What are the key features of Jamba 1.5 Large's hybrid SSM-Transformer architecture?
Jamba 1.5 Large utilizes a hybrid SSM-Transformer architecture that combines speed with superior long-context handling capabilities, allowing it to efficiently manage extensive inputs while maintaining high performance.

How does Jamba 1.5 Large handle long-context tasks?
It excels at long-context tasks with a maximum context length of 256,000 tokens, enabling it to process extensive information effectively without losing coherence.

What is the inference speed of Jamba 1.5 Large compared to similar models?
Jamba 1.5 Large delivers up to 2.5 times faster inference than comparable models, making it highly efficient for real-time applications.