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Model Information

Jamba Large 1.7 offers new improvements to our Jamba open model family. This new version builds on the novel SSM-Transformer hybrid architecture, 256K context window, and efficiency gains of previous versions, while introducing improvements in grounding and instruction-following.

Key improvements:

• Grounding: Jamba Large 1.7 provides more complete and accurate answers, grounded fully in the given context.
• Instruction following: Jamba Large 1.7 improves on steerability.

Use cases

Jamba’s long context efficiency, contextual faithfulness, and steerability make it ideal for a variety of business applications and industries, such as:

• Finance: Investment research, digital banking support chatbot, M&A due diligence.
• Healthcare: Procurement (RFP creation & response review), medical publication and reports generation.
• Retail: Brand-aligned product description generation, conversational AI.
• Education & Research: Personalized chatbot tutor, grants applications.

The models are released under the Jamba Open Model License, a permissive license allowing full research use and commercial use under the license terms. If you need to license the model for your needs, talk to us.

Model Details

Developed by: AI21 Model type: Joint Attention and Mamba (Jamba) Model size: 94B active/398B total parameters License: Jamba Open Model License Context length: 256K Knowledge cutoff date: August 22, 2024 Supported languages: English, Spanish, French, Portuguese, Italian, Dutch, German, Arabic and Hebrew

Grounding and instruction-following improvements

Usage

Find step-by-step instructions on how to privately deploy Jamba:

You can also find all instructions in our private AI (vLLM) deployment guide.

And to get started with our SDK: AI21 Python SDK guide

Further documentation

For more comprehensive guides and advanced usage:

• Tokenization guide - Using ai21-tokenizer
• Quantization guide - ExpertsInt8, bitsandbytes
• Fine-tuning guide - LoRA, qLoRA, and full fine-tuning

For more resources to start building, visit our official documentation.

The AI21 Jamba family of models are hybrid SSM-Transformer foundation models, blending speed, efficient long context processing, and accuracy. • 4 items • Updated Jul 2, 2025 • 12