Laguna XS 2.1
Laguna XS 2.1, released July 2, 2026, is Poolside's updated agentic-coding model (33B total, ~3B active MoE, 40 layers, 256 experts). It switched licensing from Apache-2.0 (the original Laguna XS.2) to OpenMDW-1.1, a permissive license co-developed with NVIDIA and the Linux Foundation specifically for AI model weights.
Overview
Laguna XS 2.1, released July 2, 2026, is Poolside's updated agentic-coding model (33B total, ~3B active MoE, 40 layers, 256 experts). It switched licensing from Apache-2.0 (the original Laguna XS.2) to OpenMDW-1.1, a permissive license co-developed with NVIDIA and the Linux Foundation specifically for AI model weights.
Strengths
- OpenMDW-1.1 license gives cleaner enterprise legal standing than a custom license
- MoE (~3B active of 33B total) targets single-GPU agentic coding
- Predecessor scored 44.5% SWE-Bench Pro, 30.1% Terminal-Bench 2.0 (vendor-reported)
Weaknesses
- OpenMDW-1.1 is a new license (mid-2026) with less legal precedent than Apache-2.0/MIT
- Predecessor (Laguna XS.2) was retired from Poolside's own API within 3 months of launch — fast iteration cadence, uncertain longevity per version
Reviewed quality benchmarks
First-party rows were run by RunLocalAI; reviewed community rows are labeled in the data. Every row links to the raw test-run log.
| Benchmark | Quant | Runtime / Hardware | Score | Raw log |
|---|---|---|---|---|
HumanEval+ tested 2026-07-21 | Q4_K_M | ollama-0.32.1-vast5090 rtx-5090 | 87.2/100 | Gist → |
Q4_K_M note:First-party HumanEval+ on a rented Vast.ai RTX 5090 32GB instance via Ollama 0.32.1. Generation via evalplus_openai_generate.py, scoring via evalplus.evaluate (native Linux, no Windows shim needed). No DB credentials were placed on the rented host — results were pulled back and ingested from the operator's machine.
Want to verify? Every row links to its Gist with full stdout and stderr of the run. The runner script is in the public repo (scripts/run-humaneval-plus.ts) — reproducible end-to-end. Browse all coding scores at /benchmarks/coding.
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 20.0 GB | 24 GB |
Get the model
Ollama
One-line install
ollama run laguna-xs-2.1Read our Ollama review →Hardware that runs this
Cards with enough VRAM for at least one quantization of Laguna XS 2.1.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run Laguna XS 2.1?
Can I use Laguna XS 2.1 commercially?
What's the context length of Laguna XS 2.1?
How do I install Laguna XS 2.1 with Ollama?
Source: Vendor official documentation
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify Laguna XS 2.1 runs on your specific hardware before committing money.