Day 1 brief · July 21, 2026
Poolside shipped Laguna S 2.1 today: a 118B MoE (8B active) coding model that sits next to models several times its size on Terminal-Bench 2.1. Here’s where it actually lands against open peers and the closed frontier, and what that means if you care about running serious agentic coding on a desk machine.
Laguna S 2.1 is Poolside’s scale-up from Laguna XS 2.1 (released July 2). Same product family, different weight class: S is the “serious local agent” box; XS is the “fits a normal Mac” box.
Total / active
118B / 8B
MoE · per token
Terminal-Bench 2.1
70.2%
thinking on · pool harness
Context
1M
thinking + no-thinking
License
OpenMDW
1.1 · weights public
This is the chart that matters for the release story. Scores below are Terminal-Bench 2.1 pass@1 as compiled in Poolside’s launch materials (max of vendor / official leaderboard / third-party, as of July 21, 2026). Closed models with undisclosed size are listed with “—” for params.
Bar scale = absolute % score (not relative). Frontier rows are closed / API tier.
| # | Model | Total | Active | TB 2.1 | Type |
|---|---|---|---|---|---|
| 1 | GPT-5.6 Sol | — | — | 88.8% | Closed |
| 2 | Kimi K3 | 2.8T | 50B | 88.3% | Open weights |
| 3 | Claude Fable 5 | — | — | 88.0% | Closed |
| 4 | GPT-5.6 Terra | — | — | 87.4% | Closed |
| 5 | GPT-5.6 Luna | — | — | 84.7% | Closed |
| 6 | Claude Opus 4.8 | — | — | 84.6% | Closed |
| 7 | Claude Sonnet 5 | — | — | 80.4% | Closed |
| 8 | Muse Spark 1.1 | — | — | 80.0% | Closed / undisclosed |
| 9 | Qwen 3.7 Max | — | — | 74.5% | API / undisclosed size |
| 10 | Tencent Hy3 | 295B | 21B | 71.7% | Open weights |
| 11 | Laguna S 2.1 | 118B | 8B | 70.2% | Open weights |
| 12 | MiniMax M3 | 428B | 23B | 66.0% | Open weights |
| 13 | DeepSeek-V4-Pro-Max | 1.6T | 49B | 64.0% | Open weights |
| 14 | Inkling | 975B | 41B | 63.8% | Open weights |
| 15 | DeepSeek-V4-Flash-Max | 284B | 13B | 61.8% | Open weights |
| 16 | Nemotron 3 Ultra | 550B | 55B | 56.4% | Open weights |
| 18 | Qwen3.6-27B | 27B | — | 51.3% | Open weights |
| 19 | Qwen3.6-35B-A3B | 35B | 3B | 44.9% | Open weights |
| 20 | Nemotron 3 Super | 120B | 12B | 38.6% | Open weights |
| 21 | Laguna XS 2.1 | 33B | 3B | 33.4% | Open weights |
| 22 | Mistral Small 4 | 119B | — | 21.4% | Open weights |
Source: Poolside “Introducing Laguna S 2.1” (2026-07-21). Rank numbers follow their published TB 2.1 table. “Active” is MoE activated params per token when disclosed.
Terminal-Bench is the launch headline. These additional agentic / software engineering numbers show where S 2.1 is strong vs where frontier still owns the board.
| Model | Size | SWE Multi | SWE Pro | DeepSWE | SWE Atlas | Toolathlon |
|---|---|---|---|---|---|---|
| Laguna S 2.1 | 118B-A8B | 78.5% | 59.4% | 40.4% | 46.2% | 49.7% |
| Tencent Hy3 | 295B-A21B | 75.8% | 57.9% | — | — | — |
| DeepSeek-V4-Pro-Max | 1.6T-A49B | 76.2% | 55.4% | 9.0% | 27.2% | 55.9% |
| Inkling | 975B-A41B | — | 54.3% | — | — | 45.5% |
| Nemotron 3 Ultra | 550B-A55B | 67.7% | — | — | — | 34.3% |
| Qwen 3.7 Max | — | 78.3% | 60.6% | — | — | — |
| Muse Spark 1.1 | — | — | 61.5% | 53.3% | 42.2% | 75.6% |
| Claude Fable 5 | — | — | 80.3% | 70.0% | — | — |
| Kimi K3 | 2.8T-A50B | — | — | 69.0% | — | — |
| GPT-5.6 Sol | — | — | — | 73.0% | — | — |
| GPT-5.6 Terra | — | — | — | 70.0% | — | — |
| GPT-5.6 Luna | — | — | — | 67.2% | — | — |
Poolside table, 2026-07-21. Laguna scores in pool harness with thinking; peers are max public reported scores. Dashes = not reported in that table.
If your constraint is “runs on a normal Mac / one consumer GPU,” look at XS 2.1 (33B total / 3B active), not S. Different weight class, different expectations. Poolside’s XS card used Terminal-Bench 2.0 (not 2.1) with their agent harness — do not mix those columns with the TB 2.1 table above without a note.
| Model | Size | SWE Verified | SWE Multi | SWE Pro | TB 2.0 |
|---|---|---|---|---|---|
| Laguna XS 2.1 | 33B-A3B | 70.9% | 63.1% | 47.6% | 37.5% |
| Laguna XS.2 | 33B-A3B | 69.9% | 57.7% | 46.3% | 35.7% |
| Qwen3.6-35B-A3B | 35B-A3B | 73.4% | 67.2% | 49.5% | 51.5% |
| North Mini Code | 30B-A3B | 67.6% | — | 40.2% | 36.0% |
| MAI-Code-1-Flash | 137B-A5B | 71.6% | 65.5% | 51.2% | 54.8% |
| gpt-oss-120B | 120B-A5B | — | — | 16.2% | 18.7% |
| Claude Haiku 4.5 | — | 73.3% | — | 39.5% | 29.8% |
| GPT-5.4 Nano | — | — | — | 52.4% | 46.3% |
Source: Hugging Face card for poolside/Laguna-XS-2.1 (benchmarks as of ~July 2, 2026). On the separate TB 2.1 leaderboard table, XS 2.1 is listed at 33.4% — different suite / compilation.
S 2.1’s story is not “we beat Sol.” It’s “we put 70% Terminal-Bench-class agentic coding into a weight class you can actually host.” That matters for privacy, air-gapped shops, cost at high volume, and people who refuse to ship their entire repo to a frontier API.
GPT-5.6 Sol / Terra / Luna and Claude Fable 5 (plus Kimi K3 at 2.8T) still own the top of Terminal-Bench and especially DeepSWE. If your job is hardest-path, multi-day agentic work and budget is not the constraint, rent the frontier.
In the disclosed-size open band, S 2.1 sits in a sweet spot: above DeepSeek V4 Pro Max and Nemotron 3 Ultra on TB 2.1 despite far fewer total parameters; within shouting distance of Hy3; far above same-size dense/open peers like Mistral Small 4. Qwen remains the naming gravity well for local builders (especially at 27B–35B), but S changes the “US open coding model” conversation on day one.
Research notes from a multi-source pass also live at:
~/Documents/Last30Days/laguna-xs-2-1-poolside-raw-v3.md