INTELLECT-3: A 100B+ MoE trained with large-scale RL
Blog post from Prime Intellect
INTELLECT-3, a 100B+ parameter Mixture-of-Experts model, sets a new standard for its size in benchmarks across math, code, science, and reasoning, surpassing many larger models. Developed using an open-source reinforcement learning (RL) stack by Prime Intellect, it demonstrates the potential for any company to engage in AI development. Built on the GLM 4.5 Air base model, INTELLECT-3 utilizes PRIME-RL, an asynchronous RL framework, and various infrastructures like Prime Sandboxes and the Environments Hub, allowing for efficient, scalable training across 512 NVIDIA H200 GPUs. The model's training involved supervised fine-tuning and large-scale RL, leveraging a diverse set of publicly available environments to enhance its reasoning and agentic capabilities. With resources and frameworks like prime-rl and verifiers open-sourced, Prime Intellect aims to democratize AI by enabling broader participation and innovation in the field, moving towards a future where AI development is accessible to all.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| AI Model Fine-tuning | 3 | 470 | 151 | 72 | -14% |
| Kubernetes | 3 | 1,493 | 255 | 93 | -18% |
| Reinforcement learning | 3 | 300 | 58 | 32 | +165% |
| LLM | 1 | 5,048 | 855 | 225 | +5% |
| Observability | 1 | 3,012 | 601 | 171 | +15% |
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