Poolside's 33B/3B-active open-weight coding model is worth bookmarking for local agent workflows, OpenRouter trials, and long-context coding benchmarks. Poolside Laguna XS 2.1 is a compact Mixture-of-Experts coding model built for agentic coding and long-horizon software work. Poolside says it has 33B total parameters, 3B active parameters per token, a 256K context window through its API and OpenRouter, and stronger results than Laguna XS.2 on SWE-bench Multilingual and terminal-style tasks. Use this as a practical evaluation target, not as a blind replacement for your current coding model. Good tests include repository navigation, multi-step bug fixes, shell-heavy tasks, tool-call formatting, and cost per completed change. The model is available as weights on Hugging Face and can also be tried through OpenRouter, including a free endpoint where availability and data-use terms should be checked before sending sensitive code. Useful checks before adopting it: Confirm the license and acceptable-use terms for your deployment. Compare BF16, FP8, NVFP4, INT4, and GGUF variants against your hardware budget. Preserve reasoning history when your harness supports it, because Poolside documents the model as reasoning-capable between tool calls. Test vLLM, SGLang, Transformers, TensorRT-LLM, Ollama, or llama.cpp support with your actual agent stack. Avoid sending proprietary code to free hosted endpoints unless the provider terms match your data policy. This is Loot rather than a blog post because the main value is direct use: model page, weights, hosted endpoint, and implementation notes.
