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README.md
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---
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library_name: transformers
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tags:
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- prime-rl
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- verifiers
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- prime-intellect
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license: mit
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language:
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- en
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base_model:
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- zai-org/GLM-4.5-Air-Base
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pipeline_tag: text-generation
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---
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# INTELLECT-3
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**INTELLECT-3** is a 100B+ parameter Mixture-of-Experts reasoning model post-trained from [GLM-4.5-Air-Base](https://huggingface.co/zai-org/GLM-4.5-Air-Base) using supervised fine-tuning (SFT) followed by large-scale reinforcement learning (RL).
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Training was performed with [prime-rl](https://github.com/PrimeIntellect-ai/prime-rl) using environments built with the [verifiers](https://github.com/PrimeIntellect-ai/verifiers) library. All training and evaluation environments are available on the [Environments Hub](https://app.primeintellect.ai/dashboard/environments).
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The model, training frameworks, and environments are open-sourced under fully-permissive licenses (MIT and Apache 2.0).
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For more details, see the [technical report](PAPER_LINK_PLACEHOLDER).
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## Evaluation
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INTELLECT-3 achieves best-in-class performance on math, coding, and reasoning benchmarks:
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| Benchmark | Score |
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|-----------|-------|
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| AIME 2025 | 88.0 |
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| LiveCodeBench v6 | 69.3 |
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| GPQA Diamond | 74.4 |
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| HLE | 14.6 |
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## Model Variants
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| Model | HuggingFace |
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|-------|-------------|
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| INTELLECT-3 | [PrimeIntellect/INTELLECT-3](https://huggingface.co/PrimeIntellect/INTELLECT-3) |
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| INTELLECT-3-FP8 | [PrimeIntellect/INTELLECT-3-FP8](https://huggingface.co/PrimeIntellect/INTELLECT-3-FP8) |
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## Serving with vLLM
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The BF16 version can be served on 2x H200s:
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```bash
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vllm serve PrimeIntellect/INTELLECT-3 \
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--tensor-parallel-size 2 \
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--tool-call-parser qwen3_coder \
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--reasoning-parser deepseek_r1
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```
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The FP8 version can be served on a single H200:
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```bash
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vllm serve PrimeIntellect/INTELLECT-3-FP8 \
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--tool-call-parser qwen3_coder \
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--reasoning-parser deepseek_r1
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```
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## Citation
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```bibtex
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@misc{intellect3,
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title={INTELLECT-3: Technical Report},
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author={Prime Intellect Team},
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year={2025},
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url={https://huggingface.co/PrimeIntellect/INTELLECT-3}
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}
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```
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