Laguna XS 2.1Poolside
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RankLLMCastorini
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Related Products
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About
Laguna XS 2.1 is an upgraded open weight agentic coding model designed for long-horizon work on a local machine. It uses a 33-billion-parameter Mixture-of-Experts architecture with 3 billion activated parameters per token, retaining the same efficient architecture as Laguna XS.2 while improving multilingual software engineering and terminal-style task performance. The model is built to support coding agents that inspect repositories, reason through complex changes, use tools, execute commands, and continue working across extended tasks. It is served with a 256K context window, giving agents room to work with large codebases, lengthy histories, and multi-step workflows. Laguna XS 2.1 is supported by vLLM, SGLang, NVIDIA TensorRT-LLM, Hugging Face Transformers, and Ollama, with native llama.cpp support planned. It is available in BF16, FP8, INT4, and NVFP4 checkpoints, allowing developers to choose between maximum fidelity and configurations suited to tighter VRAM or compute budgets.
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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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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Local-first developer tooling teams that need an efficient open model for persistent coding agents on limited hardware
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Audience
Academic researchers and developers seeking a solution offering tools for implementing and evaluating listwise reranking with large language models
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationPoolside
Founded: 2023
United States
poolside.ai/blog/introducing-laguna-xs-2-1
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Company InformationCastorini
Canada
github.com/castorini/rank_llm/
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Categories |
Categories |
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Integrations
Agent Client Protocol (ACP)
Cline
Gemini
Hermes Agent
Hugging Face
IntelliJ IDEA
Kilo Code
Llama
Mistral AI
NVIDIA TensorRT
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Integrations
Agent Client Protocol (ACP)
Cline
Gemini
Hermes Agent
Hugging Face
IntelliJ IDEA
Kilo Code
Llama
Mistral AI
NVIDIA TensorRT
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