Laguna S 2.1
PulseAugur coverage of Laguna S 2.1 — every cluster mentioning Laguna S 2.1 across labs, papers, and developer communities, ranked by signal.
- 2026-08-13 product_launch Laguna S 2.1 announced a 10% price reduction, making its inference cost $0.18 per 1 million output tokens. source
- 2026-08-01 product_launch Poolside released updated weights for the Laguna S 2.1 model, increasing its context size and updating configurations. source
- 2026-08-01 product_launch Laguna S 2.1 on AI Gateway has increased its capacity by 10x for both free and paid tiers. source
- 2026-07-24 product_launch The Laguna S 2.1 model was released with multiple context window options and open-source availability. source
- 2026-07-24 product_launch Poolside released the Laguna S 2.1 model. source
- 2026-07-23 product_launch Poolside released its Laguna S 2.1 AI model, which demonstrates superior performance over larger models through self-revision and persistence. source
- 2026-07-23 product_launch Poolside released the Laguna S 2.1 model, demonstrating strong performance through agent efficiency. source
- 2026-07-23 product_launch Poolside released its new open-weight coding model, Laguna S 2.1. source
- 2026-07-23 product_launch Poolside AI released its Laguna S 2.1 model. source
- 2026-07-22 product_launch Poolside has released Laguna S 2.1. source
- 2026-07-22 product_launch Poolside AI has released its Laguna S 2.1 model. source
- 2026-07-22 product_launch Poolside released an update for the Laguna S 2.1 model to fix a looping issue. source
- 2026-07-22 product_launch Poolside released its new Laguna S 2.1 AI model, which is an open-source model outperforming larger competitors. source
- 2026-07-22 product_launch Poolside released the Laguna S 2.1 model. source
- 2026-07-22 product_launch Unsloth has released various quantization options for the Laguna S 2.1 large language model. source
1 day(s) with sentiment data
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Laguna S 2.1 and Ling 3 Flash AI models to face off in game generation benchmark
Two AI models, Laguna S 2.1 and Ling 3 Flash, are set to compete in a performance test on identical DGX Spark hardware. The creator of the test noted that predicting the outcome based solely on pre-test metrics is diffi…
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Laguna S 2.1 cuts price by 10% to $0.18/1M tokens
Laguna S 2.1 has reduced its price by 10% within the last 30 days, now costing $0.18 per 1 million output tokens. This model remains open-weight, allowing for self-hosted and more cost-effective inference.
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Laguna S 2.1 model updated with 1M context and new weights
Poolside has released updated weights for their Laguna S 2.1 model, specifically for FP8 and NVFP4 formats. These updates increase the default context size to 1 million tokens and include revised configurations. Users h…
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Laguna S 2.1 boosts AI Gateway capacity tenfold
Laguna S 2.1, an AI model available on AI Gateway, has significantly increased its capacity by 10x across both free and paid tiers. This enhancement allows for greater request volumes, particularly benefiting agentic co…
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LLaMA community seeks new 70-80B parameter model contenders
A user on the r/LocalLLaMA subreddit is seeking recommendations and expressing a desire for new large language models in the 70-80 billion parameter range. They currently use models like DSV4 Flash 0731, Inkling Small, …
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NVIDIA GB10/DGX Spark users debate best AI model performance
A user on Reddit's r/LocalLLaMA community is seeking recommendations for the best performing and most stable AI model that can run on a single NVIDIA GB10/DGX Grace Blackwell Superchip with Apache Spark. The discussion …
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Laguna S 2.1 model size increases significantly to 96GB
The Laguna S 2.1 model, specifically its Q4_K_M variant, has seen a significant increase in size from 68GB to 96GB. This change involves upgrading eight layers to FP16 while the rest remain in 4-bit quantization. The re…
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Laguna S 2.1 model shows benchmark strength but practical inference weakness
The Laguna S 2.1 model performs well in coding benchmarks but struggles with practical throughput during local inference. When compared against Qwen 3.6 on DGX Spark hardware, the disparity between benchmark scores and …
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Poolside releases Laguna XS 2.1 and Laguna S 2.1 models
Poolside has released two new models: Laguna XS 2.1 and Laguna S 2.1. The Laguna XS 2.1 model offers a context window of 262.1k tokens and is available for $0.06 in and $0.12 out per million tokens, or as a free and ope…
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Small AI model Laguna S 2.1 outperforms larger rivals by revising its work
Poolside's Laguna S 2.1, a smaller AI model, has demonstrated the ability to outperform larger models. This is achieved through its capacity for self-revision and persistence during complex, long-duration tasks. Notably…
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Poolside's Laguna S 2.1 model prioritizes agent efficiency over scale
Poolside's Laguna S 2.1 model demonstrates that agent efficiency can outperform raw scale, achieving a 70.2% score on the Terminal-Bench 2.1 test. This 8-billion parameter model, utilizing a novel thinking mode, has suc…
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Poolside's Laguna S 2.1 coding model outperforms larger rivals
Poolside has launched Laguna S 2.1, a compact open-weight coding model designed to improve its problem-solving capabilities. Unlike larger models that rely on sheer scale, Laguna S 2.1 is trained to iteratively check it…
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Poolside AI's Laguna S 2.1 achieves superior performance with a smaller footprint
Poolside AI has released its Laguna S 2.1 model, which reportedly outperforms larger competitors despite being 10 times smaller. The model was developed using a "Model Factory" that conducts 10,000 to 20,000 experiments…
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Poolside releases Laguna S 2.1, users share experiences
Poolside has released Laguna S 2.1, a new iteration of their language model. Users on the r/LocalLLaMA subreddit are discussing their experiences and opinions with the model, particularly its performance in agent loops.
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Poolside AI releases Laguna S 2.1, touts rapid model factory
Poolside AI has released its Laguna S 2.1 model, which reportedly outperforms models from Thinking Machines that are nearly ten times its size. The company's co-founder, Eiso Kant, discussed their "Model Factory" approa…
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Laguna S 2.1 model exhibits reasoning issues due to chat template configuration
A user on r/LocalLLaMA has identified an issue with the Laguna S 2.1 model where its reasoning phase is not functioning correctly. The problem appears to be related to the chat template, as disabling a specific setting,…
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Laguna S 2.1 model receives looping issue fix
Poolside has released an update for their Laguna S 2.1 model, addressing a looping issue that users have encountered. Both full precision and FP8 versions of the model have been updated, with other variants expected to …
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New equation predicts LLM inference speed on consumer hardware
A solo researcher has developed an equation to predict the inference speed of large language models on consumer hardware, based on parameters like model size, RAM, and bandwidth. This equation, derived from four observe…
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New benchmark shows strong link between Base64 generation and AI intelligence
A new benchmark called Encode Bench has revealed a strong correlation between a language model's ability to generate Base64 encoded responses and its intelligence scores. The benchmark, which tests models on tasks requi…
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Poolside's Laguna S 2.1 open model surpasses DeepSeek-V4-Pro-Max
Poolside has released Laguna S 2.1, an 118-billion parameter Mixture-of-Experts model that outperforms the 1.6-trillion parameter DeepSeek-V4-Pro-Max on the Terminal-Bench 2.1 benchmark. This American-made open model bo…