AI

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

Read full article at source ↗

Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 08/11/2026, 03:47:26 UTC.

Briefings

A 1.1 GB web-search subagent named Obsessive-1.7B was trained to answer factual questions by calling web_search, providing a short value, a word-for-word quote, and the URL. It returns a 'Not found' message if the answer is missing, but also frequently invents answers or quotes neighboring facts. The model runs as a subagent under a larger base model, not as a standalone chat model, and uses Llama Server with a LoRA rank of 16 on an RTX 4060 laptop.

Key points

• Obsessive-1.7B is a 1.1 GB web-search subagent trained to answer factual questions by calling web_search, providing a short value, a word-for-word quote, and the URL.
• The model returns a 'Not found' message if the answer is missing, but also frequently invents answers or quotes neighboring facts, with 10% of answers being invented values.

Context

The subagent was developed by /u/MuzafferMahi for the r/LocalLLaMA subreddit, using Llama Server with a LoRA rank of 16 on an RTX 4060 laptop. It uses LFM3-1.7B base model with Llama Server configuration, trained on 9k tool-calling conversations.

Limitations

Coverage is limited to 131 fixed results from a 1.1 GB model; the base model wins on raw correct answers live but returns nothing 62% of the time. Multi-turn chats confuse it, and it only supports English with a single question per conversation.

Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 08/11/2026, 04:32:43 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.

View archived briefing on IPFS
bafybeiertxm7g6ytsbicmpwegiuyyewrm747qkdhgbwslvgeoiivixd67y