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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Celeris-1 stands out as a swift and versatile language model platform, complemented by a diffusion model that achieves cutting-edge intelligence at unprecedented speeds. Unlike conventional autoregressive models that generate tokens sequentially, Celeris employs a diffusion-based inference architecture that allows for simultaneous generation, resulting in response times that can be measured in mere milliseconds. On the MMLU-Pro benchmark, Celeris-1 boasts an impressive accuracy of 75.9% while achieving a median response time of 158 milliseconds and producing an astonishing 1,664 output tokens per second, positioning it closely to leading models but operating over ten times faster. This powerful model is accessible through an API that is compatible with OpenAI, enabling developers to seamlessly integrate it into existing SDKs and applications with minimal modifications. Additionally, it supports streaming capabilities for real-time applications, allowing for response times as low as 24 milliseconds without any buffering or delays, making it an ideal choice for interactive use cases. Overall, Celeris-1 represents a significant advancement in the efficiency and performance of language models.

Description

MiniMax M3 is a frontier open-weight AI model built for coding, agentic work, multimodal understanding, and ultra-long-context tasks. The model supports up to a 1 million token context window, allowing it to work across large codebases, long documents, logs, project histories, and complex task environments. MiniMax M3 introduces MiniMax Sparse Attention, a sparse attention architecture designed to make long-context processing more efficient. The model is natively multimodal, with training that supports deeper semantic fusion across text, image, and video inputs. It is designed to support software engineering tasks, repository analysis, terminal-style work, browser-style retrieval, tool use, and autonomous workflows. MiniMax M3 has a mixture-of-experts architecture with hundreds of billions of total parameters and a smaller activated parameter count for more efficient inference. Developers can use it for AI coding assistants, workflow automation, research agents, document analysis, visual reasoning, and enterprise AI systems. Its long-context capability makes it especially useful when tasks require many files, references, instructions, or interaction histories to stay available at once. MiniMax M3 helps teams build more capable AI agents that can understand larger problems, work across multiple modalities, and execute complex tasks with stronger context awareness.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

APIFree
Alibaba AI Coding Plan
Claude Code
Clawd.run
Cline
ClinePass
Factory Droid
Fireworks AI
Hermes Agent
Kilo Code
MaxHermes
MiniMax Agent
MiniMax Code
MiniMax Mavis
Ollama
OpenClaw
Roo Code
Tabbit Browser
Together AI
Vision Agents

Integrations

APIFree
Alibaba AI Coding Plan
Claude Code
Clawd.run
Cline
ClinePass
Factory Droid
Fireworks AI
Hermes Agent
Kilo Code
MaxHermes
MiniMax Agent
MiniMax Code
MiniMax Mavis
Ollama
OpenClaw
Roo Code
Tabbit Browser
Together AI
Vision Agents

Pricing Details

$0.20 per 1M tokens
Free Trial
Free Version

Pricing Details

Free
Open source
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Celeris-1

Country

United States

Website

celeris.ai/

Vendor Details

Company Name

MiniMax

Founded

2021

Country

Singapore

Website

www.minimax.io

Product Features

Alternatives

No Alternatives

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