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
Inkling 2 Small is a general-purpose multimodal AI model developed by Thinking Machines Lab for software engineering, advanced reasoning, visual analysis, and autonomous agent applications. The model features a sparse mixture-of-experts architecture containing 594 billion total parameters, with approximately 17 billion parameters activated during inference. Its one-million-token context window supports processing large documents, software repositories, extended conversations, and complex collections of information. Inkling 2 Small accepts text and image inputs and generates text outputs, enabling visual reasoning, programming assistance, document analysis, and multimodal problem-solving. Its agentic coding capabilities support autonomous software development, code debugging, repository modifications, application creation, and verification of completed engineering tasks. The model can also perform extended research workflows involving machine learning experimentation, GPU kernel optimization, data analysis, and iterative scientific problem-solving. Configurable reasoning effort allows users to balance response speed and computational resources against the complexity of individual tasks. Thinking Machines Lab reports benchmark scores of 25.4% on FrontierCode 2.0, 72.1% on DeepSWE 1.1, and 86.3% on SWE-Bench Pro v2 Hard. Inkling 2 Small is available for inference and fine-tuning through Tinker, with model weights scheduled for release under the Apache 2.0 license after additional safety evaluations.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Model Context Protocol (MCP)
No
Tinker
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0.30 per million input tokens
$0.30 per million input tokens, $0.03 per million cached input tokens, and $1.00 per million output 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
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)
No
In Person
No
Vendor Details
Company Name
Reflection
Country
United States
Website
reflection.ai/blog/introducing-beam
Vendor Details
Company Name
Thinking Machines Lab
Founded
2025
Country
United States
Website
thinkingmachines.ai/