Poolside
@poolsideai
We build models for agentic coding and long-horizon tasks. Try Laguna:
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Today we're releasing Laguna S 2.1, our most capable model to date.
It's a 118B total parameter Mixture-of-Experts model with 8B activated per token, a context window of up to 1M tokens, and thinking and no-thinking modes.
Capable enough to hold its own against models many times its size. Small enough to run on a single @NVIDIAAI DGX Spark.
Laguna S 2.1 is fully open under OpenMDW-1.1, with weights available today on @huggingface
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Turns out, the next Laguna also fits on a @NVIDIAAI DGX Spark 👀
Today we’re releasing Laguna XS 2.1.
It’s a small upgrade to the Laguna XS.2 model, the same 33B total / 3B active MoE and stronger results on multilingual coding and terminal-style tasks.
Available now on @huggingface, @OpenRouter, and via Poolside API.
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setup hell kills good RL ideas.
so we’re giving researchers Laguna XS.2, @PrimeIntellect Lab, and a weekend in London to run the whole loop:
tasks → evals → rewards → training → rollouts → adapters → inference
14 days to go.
come touch the weights:
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Poolside is hosting a 2-day model research hackathon in London.
Join us to push an open-weight agent model as far as you can. RL and fine-tune Laguna XS.2, our latest-generation model, on Prime Intellect Lab.
Dates: May 29–30
Partners: @nvidia + @PrimeIntellect + @huggingface
Prize: NVIDIA DGX Spark
Agents need better models.
Better models need cracked researchers.
Link below.
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