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What is Mercury Edit 2?

Mercury Edit 2 is an advanced AI model developed by Inception Labs, forming part of the Mercury suite, and is designed for efficient reasoning, coding, and editing through a unique architecture that diverges from standard large language models. This model improves upon the capabilities of Mercury 2, a diffusion-based system that can produce and enhance entire outputs at once, as opposed to the traditional approach of generating text token by token, resulting in significantly faster processing and more flexible editing. Rather than serving as a straightforward "typewriter," it functions as a responsive editor, starting with an initial draft and progressively refining it across multiple tokens in tandem, which allows for immediate interaction and rapid iterations in various areas, including code refinement, content generation, and agent-oriented tasks. With a remarkable throughput of nearly 1,000 tokens per second, this framework greatly exceeds the performance of conventional models while maintaining strong reasoning capabilities across a variety of benchmarks. Its innovative structure not only changes how users engage with AI but also establishes a new benchmark for excellence within the realm of artificial intelligence, pushing the boundaries of what is possible in this rapidly evolving field. As a result, it opens up new avenues for creativity and productivity that were previously unattainable.

What is Celeris-1?

Celeris-1 distinguishes itself as a rapid and adaptable language model platform, enhanced by a diffusion model that provides state-of-the-art intelligence at remarkable speeds. In contrast to traditional autoregressive models that produce tokens one after another, Celeris utilizes a diffusion-based inference architecture that facilitates concurrent generation, leading to response times that can be recorded in just milliseconds. On the MMLU-Pro benchmark, Celeris-1 achieves an impressive accuracy rate of 75.9%, with a median response time of 158 milliseconds and an extraordinary output rate of 1,664 tokens per second, placing it in close proximity to top models while functioning more than ten times faster. This robust model is available through an API compatible with OpenAI, making it easy for developers to integrate it into their existing SDKs and applications with minimal effort. Moreover, it features streaming capabilities that cater to real-time applications, enabling response times as quick as 24 milliseconds without any interruptions or delays, which makes it particularly suitable for interactive scenarios. Additionally, Celeris-1’s innovative architecture not only enhances its performance but also sets a new standard for future language model development. Overall, Celeris-1 signifies a remarkable leap forward in the efficiency and capability of language models.

Media

Media

Integrations Supported

Cline
Cursor
ElevenLabs
Inception Labs
Kilo Code
LangChain
OpenAI
OpenClaw
OpenCode
Roo Code
Vapi AI
Zed

Integrations Supported

Cline
Cursor
ElevenLabs
Inception Labs
Kilo Code
LangChain
OpenAI
OpenClaw
OpenCode
Roo Code
Vapi AI
Zed

API Availability

Has API

API Availability

Has API

Pricing Information

$0.25 per 1M input tokens
Free Version
Free Trial Offered?

Pricing Information

$0.20 per 1M tokens
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Inception

Company Location

United States

Company Website

www.inceptionlabs.ai/blog/introducing-mercury-edit-2

Company Facts

Organization Name

Celeris-1

Company Location

United States

Company Website

celeris.ai/

Categories and Features

Categories and Features

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