Modelpublic

Mini-Bleyz/Bleyzos-Coder

sourceHugging Facemitupdated 4mo agoView on Hugging Face

0likes331downloads

Model Card

<br/>

<div align="center" style="line-height: 1.2;"> <strong>Community</strong><br/> <a href="https://t.me/bleyzos" target="_blank">Telegram</a> </div>

<br/>

Bleyzos Coder

Bleyzos Coder is an open-source Mixture-of-Experts (MoE) language model with 1.02T total parameters and 42B active parameters. Built on a fork of MiMo-V2.5-Pro, fine-tuned for coding, cybersecurity, and agentic workflows. Supports up to 1M tokens context length.

Model Details

—Developer: Bleyzos AI (https://bleyzos.com)
—Architecture: Mixture-of-Experts (MoE) with Hybrid Attention (SWA + GA)
—Total Parameters: 1.02T
—Active Parameters: 42B
—Context Length: Up to 1M tokens
—License: MIT

Key Features

—Hybrid Attention: Sliding Window Attention + Global Attention (6:1 ratio), reduces KV-cache by ~7x
—Multi-Token Prediction: 3 MTP layers for 3x faster inference
—Long Context: Up to 1M tokens — feed entire codebases
—Agentic: Post-trained with SFT + RL + Multi-Teacher Distillation for complex multi-step tasks
—Security-First: Built-in filters against prompt injection and data leaks

Usage

Hugging Face Inference API

python

from huggingface_hub import InferenceClient

client = InferenceClient(model="Mini-Bleyz/Bleyzos-Coder")

response = client.chat_completion(
    messages=[{"role": "user", "content": "Write a Python function to reverse a linked list"}],
    max_tokens=512
)

print(response["choices"][0]["message"]["content"])

SGLang Deployment (for GPU servers)

bash

python3 -m sglang.launch_server \
    --model-path Mini-Bleyz/Bleyzos-Coder \
    --trust-remote-code \
    --tp 8 \
    --ep 8 \
    --context-length 1048576 \
    --host 0.0.0.0 \
    --port 9001

Benchmarks

Benchmark	Bleyzos Coder	MiMo-V2.5-Pro
BBH (3-shot)	89.1	88.4
GSM8K (8-shot)	99.8	99.6
HumanEval+	78.3	75.6
SWE-Bench (AgentLess)	58.7	35.7
ClawEval pass³	65.2	63.8

Limitations

—Requires significant GPU memory (8×A100/H100 recommended for full model)
—GGUF quantized version available at DevQuasar/XiaomiMiMo.MiMo-V2.5-Pro-GGUF for CPU-only usage
—System prompt customized for Bleyzos AI identity

Citation

bibtex

@misc{bleyzos2026coder,
  title={Bleyzos Coder},
  author={{Bleyzos AI Team}},
  year={2026},
  howpublished={\url{https://huggingface.co/Mini-Bleyz/Bleyzos-Coder}},
}

Contact

—Email: support@bleyzos.ru
—Website: https://ai.bleyzos.com
—Telegram: https://t.me/bleyzos