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Average Ratings 0 Ratings
Description
Beam represents Reflection’s inaugural open-weight model, characterized as a sparse Mixture-of-Experts framework featuring a staggering 501 billion parameters, of which 23 billion are actively utilized, specifically crafted for tasks involving coding, reasoning, and agentic functions. Its prowess is derived from extensive pretraining and reinforcement learning, having been developed using a vast dataset of 23.8 trillion diverse, high-quality tokens sourced from the web, public domains, and proprietary licensed materials. With a targeted emphasis on enhancing coding and agentic capabilities, Beam is engineered to provide competitive open-weight performance while ensuring efficient inference compute. This model adeptly handles a wide array of tasks, including intricate software engineering, terminal operations, STEM activities, web searches, tool utilization, and general knowledge inquiries. Reinforcement learning techniques have been employed to bolster its abilities in multi-step reasoning, tool application, and responsiveness to environmental feedback. Moreover, users have the flexibility to manage the balance between efficiency and performance through an adjustable reasoning effort parameter, thus tailoring the model's output to better suit their specific needs.
Description
Sarvam-M is an advanced, multilingual large language model that integrates hybrid reasoning to excel in various Indian languages, mathematical tasks, and programming challenges all within a single, streamlined framework. It is built on the foundation of Mistral-Small, boasting a robust architecture with 24 billion parameters, which has been refined through supervised fine-tuning, reinforcement learning with clear rewards, and optimizations for inference to enhance both precision and efficiency. This model is meticulously trained to proficiently handle over ten prominent Indic languages, accommodating native scripts, romanized text, and code-mixed submissions, thereby facilitating smooth multilingual interactions in a variety of linguistic environments. Moreover, Sarvam-M adopts a hybrid reasoning framework, enabling it to alternate between an in-depth “thinking” mode for intricate tasks such as mathematics, logic puzzles, and programming, and a rapid response mode for everyday inquiries, providing an effective balance between speed and performance. This versatility makes Sarvam-M an invaluable tool for users looking to engage with technology in an increasingly diverse linguistic landscape.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Sarvam AI
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Reflection
Country
United States
Website
reflection.ai/blog/introducing-beam
Vendor Details
Company Name
Sarvam
Founded
2023
Country
India
Website
www.sarvam.ai/blogs/sarvam-m