Observed Signal · Jul 29, 2026 · Technical Release · Source: TheSequence · Impact: 2/5 · Sentiment: Neutral
Large Language Models (LLM) & AI Market: 118B Laguna Outperforms Much Larger Models
The article analyzes Laguna S 2.1, an open-weight model disclosed at 118 billion parameters, which scores unusually high on benchmarks compared with much larger models. Laguna S 2.1 posts 70.2% on Terminal-Bench 2.1—above 1.6T DeepSeek-V4-Pro-Max (64.0%), 975B Inkling (63.8%), and 550B Nemotron 3 Ultra (56.4). On the tougher DeepSWE benchmark the gap widens: Laguna S 2.1 scores 40.4 versus DeepSeek-V4-Pro-Max’s 9.0. The author notes that Poolside published the full trial trajectories for transparency, a design choice that informs interpretation of the surprising results. The piece was published on 2026-07-29.
A notable technical/model release and transparent evaluation showing atypical performance that is relevant to AI model benchmarking; not a major platform policy change or industry-shifting event for AdTech.
Key Takeaways & Evidence Grounding
- Laguna S 2.1 is disclosed as a 118 billion-parameter open-weight model.
- Laguna S 2.1 scored 70.2% on Terminal-Bench 2.1.
- DeepSeek-V4-Pro-Max (1.6 trillion parameters) scored 64.0 on Terminal-Bench 2.1.
- Inkling (975 billion parameters) scored 63.8 and Nemotron 3 Ultra (550 billion parameters) scored 56.4 on Terminal-Bench 2.1.
- On DeepSWE, Laguna S 2.1 scored 40.4 while DeepSeek-V4-Pro-Max scored 9.0; Poolside published full trial trajectories from the final evaluation set.
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“Poolside seems to have anticipated that reaction, because they published every trajectory from every trial in the final evaluation set....”
The Sequence
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“Title: The Sequence AI of the Week #903: Laguna, the 118 Billion Parameters that Walks Into a Trillion-Parameter Bar...”
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