Laguna S 2.1.

specs at a glance

how good is Laguna S 2.1 at coding?

Laguna S 2.1 is on our board but deliberately unranked. We rank by SWE-bench Verified, Poolside has not published that number, and no independent evaluation has run it, so there is nothing here we could stand behind. What the maker does publish is 59.4% on SWE-bench Pro and 70.2% (TB2.1) on Terminal-Bench, measured on its own scaffold and not comparable like-for-like with the ranked rows. It moves into the ranking the moment a confirmed score exists. On the harder SWE-bench Pro it scores 59.4%. Terminal-Bench (agentic terminal work): 70.2% (TB2.1).

Score provenance: Vendor-reported (Poolside, Jul 21 2026): Terminal-Bench 2.1 70.2% with thinking enabled (60.4% without), SWE-bench Pro 59.4%, SWE-bench Multilingual 78.5%, DeepSWE v1.1 40.4%. Poolside published no SWE-bench Verified score, so it stays unranked pending an independent eval. vals.ai has evaluated Laguna M.1 (57.6%) and Laguna XS.2 (55.2%) but not S 2.1, and a near-miss version is not a match. Price: OpenRouter $0.10/$0.20 per 1M.

Context added 2026-08-23: Nvidia is paying Poolside $6B for a non-exclusive license to the Model Factory system that builds this family, is investing $1B at a $13B post-money valuation, and has made job offers to the 109 engineers who built Laguna, per Bloomberg. Poolside stays independent and keeps shipping, so the row is unaffected, but who is training future Laguna builds is now an open question. See /p/nvidia-poolside-6b-license-model-factory-109-staff/.

Re-checked 2026-09-09: vals.ai's SWE-bench Verified board is unchanged since the September 1 archival and still shows no evaluation for this model; all previously-tracked ranked scores were also re-verified this run and hold within normal variance (largest drift under 0.4pp).

what does Laguna S 2.1 cost?

$0.10 per 1M input tokens and $0.20 per 1M output — as listed by the maker. Coding workloads are output-heavy, so weight the output rate when budgeting. Run your own volume through the AI API cost calculator for a monthly estimate.

where can you use it?

Available via Open weights (OpenMDW-1.1) · OpenRouter · Baseten · Vercel AI Gateway · self-host. Because it ships open weights, you can also self-host it on your own hardware or any inference provider — with the version pinned so the model can't change under you.

Full storyLaguna S 2.1: 8B Active Params, 70% Terminal-Bench

Ranked on our AI Coding Leaderboard — scores confirmed against primary sources only, updated 2026-09-03.