Beam

Beam

Reflection
Ling 3.0 Tiny

Ling 3.0 Tiny

Ant Group
+
+

Related Products

  • LTX
    182 Ratings
    Visit Website
  • Cloverleaf
    189 Ratings
    Visit Website
  • Portfolio Manager
    3 Ratings
    Visit Website
  • Interfacing Integrated Management System (IMS)
    66 Ratings
    Visit Website
  • GWI
    201 Ratings
    Visit Website
  • InEight
    168 Ratings
    Visit Website
  • JetBrains Junie
    12 Ratings
    Visit Website
  • Runpod
    230 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • Dialpad Support
    1,600 Ratings
    Visit Website

About

Beam is Reflection’s first open-weight model, a sparse Mixture-of-Experts model with 501 billion total parameters and 23 billion active parameters, built for coding, reasoning, and agentic workloads. Its capabilities come from large-scale pretraining and reinforcement learning, including training on 23.8 trillion diverse, curated, high-quality tokens from the web, public sources, and proprietary licensed datasets. Beam was trained with a particular focus on coding and agentic performance and is designed to deliver competitive open-weight capabilities with efficient inference compute. It supports complex software engineering, terminal, STEM, web search, tool-use, and general knowledge tasks, with reinforcement learning designed to improve multi-step reasoning, tool use, and adaptation to environment feedback. Users can control the tradeoff between performance and token usage through a reasoning effort parameter.

About

Ling 3.0 Tiny is an open-weights reasoning model with 7.9B total parameters, 1.3B active parameters, and a 262K-token context window. Built with a mixture-of-experts architecture, it extends the open-weights Pareto frontier for intelligence versus active parameters and is small enough to run locally in many settings. The model scores 25 on the Artificial Analysis Intelligence Index, comparable to gpt-oss-120b (high, 24) while using 15x fewer total parameters and 4x fewer active parameters. This parameter efficiency comes with relatively high token usage, with 213M output tokens required to run the Intelligence Index. Ling 3.0 Tiny also shows substantial improvements in hallucination behavior over Ling-mini-2.0, improving its AA-Omniscience score by 59 points while maintaining similar accuracy. Rather than guessing when uncertain, it attempted only 37% of questions in the evaluation, resulting in a 30% hallucination rate compared with 96% for the previous generation.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers, AI researchers, and engineering teams requiring a tool to run coding, reasoning, tool-use, and agentic workloads with an efficient open-weight language model

Audience

AI developers, researchers, and teams seeking to run, evaluate, customize, or integrate a compact open-weights reasoning model with long-context and tool-use capabilities

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Reflection
United States
reflection.ai/blog/introducing-beam

Company Information

Ant Group
Founded: 2014
China
ant-ling.com

Alternatives

GLM-5.3

GLM-5.3

Z.ai

Alternatives

GLM-5.2

GLM-5.2

Z.ai
Kimi K3

Kimi K3

Moonshot AI
Kimi K3

Kimi K3

Moonshot AI
Qwen3.8-Max

Qwen3.8-Max

Alibaba
Qwen3.8-Max

Qwen3.8-Max

Alibaba
Inkling

Inkling

Thinking Machines Lab
Ling 2.6 Flash

Ling 2.6 Flash

Ant Group
Qwen3.5

Qwen3.5

Alibaba
Ling 3.0 Flash

Ling 3.0 Flash

Ant Group

Categories

AI Models Supported

Categories

AI Models Supported

Integrations

Claude Code Not Supported
Hermes Agent Not Supported
Kilo Code Not Supported
OpenClaw Not Supported
OpenRouter Not Supported
ZenMux Not Supported

Integrations

Claude Code Supported
Hermes Agent Supported
Kilo Code Supported
OpenClaw Supported
OpenRouter Supported
ZenMux Supported
Claim Beam and update features and information
Claim Beam and update features and information
Claim Ling 3.0 Tiny and update features and information
Claim Ling 3.0 Tiny and update features and information