README.md

---
license: mit
language:
- en
- ru
tags:
- text-generation
- agent
- long-context
- code
- security
- made-by-bleyzos
pipeline_tag: text-generation
---

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    <img src="https://cdn.bleyzos.ru/brand.png" width="60%" alt="Bleyzos Coder" />
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  <strong>Community</strong><br/>
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# 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](https://huggingface.co/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