LFM3

LFM3

Liquid AI
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About

GLM-5.3-Flash is Z.ai’s natively multimodal model in the GLM-5 series (previously previewed as Ox Alpha), designed to deliver strong coding, agentic, visual, and knowledge-work performance at relatively low inference cost. It uses 320 billion total parameters with 18 billion active parameters, along with a hybrid architecture that combines sparse and linear attention to reduce the cost of long-context processing. The model supports context lengths of up to one million tokens and was trained on a 30-trillion-token multimodal corpus. GLM-5.3-Flash can reason across text, images, documents, interfaces, dashboards, and other visual information while using that feedback to refine its own outputs. Z.ai reports substantial gains over GLM-5.2 on coding and agentic benchmarks, including DeepSWE and AutomationBench, while approaching higher-cost frontier models on several evaluations.

About

LFM3 is Liquid AI’s family of compact, open-weight foundation models for text, vision, audio, and multimodal tasks. The release includes text-generation, vision-language, audio, omni, and decision-model variants. Developers can download the model weights, adapt supported models through fine-tuning, and run them locally on edge hardware or access them through Liquid AI’s hosted API. Use cases include conversational assistants, tool calling, speech transcription and generation, image and video understanding, document extraction, classification, routing, and robotics applications. LFM3 is intended for developers, researchers, and organizations building specialized AI applications that need flexible deployment choices, including local inference. Open-weight models are available under Liquid AI’s LFM Open License; commercial eligibility and terms depend on an organization’s annual revenue.

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

Platforms Supported

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

Audience

Developers, AI engineers, agent builders, researchers, and organizations that need cost-efficient multimodal reasoning, long-context processing, advanced coding, visual analysis, and autonomous workflow capabilities

Audience

Developers, AI researchers, and organizations building specialized AI applications, including applications using local or edge inference.

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 Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$0.15 per 1M tokens (input)
Input: $0.15 per 1M tokens
Output: $0.50 per 1M tokens
Cached input: $0.03 per 1M tokens
Free Version Not Supported
Free Trial Not Supported

Pricing

$0.08/MTok
LFM3-1.7B API usage is $0.08 per million input tokens, $0.02 per million cached input tokens, and $0.20 per million output tokens. New organizations receive $2 in API credit. Open-weight models can be used in production free by developers, researchers, nonprofits, and businesses with less than $10 million in annual revenue; businesses above that threshold require a paid license.
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

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

Pros & Cons from Real Users

Pros

  • What makes it exciting is that it seems built for the exact workloads developers care about right now: long-horizon coding, complex reasoning, big-context analysis, and agentic workflows. A million-token context window is especially useful if you want to drop in a large repo, long spec, research corpus, or messy project history and have the model reason across it.

Cons

  • I would treat it as something exciting to test, not something to blindly trust with sensitive work. Even the independent Ox Alpha site warns that messages are processed by the upstream model API, so I would keep secrets, private code, and customer data out of it until there is a clearer owner, model card, privacy policy, and production story.

Training

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

Training

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

Company Information

Z.ai
Founded: 2019
China
z.ai

Company Information

Liquid AI
Founded: 2023
United States
www.liquid.ai/blog/lfm3

Alternatives

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Qwen3.5

Qwen3.5

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MiniMax M3

MiniMax M3

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Inkling

Inkling

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Qwen3.5

Qwen3.5

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Qwen3.8-27B

Qwen3.8-27B

Alibaba

Categories

Categories

AI Coding Models Supported
AI Models Supported
Multimodal Models Supported

Integrations

OpenRouter Supported
Cheaper Inference Supported
Claude Code Supported
DeepSeek Harness Supported
GLM Coding Plan Supported
Hermes Agent Supported
Hugging Face Not Supported
Hugging Face Transformers Not Supported
LM Studio Not Supported
Ollama Not Supported
OpenClaw Supported
OpenCode Go Supported
OpenCode Zen Supported
Pi Agent Supported
Unsloth Not Supported
Vercel AI Gateway Not Supported
Z.ai Supported
omp Supported
vLLM Not Supported

Integrations

OpenRouter Supported
Cheaper Inference Not Supported
Claude Code Not Supported
DeepSeek Harness Not Supported
GLM Coding Plan Not Supported
Hermes Agent Not Supported
Hugging Face Supported
Hugging Face Transformers Supported
LM Studio Supported
Ollama Supported
OpenClaw Not Supported
OpenCode Go Not Supported
OpenCode Zen Not Supported
Pi Agent Not Supported
Unsloth Supported
Vercel AI Gateway Supported
Z.ai Not Supported
omp Not Supported
vLLM Supported
Claim GLM-5.3-Flash and update features and information
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