Average Ratings 0 Ratings
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
Qwen3.5-Plus is an advanced multimodal foundation model engineered to deliver efficient large-context reasoning across text, image, and video inputs. Powered by a hybrid architecture that merges linear attention mechanisms with a sparse mixture-of-experts framework, the model achieves state-of-the-art performance while reducing computational overhead. It supports deep thinking mode, enabling extended reasoning chains of up to 80K tokens and total context windows of up to 1 million tokens. Developers can leverage features such as structured output generation, function calling, web search, and integrated code interpretation to build intelligent agent workflows. The model is optimized for high throughput, supporting large token-per-minute limits and robust rate limits for enterprise-scale applications. Qwen3.5-Plus also includes explicit caching options to reduce costs during repeated inference tasks. With tiered pricing based on input and output tokens, organizations can scale usage predictably. OpenAI-compatible API endpoints make integration straightforward across existing AI stacks and developer tools. Designed for demanding applications, Qwen3.5-Plus excels in long-document analysis, multimodal reasoning, and advanced AI agent development.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Alibaba AI Coding Plan
No
Alibaba Cloud Model Studio
No
OpenClaw
No
Qwen3.5
No
Shiori
No
Tabbit Browser
No
Integrations
Alibaba AI Coding Plan
Yes
Alibaba Cloud Model Studio
Yes
OpenClaw
Yes
Qwen3.5
Yes
Shiori
Yes
Tabbit Browser
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0.4 per 1M tokens
Input: $0.4 per 1M tokens
Output: $2.4 per 1M tokens
Output: $2.4 per 1M tokens
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)
No
Online Support
No
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)
No
In Person
No
Vendor Details
Company Name
Reflection
Country
United States
Website
reflection.ai/blog/introducing-beam
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai