AI21 Labs’ Jamba 1.5 stands out as a pioneering hybrid model that combines transformer and state space model (SSM) architectures for exceptional efficiency and performance. Released on August 22, 2024, the Jamba 1.5 family includes Jamba 1.5 Mini and Jamba 1.5 Large, designed to handle long-context tasks with speed and precision. As of January 2026, while newer iterations like Jamba 1.6 and 1.7 have emerged, Jamba 1.5 remains a benchmark for open-source models in enterprise applications.
What is Jamba 1.5 from AI21 Labs?
Jamba 1.5 is AI21 Labs’ open-source family of large language models, introducing a hybrid SSM-transformer architecture with mixture-of-experts (MoE) elements. This design addresses limitations in traditional transformers, such as high memory usage for long contexts. The family includes two variants: Mini for efficient, lightweight tasks and Large for demanding enterprise workflows.
For beginners: Jamba 1.5 is like a versatile AI assistant that processes vast amounts of information quickly—think summarizing a book or analyzing reports—without needing massive hardware.
For advanced users: Jamba 1.5 Mini has 52 billion total parameters (12B active), while Large boasts 398B total (94B active). The hybrid setup interleaves SSM layers for efficient sequence modeling with transformer attention for reasoning, supporting a 256K token context window—the longest in open models at launch. This covers queries like “Jamba 1.5 AI21 explained” or “Jamba 1.5 architecture.”
Features of Jamba 1.5 Mini and Large
Jamba 1.5 excels in speed, context handling, and enterprise tools, making it a top choice for developers.
Beginner-Level Features
- Long Context Window: Processes up to 256K tokens, ideal for handling entire documents or conversations without losing details.
- High Speed: Up to 2.5 times faster than comparable models on long inputs, reducing wait times for responses.
- Open-Source Availability: Free to download and customize under Apache 2.0, with support for function calling and structured outputs like JSON.
Advanced-Level Features
- Hybrid Architecture: Combines SSM for low-memory efficiency with MoE for selective parameter activation, enabling deployment on single GPU nodes.
- Business Optimizations: Native support for grounded generation (citations), tool use, and RAG workflows.
- Multilingual and Multimodal: Handles diverse languages and integrates with vision tasks in later variants.
| Feature | Jamba 1.5 Mini | Jamba 1.5 Large |
|---|---|---|
| Parameters | 52B total (12B active) | 398B total (94B active) |
| Context Window | 256K tokens | 256K tokens |
| Speed Advantage | 2.5x faster on long contexts | High-throughput for complex tasks |
| Best For | Cost-effective apps | Enterprise-scale reasoning |
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Jamba 1.5 Release Date and Updates
Jamba 1.5 was released on August 22, 2024, following the original Jamba in March 2024. Key 2025 updates include Jamba 1.6 on March 6, 2025, for enhanced private deployments, and Jamba Reasoning 3B on October 8, 2025, a 3B model with 2-4x efficiency gains. Jamba 1.7 followed in July 2025, building on the hybrid design. As of January 2026, these evolutions maintain Jamba 1.5’s core strengths while adding agentic features.
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How to Access Jamba 1.5
Access is straightforward across platforms:
- Hugging Face: Download weights for Mini and Large models.
- Cloud Services: Available on AWS Bedrock, Google Vertex AI, Microsoft Azure, and NVIDIA API catalog.
- AI21 Studio: Web-based interface for testing and API integration.
- Self-Hosting: Optimized for NVIDIA GPUs or edge devices.
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Jamba 1.5 vs Other Models: Benchmarks and Comparisons
Jamba 1.5 outperforms peers in efficiency and long-context tasks.
- vs Llama 3.1: Jamba 1.5 Large scores 65.4 on Arena Hard, surpassing Llama 3.1 405B; Mini beats Llama 3.1 70B in speed.
- vs Mistral Models: 10x more memory-efficient than Mistral equivalents.
| Model | Arena Hard Score | Context Window |
|---|---|---|
| Jamba 1.5 Mini | 46.1 | 256K |
| Jamba 1.5 Large | 65.4 | 256K |
| Llama 3.1 70B | Lower | 128K |
| Mixtral 8x22B | Lower | Shorter |
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Real-World Use Cases for Jamba 1.5
Jamba 1.5 powers practical applications:
- Beginner: Summarizing long articles or generating content in AI21 Studio.
- Intermediate: Customer support chatbots handling multilingual queries.
- Advanced: RAG for financial analysis or agentic workflows in compliance.
Examples include document comparison in retail or insight extraction in research. This answers “Jamba 1.5 use cases” or “Jamba 1.5 real-world examples.”
Latest Updates and Future Developments
In 2025, AI21 released Jamba 1.6 for enterprise privacy and Jamba Reasoning 3B for on-device efficiency. As of January 2026, integrations with NVIDIA NIM continue, with focus on hybrid advancements.
For “Jamba 1.5 latest news 2026.”
Beginner to Advanced: Tips for Using Jamba 1.5
- Beginners: Test prompts in AI21 Studio for quick results.
- Intermediate: Integrate via API for apps like summarization.
- Advanced: Fine-tune on Hugging Face for custom RAG systems.
FAQ
When was Jamba 1.5 released?
August 22, 2024, with Mini and Large variants available immediately.
What are the features of Jamba 1.5?
Hybrid SSM-transformer architecture, 256K context, up to 2.5x speed, and support for function calling and structured outputs.
How does Jamba 1.5 compare to Llama 3.1?
Jamba 1.5 Large outperforms Llama 3.1 405B on Arena Hard, with longer context and better efficiency.
How to access Jamba 1.5 models?
Download from Hugging Face or use via AWS Bedrock, Azure, or Google Vertex AI.
What are Jamba 1.5 benchmarks?
Mini: 46.1 Arena Hard; Large: 65.4, leading in long-context evaluations.
Can Jamba 1.5 handle long-context tasks?
Yes, with a 256K token window, it’s optimized for document analysis and RAG.