Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Jamba stands out as the most potent and effective long context model, specifically designed for builders while catering to enterprise needs. With superior latency compared to other leading models of similar sizes, Jamba boasts a remarkable 256k context window, the longest that is openly accessible. Its innovative Mamba-Transformer MoE architecture focuses on maximizing cost-effectiveness and efficiency. Key features available out of the box include function calls, JSON mode output, document objects, and citation mode, all designed to enhance user experience. Jamba 1.5 models deliver exceptional performance throughout their extensive context window and consistently achieve high scores on various quality benchmarks. Enterprises can benefit from secure deployment options tailored to their unique requirements, allowing for seamless integration into existing systems. Jamba can be easily accessed on our robust SaaS platform, while deployment options extend to strategic partners, ensuring flexibility for users. For organizations with specialized needs, we provide dedicated management and continuous pre-training, ensuring that every client can leverage Jamba’s capabilities to the fullest. This adaptability makes Jamba a prime choice for enterprises looking for cutting-edge solutions.

Description

Qwen2.5-1M, an open-source language model from the Qwen team, has been meticulously crafted to manage context lengths reaching as high as one million tokens. This version introduces two distinct model variants, namely Qwen2.5-7B-Instruct-1M and Qwen2.5-14B-Instruct-1M, representing a significant advancement as it is the first instance of Qwen models being enhanced to accommodate such large context lengths. In addition to this, the team has released an inference framework that is based on vLLM and incorporates sparse attention mechanisms, which greatly enhance the processing speed for 1M-token inputs, achieving improvements between three to seven times. A detailed technical report accompanies this release, providing in-depth insights into the design choices and the results from various ablation studies. This transparency allows users to fully understand the capabilities and underlying technology of the models.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Hugging Face
Alibaba Cloud
Amazon Web Services (AWS)
Azure Databricks
C
C#
F#
Go
Google Cloud Platform
HTML
JavaScript
Julia
LM-Kit.NET
LlamaIndex
ModelScope
PHP
SQL
Snowflake
Streamlit
Visual Basic

Integrations

Hugging Face
Alibaba Cloud
Amazon Web Services (AWS)
Azure Databricks
C
C#
F#
Go
Google Cloud Platform
HTML
JavaScript
Julia
LM-Kit.NET
LlamaIndex
ModelScope
PHP
SQL
Snowflake
Streamlit
Visual Basic

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

AI21 Labs

Country

Israel

Website

www.ai21.com/jamba

Vendor Details

Company Name

Alibaba

Founded

1999

Country

China

Website

qwenlm.github.io/blog/qwen2.5-1m/

Product Features

Product Features

Alternatives

Codestral Mamba Reviews

Codestral Mamba

Mistral AI

Alternatives

Qwen2.5-Max Reviews

Qwen2.5-Max

Alibaba
Mistral NeMo Reviews

Mistral NeMo

Mistral AI
Qwen3.5-Plus Reviews

Qwen3.5-Plus

Alibaba
CodeQwen Reviews

CodeQwen

Alibaba