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Research & analysis · 2026-09-13

A local Deep Research replacement that runs on a few dollars a month

A local deep-research pipeline using GPT-OSS 120B and Gemma 12B produces results on par with cloud deep research at a fraction of the token cost.

This person built a local version of the deep-research feature offered by Claude, ChatGPT and Gemini. Their pipeline runs GPT-OSS 120B through the Brave API, which costs about $5 a month with a credit included, and uses Gemma 12B QAT for summarisation, which they found performed just as well as 26B and 31B models for that task.

A run takes five to ten minutes, and when they tested the same research prompts against cloud deep research the results were on par. Their motivation is cost: they describe the token consumption of cloud deep-research runs as a rip-off.

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Reported anonymously by an r/LocalLLM contributor · 2 upvotes at capture

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CURRENT2026-09-13A local Deep Research replacement that runs on a few dollars a month

A local deep-research pipeline using GPT-OSS 120B and Gemma 12B produces results on par with cloud deep research at a fraction of the token cost.

Research & analysisHardware unspecifiedGPT-OSS 120B, Gemma 12BRuntime unspecified
ChangedDescriptionModels
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DescriptionPreviousThis person built a local version of the deep-research feature offered by Claude, ChatGPT and Gemini. Their pipeline runs GPT-OSS 120B through the Brave API, which costs about $5 a month with a credit included, and uses Gemma 4 12B QAT for summarisation, which they found performed just as well as 26B and 31B models for that task. A run takes five to ten minutes, and when they tested the same research prompts against cloud deep research the results were on par. Their motivation is cost: they describe the token consumption of cloud deep-research runs as a rip-off.This snapshotThis person built a local version of the deep-research feature offered by Claude, ChatGPT and Gemini. Their pipeline runs GPT-OSS 120B through the Brave API, which costs about $5 a month with a credit included, and uses Gemma 12B QAT for summarisation, which they found performed just as well as 26B and 31B models for that task. A run takes five to ten minutes, and when they tested the same research prompts against cloud deep research the results were on par. Their motivation is cost: they describe the token consumption of cloud deep-research runs as a rip-off.
ModelsPreviousGPT-OSS 120B, Gemma 4 12BThis snapshotGPT-OSS 120B, Gemma 12B

This is the currently published snapshot.

REVISION 12026-09-13A local Deep Research replacement that runs on a few dollars a month

A local deep-research pipeline using GPT-OSS 120B and Gemma 4 12B produces results on par with cloud deep research at a fraction of the token cost.

Research & analysisHardware unspecifiedGPT-OSS 120B, Gemma 4 12BRuntime unspecified

Archived published snapshot — kept for context and comparison.

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