Models

Rnj-1 is a family of 8B parameter open-weight, dense models trained from scratch by Essential AI, optimized for code and STEM with capabilities on par with SOTA open-weight models.

A fine-tuned version of Deepseek-R1-Distilled-Qwen-1.5B that surpasses the performance of OpenAI’s o1-preview with just 1.5B parameters on popular math evaluations.

Next-Gen Sovereign AI Ecosystem - 7 specialized models for Coding, Vision, Reasoning, Edge & RAG. 131K context, 11 Stop Tokens. Native with OpenClaw, VSCode, Cursor, LangChain & 12+ platforms. Forged by NJIRLAH.

The 4th Evolutionary Leap of NJIR.AI Sovereign Intelligence. A closed-ecosystem swarm of 11 proprietary nodes mastering autonomous coding, multilingual logic, edge-compute, and database architecture.

Ling-3.0-tiny is a lightweight 7.9B-parameter hybrid reasoning MoE with just 1.3B active parameters per token, offering strong reasoning and agentic capabilities at low inference cost.

s1 is a reasoning model finetuned from Qwen2.5-32B-Instruct on just 1,000 examples. It matches o1-preview & exhibits test-time scaling via budget forcing.

s1 is a reasoning model finetuned from Qwen2.5-32B-Instruct on just 1,000 examples. It matches o1-preview & exhibits test-time scaling via budget forcing.

a reasoning model finetuned from Qwen2.5-32B-Instruct on just 1,000 examples. It matches o1-preview & exhibits test-time scaling via budget forcing. available in [F16, q8_0, q6_K, q4_K_S]