Activefastllm Proprietary

Jamba 1.5 Mini

by AI21 Labs· Released August 2024· Cutoff March 2024

Jamba 1.5 Mini is a lightweight, efficient large language model from AI21 Labs, designed for high-speed inference and cost-effective deployment. It leverages a hybrid architecture combining Mamba (state space model) and Transformer components, achieving strong performance on a variety of tasks with a 256K token context window. As the smaller sibling of Jamba 1.5 Large, it offers a balance of speed and capability for production use cases.

Official Site API Docs 📄 Research Paper

Input cost

$0.20 per 1M tokens

Output cost

$0.80 per 1M tokens

Context window

256K tokens

Max output

4096 tokens

Modalities

text

License

proprietary

Capabilities

Function CallingCode GenerationStreamingJSON ModeStructured OutputMultilingual SupportLong Context Understanding

Best For

High-speed, cost-efficient text generation and understanding tasks with long context requirements.

Strengths

Extremely fast inference due to hybrid Mamba-Transformer architecture
Very large 256K token context window
Cost-effective pricing for high-volume applications
Strong performance on long-document tasks and code generation

Limitations

Smaller model size may limit performance on complex reasoning compared to larger models
No native vision or multimodal capabilities
Limited ecosystem and community compared to open-source alternatives
Proprietary license restricts modification and redistribution

Use Cases

Real-time chatbots and virtual assistants

Long-document summarization and analysis

Code generation and code review automation

Customer support ticket classification and response

Content generation for marketing and social media

Data extraction from large text corpora

Interactive storytelling and creative writing

Improvements Over Previous Model

Introduced as a new model family; no direct predecessor in the Jamba series
Hybrid Mamba-Transformer architecture for efficient long-context processing
256K token context window, significantly larger than typical models at launch
Optimized for low-latency inference suitable for real-time applications
Competitive pricing at $0.20/M input tokens, lower than many comparable models

Back to all models

Use Cases

Real-time chatbots and virtual assistants

Long-document summarization and analysis

Code generation and code review automation

Customer support ticket classification and response

Content generation for marketing and social media

Data extraction from large text corpora

Interactive storytelling and creative writing

Improvements Over Previous Model

Introduced as a new model family; no direct predecessor in the Jamba series

Hybrid Mamba-Transformer architecture for efficient long-context processing

256K token context window, significantly larger than typical models at launch

Optimized for low-latency inference suitable for real-time applications

Competitive pricing at $0.20/M input tokens, lower than many comparable models