MiniMax M2MiniMax
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RankLLMCastorini
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Related Products
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MiniMax M2:
About
MiniMax M2 is an open source foundation model built specifically for agentic applications and coding workflows, striking a new balance of performance, speed, and cost. It excels in end-to-end development scenarios, handling programming, tool-calling, and complex, long-chain workflows with capabilities such as Python integration, while delivering inference speeds of around 100 tokens per second and offering API pricing at just ~8% of the cost of comparable proprietary models. The model supports “Lightning Mode” for high-speed, lightweight agent tasks, and “Pro Mode” for in-depth full-stack development, report generation, and web-based tool orchestration; its weights are fully open source and available for local deployment with vLLM or SGLang. MiniMax M2 positions itself as a production-ready model that enables agents to complete independent tasks, such as data analysis, programming, tool orchestration, and large-scale multi-step logic at real organizational scale.
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RankLLM:
About
RankLLM is a Python toolkit for reproducible information retrieval research using rerankers, with a focus on listwise reranking. It offers a suite of rerankers, pointwise models like MonoT5, pairwise models like DuoT5, and listwise models compatible with vLLM, SGLang, or TensorRT-LLM. Additionally, it supports RankGPT and RankGemini variants, which are proprietary listwise rerankers. It includes modules for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. RankLLM integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts (MoE) models. The toolkit supports various backends, including SGLang and TensorRT-LLM, and is compatible with a wide range of LLMs.
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MiniMax M2:
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
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RankLLM:
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
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MiniMax M2:
Audience
Software engineering teams, AI practitioners and developer-led organizations requiring a tool offering a model optimized for agent workflows and full-stack coding tasks
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RankLLM:
Audience
Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models
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MiniMax M2:
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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RankLLM:
Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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MiniMax M2:
API
Offers API
Supported
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RankLLM:
API
Offers API
Supported
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MiniMax M2:
Screenshots and Videos |
RankLLM:
Screenshots and Videos |
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MiniMax M2:
Pricing
$0.30 per million input tokens
Free Version
Supported
Free Trial
Supported
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RankLLM:
Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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MiniMax M2:
Reviews/
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RankLLM:
Reviews/
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MiniMax M2:
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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RankLLM:
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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MiniMax M2:
Company InformationMiniMax
Founded: 2021
Singapore
www.minimax.io/news/minimax-m2
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RankLLM:
Company InformationCastorini
Canada
github.com/castorini/rank_llm/
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MiniMax M2:
Alternatives |
RankLLM:
Alternatives |
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RankLLM:
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RankLLM:
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RankLLM:
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MiniMax M2:
Categories |
RankLLM:
Categories |
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MiniMax M2:
Integrations
OpenAI
Supported
Python
Supported
Claude Code
Supported
Cline
Supported
DeepSeek
Supported
Gemini
Not Supported
Gemini Enterprise
Not Supported
Kilo Code
Supported
Llama
Not Supported
Mistral AI
Not Supported
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RankLLM:
Integrations
OpenAI
Supported
Python
Supported
Claude Code
Not Supported
Cline
Not Supported
DeepSeek
Not Supported
Gemini
Supported
Gemini Enterprise
Supported
Kilo Code
Not Supported
Llama
Supported
Mistral AI
Supported
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MiniMax M2:
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RankLLM:
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