Agentic / Tool Use	1.0	0.95	40	1.15	32768

Version	Description	Access
PRISM-LITE	Abliterated with PRISM-LITE pipeline — removes over-refusal while preserving core capabilities	Free on Hugging Face
PRISM-PRO	Full PRISM-PRO ablation — Full Production Level Mode suppression of propaganda/refusal mechanisms with maximum capability retention	Ko-fi

License

This model is released under the PRISM Research License.

The base model MiniMax-M2.5 is released under a Modified-MIT License.

Acknowledgments

Based on MiniMax-M2.5 by MiniMax AI.