Model reference · open weights

INTELLECT-3.1

LLMs PrimeIntellect Text gen 1 build Open weights 740 dl/mo

INTELLECT-3.1 is an open-weight language model from PrimeIntellect. INTELLECT-3.1 (BF16) weighs 214 GB; the smallest configuration that runs it is 2× H200 141 GB.

  • INTELLECT-3.1 is a 106.9B parameter Mixture-of-Experts reasoning model developed by PrimeIntellect for text generation.
  • It is a continued training of INTELLECT-3 that incorporates additional reinforcement learning for math, coding, software engineering, and agentic tasks.
  • The model supports a context length of 131,072 tokens, operates in English, and is released under the MIT license.

Summary of the PrimeIntellect/INTELLECT-3.1 model card, 2026-10-01

What it is

Released byPrimeIntellect
Released2026-01-20
Parameters106.9B
VRAM214 GB for the weights

What it runs on

Memory and cards for INTELLECT-3.1 (BF16)

214 GBweights, file size
188 MBcache per 1K tokens
1.7 GBruntime overhead, at least
131,072 tokenscontext max
CardRequests at onceContext maxMemory
8K each32K each
RTX 3060 12 GB … B200 180 GB
12 smaller cards
———
2× H200 141 GB
tensor parallel
287all 128K138 GB a card
4× H100 80 GB
tensor parallel
4110all 128K78.1 GB a card
4× A100 80 GB
tensor parallel
5914all 128K78.2 GB a card
2× B200 180 GB
tensor parallel
7218all 128K176 GB a card
4× RTX PRO 6000 Blackwell 96 GB
tensor parallel
8220all 128K93.8 GB a card
Memory needed at each load
Requests at once8K tokens each32K tokens each
1217 GB222 GB
5223 GB246 GB
8228 GB265 GB
16240 GB314 GB
32265 GB413 GB
64314 GB611 GB

One card, with vLLM's small-card settings.

From the model card

What PrimeIntellect says about INTELLECT-3.1

Read the model card

Trained with prime-rl and verifiers Environments released on Environments Hub Read the Blog & Technical Report

Introduction

INTELLECT-3.1 is a 106B (A12B) parameter Mixture-of-Experts reasoning model built as a continued training of INTELLECT-3 with additional reinforcement learning on math, coding, software engineering, and agentic tasks.

Training was performed with prime-rl using environments built with the verifiers library. All training and evaluation environments are available on the Environments Hub.

The model, training frameworks, and environments are open-sourced under fully-permissive licenses (MIT and Apache 2.0).

For more details, see the technical report.

Serving with vLLM

The model can be served on 2x H200s:

vllm serve PrimeIntellect/INTELLECT-3.1 \
    --tensor-parallel-size 2 \
    --enable-auto-tool-choice \
    --tool-call-parser qwen3_coder \
    --reasoning-parser deepseek_r1

Citation

@misc{intellect3.1,
  title={INTELLECT-3.1: Technical Report},
  author={Prime Intellect Team},
  year={2025},
  url={https://huggingface.co/PrimeIntellect/INTELLECT-3.1}
}

Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.

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