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Preferred Networks

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  1. PFN releases PLaMo 3.0 Fin, a finance-focused small language model with open weights that runs from a single GPU in closed environments

    Preferred Networks built PLaMo 3.0 Fin on PLaMo 3 NICT, a pretrained model from joint research with NICT, by further training on Japanese finance data, and released it as an open-weight finance-focused small language model. Aimed at financial institutions' operations, it reasons before answering with the reasoning trace in Japanese and can call external tools such as web search, calculation and internal databases. Its small size lets it run from a single GPU in closed cloud or on-premises environments, positioned as the core model of AI agents handling tasks such as inquiry classification, document extraction and alert analysis.

  2. PFN releases PLaMo 3.0 Fin, an 8B finance-focused model: Japanese financial benchmark rises from 48.0 to 55.8

    Preferred Networks released PLaMo 3.0 Fin, an 8B-parameter language model specialized for finance, built from PLaMo 3 NICT 8B Base through continued pretraining on financial corpora, supervised fine-tuning and direct preference optimization, with Japanese reasoning traces and external tool calls. Its average score on the Japanese financial-knowledge benchmark japanese-lm-fin-harness rose from 48.0 for the base model to 55.8, above Gemma 4 E4B and gpt-oss-20b and below Qwen3.5-9B and Ministral 3 14B under PFN's own measurement setup.

  3. PFN opens the weights of PLaMo 3 Translate: a 0.8B model runs 53 languages offline

    Preferred Networks released PLaMo 3 Translate, a translation-specialized LLM suite originally built for its own PLaMo Translate service, as open weights on Hugging Face in four sizes (0.8B, 2B, 8B, 31B), runnable entirely offline on smartphones, laptops or internal corporate servers across 53 languages including English and Japanese. Under the PLaMo Community License, individuals and enterprises with annual revenue of 1 billion yen or less in their most recent fiscal year can download and use the models free for commercial and non-commercial purposes; larger organizations need a commercial license. PFN says its comparative evaluations put even the smallest 0.8B version ahead of comparable translation-specific LLMs such as Google's TranslateGemma and Tencent's Hy-MT2.

  4. PFN opens the weights of its translation-focused LLM PLaMo 3 Translate, letting the 0.8B model translate 53 languages on an offline phone

    PFN released PLaMo 3 Translate, the translation-focused large language model behind its PLaMo translation service, as open-weight models in four sizes, 0.8B, 2B, 8B and 31B, which can be embedded in phones, laptops or in-house servers to translate among 53 languages including Japanese and English without a network connection. By PFN's own evaluation, the smallest model scores above Google's TranslateGemma and Tencent's Hy-MT2 on translation quality, and companies and individuals with revenue or sales of 1 billion yen or less in the latest fiscal year may use it commercially for free under the PLaMo Community License.

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