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# PLaMo 3.0 Fin

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Preferred Networks Nov 9, 2026
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.
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.
Preferred Networks
PLaMo 3.0 Fin Supervised Fine-tuning
Preferred Networks Nov 9, 2026
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.
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.
Preferred Networks
PLaMo 3.0 Fin Direct Preference Optimization Continued Pretraining

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