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New 1.1 GB language model 'Obsessive-1.7B' excels at focused web searches

A new fine-tuned language model named Obsessive-1.7B has been developed, designed specifically to act as a subagent for web searches. This model, weighing just 1.1 GB, excels at taking a factual question, performing a single web search, and then providing a concise answer with a verbatim quote and the source URL. It demonstrates a significant improvement over its base model in accurately identifying when an answer is present in search results and correctly reporting when it is not found, while also reducing the tendency to invent answers. AI

IMPACT This specialized model could improve the efficiency and accuracy of AI agents performing web-based information retrieval.

RANK_REASON Release of a specialized, fine-tuned language model for a specific task (web search subagent).

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New 1.1 GB language model 'Obsessive-1.7B' excels at focused web searches

How we ranked this

Signal score
3 / 100
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Newsworthiness bucket
Tool
Release of a specialized, fine-tuned language model for a specific task (web search subagent).
Source corroboration
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, product
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/MuzafferMahi ·

    Obsessive-1.7B: a 1.1 GB web-search subagent

    <!-- SC_OFF --><div class="md"><p>I fine-tuned LFM3-1.7B to do one job: take a factual question, call <code>web_search</code> once, and answer with a short value, a word-for-word quote and the URL. If the results don’t contain the answer, it says “Not found in the search results.…