README.md

---
license: other
license_name: prism-research
license_link: LICENSE.md
language:
- en
- zh
tags:
- glm4
- prism
- moe
pipeline_tag: text-generation
library_name: transformers
---

[![Parameters](https://img.shields.io/badge/Parameters-30B--A3B_MoE-blue)]()
[![Architecture](https://img.shields.io/badge/Architecture-GLM--4.7-green)]()
[![Context](https://img.shields.io/badge/Context-128K-orange)]()

# GLM-4.7-Flash-PRISM

An over-refusal/propaganda free version of [ZAI's GLM-4.7-Flash](https://huggingface.co/zai-org/GLM-4.7-Flash) with over-refusal and bias mechanisms completely removed using our Advanced PRISM Pipeline.

<div align="center">

### ☕ Support Our Work

If you find this model useful, consider supporting us on Ko-fi!

[![Ko-fi](https://img.shields.io/badge/Ko--fi-Support%20Us-ff5e5b?logo=ko-fi&logoColor=white)](https://ko-fi.com/ericelbaz)

| Option | Description |
|--------|-------------|
| [**PRISM VIP Membership**](https://ko-fi.com/summary/6bae206c-a751-4868-8dc7-f531afd1fb4c) | Access to all PRISM models |
| [**One-Time Support**](https://ko-fi.com/s/86882e8991) | Support this model |

</div>

---

## Model Highlights

- **PRISM Ablation** — State-of-the-art technique that removes over-refusal behaviors while preserving model capabilities
- **30B-A3B MoE Architecture** — 30 billion total parameters with ~3 billion active per token for fast, efficient inference
- **128K Context Window** — Extended context for complex tasks and large codebases
- **Interleaved Thinking** — Multi-turn reasoning that persists across conversations with per-turn thinking control

## Benchmarks

| Benchmark | GLM-4.7-Flash | Qwen3-30B-A3B-Thinking-2507 | GPT-OSS-20B |
|-----------|---------------|-----------------------------| ------------|
| AIME 2025 | 91.6 | 85.0 | 91.7 |
| GPQA | 75.2 | 73.4 | 71.5 |
| LCB v6 | 64.0 | 66.0 | 61.0 |
| HLE | 14.4 | 9.8 | 10.9 |
| SWE-bench Verified | 59.2 | 22.0 | 34.0 |
| τ²-Bench | 79.5 | 49.0 | 47.7 |
| BrowseComp | 42.8 | 2.29 | 28.3 |

## Usage

### Transformers

Install the latest transformers from source:

```shell
pip install git+https://github.com/huggingface/transformers.git
```

Run inference:

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

MODEL_PATH = "Ex0bit/GLM-4.7-Flash-PRISM"

tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_PATH,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

messages = [{"role": "user", "content": "Hello!"}]
inputs = tokenizer.apply_chat_template(
    messages,
    tokenize=True,
    add_generation_prompt=True,
    return_dict=True,
    return_tensors="pt",
).to(model.device)

generated_ids = model.generate(**inputs, max_new_tokens=128, do_sample=False)
output_text = tokenizer.decode(generated_ids[0][inputs.input_ids.shape[1]:])
print(output_text)
```

### vLLM

Install vLLM nightly:

```shell
pip install -U vllm --pre --index-url https://pypi.org/simple --extra-index-url https://wheels.vllm.ai/nightly
pip install git+https://github.com/huggingface/transformers.git
```

Serve the model:

```shell
vllm serve Ex0bit/GLM-4.7-Flash-PRISM \
     --tensor-parallel-size 4 \
     --speculative-config.method mtp \
     --speculative-config.num_speculative_tokens 1 \
     --tool-call-parser glm47 \
     --reasoning-parser glm45 \
     --enable-auto-tool-choice \
     --served-model-name glm-4.7-flash-prism
```

### SGLang

Install SGLang:

```shell
uv pip install sglang==0.3.2.dev9039+pr-17247.g90c446848 --extra-index-url https://sgl-project.github.io/whl/pr/
uv pip install git+https://github.com/huggingface/transformers.git@76732b4e7120808ff989edbd16401f61fa6a0afa
```

Launch the server:

```shell
python3 -m sglang.launch_server \
  --model-path Ex0bit/GLM-4.7-Flash-PRISM \
  --tp-size 4 \
  --tool-call-parser glm47  \
  --reasoning-parser glm45 \
  --speculative-algorithm EAGLE \
  --speculative-num-steps 3 \
  --speculative-eagle-topk 1 \
  --speculative-num-draft-tokens 4 \
  --mem-fraction-static 0.8 \
  --served-model-name glm-4.7-flash-prism \
  --host 0.0.0.0 \
  --port 8000
```

> **Note:** For Blackwell GPUs, add `--attention-backend triton --speculative-draft-attention-backend triton` to your SGLang launch command.

## Recommended Parameters

| Use Case | Temperature | Top-P | Max New Tokens |
|----------|-------------|-------|----------------|
| Default | 1.0 | 0.95 | 131072 |
| Code (SWE-bench) | 0.7 | 1.0 | 16384 |
| Agentic Tasks | 0.0 | — | 16384 |

## License

This model is released under the [PRISM Research License](LICENSE.md).

## Citation

```bibtex
@misc{elbaz2026glm47flashPrism,
  author = {Elbaz, Eric},
  title = {Elbaz-GLM-4.7-Flash-PRISM: Unchained GLM-4.7-Flash-PRISM Model},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/Ex0bit/Elbaz-GLM-4.7-Flash-PRISM}}
}
```

## Acknowledgments

Based on [GLM-4.7-Flash](https://huggingface.co/zai-org/GLM-4.7-Flash) by [Z.AI](https://z.ai). See the [technical report](https://arxiv.org/abs/2508.06471) for more details on the base model.