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What is Kimi K2?
Kimi K2 showcases a groundbreaking series of open-source large language models that employ a mixture-of-experts (MoE) architecture, featuring an impressive total of 1 trillion parameters, with 32 billion parameters activated specifically for enhanced task performance. With the Muon optimizer at its core, this model has been trained on an extensive dataset exceeding 15.5 trillion tokens, and its capabilities are further amplified by MuonClip’s attention-logit clamping mechanism, enabling outstanding performance in advanced knowledge comprehension, logical reasoning, mathematics, programming, and various agentic tasks. Moonshot AI offers two unique configurations: Kimi-K2-Base, which is tailored for research-level fine-tuning, and Kimi-K2-Instruct, designed for immediate use in chat and tool interactions, thus allowing for both customized development and the smooth integration of agentic functionalities. Comparative evaluations reveal that Kimi K2 outperforms many leading open-source models and competes strongly against top proprietary systems, particularly in coding tasks and complex analysis. Additionally, it features an impressive context length of 128 K tokens, compatibility with tool-calling APIs, and support for widely used inference engines, making it a flexible solution for a range of applications. The innovative architecture and features of Kimi K2 not only position it as a notable achievement in artificial intelligence language processing but also as a transformative tool that could redefine the landscape of how language models are utilized in various domains. This advancement indicates a promising future for AI applications, suggesting that Kimi K2 may lead the way in setting new standards for performance and versatility in the industry.
What is Devstral?
Devstral represents a joint initiative by Mistral AI and All Hands AI, creating an open-source large language model designed explicitly for the field of software engineering. This innovative model exhibits exceptional skill in navigating complex codebases, efficiently managing edits across multiple files, and tackling real-world issues, achieving an impressive 46.8% score on the SWE-Bench Verified benchmark, which positions it ahead of all other open-source models. Built upon the foundation of Mistral-Small-3.1, Devstral features a vast context window that accommodates up to 128,000 tokens. It is optimized for peak performance on advanced hardware configurations, such as Macs with 32GB of RAM or Nvidia RTX 4090 GPUs, and is compatible with several inference frameworks, including vLLM, Transformers, and Ollama. Released under the Apache 2.0 license, Devstral is readily available on various platforms, including Hugging Face, Ollama, Kaggle, Unsloth, and LM Studio, enabling developers to effortlessly incorporate its features into their applications. This model not only boosts efficiency for software engineers but also acts as a crucial tool for anyone engaged in coding tasks, thereby broadening its utility and appeal across the tech community. Furthermore, its open-source nature encourages continuous improvement and collaboration among developers worldwide.
Integrations Supported
AiAssistWorks
Brokk
NVIDIA TensorRT
Nebius Token Factory
Okara
Integrations Supported
Hugging Face
Kaggle
LM Studio
Mistral AI
Mistral Code
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Open source
Free Version
Pricing Information
$0.1 per million input tokens
Free Version
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Customer Service / Support
Web-Based Support
Customer Service / Support
Standard Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
On-Site Training
Company Facts
Organization Name
Moonshot AI
Date Founded
2023
Company Location
China
Company Website
moonshotai.github.io/Kimi-K2/
Company Facts
Organization Name
Mistral AI
Date Founded
2023
Company Location
France
Company Website
mistral.ai/news/devstral
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
AI Reasoning Models
Not specified
Foundation Models
Not specified
Large Language Models
Not specified
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified