Scaling Context, Not Parameters: Training a Compact 7B Language Model for Efficient Long-Context Processing

We present MegaBeam-Mistral-7B 1 , a language model that supports 512K-token context length.Our work addresses practical limitations in long-context training, supporting real-world tasks such as compliance monitoring and verification.Evaluated on three longcontext benchmarks, our 7B-parameter model demonstrates superior in-context learning performance on HELMET and robust retrieval and tracing capability on RULER.It is currently the only open model to achieve competitive longrange reasoning on BABILong at 512K context length without RAG or targeted fine-tuning.Released as fully open source under the Apache 2.0 license, the model has been downloaded over 100,000 times on Hugging Face.