@karminski3: Finally, a useful local DeepResearch is available! I've packaged a skill for everyone, ready to use out of the box. The driving model is Apodex's newly released open-weight DeepResearch fine-tuned model Apodex-1.0-mini (now available a…
Summary
Apodex has released an open-weight DeepResearch fine-tuned model, Apodex-1.0-mini, based on Qwen3.5-35B-A3B. It scores 71.5 on BrowseComp, approaching flagship model performance, and can run efficiently locally. The author packaged an out-of-the-box skill.
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Cached at: 07/07/26, 01:31 PM
Finally, a good local DeepResearch is available! I’ve packaged a skill for you, ready to use out of the box.
The driving model is Apodex’s newly released open-weight DeepResearch fine-tuned model Apodex-1.0-mini (now available as Apodex deep research). This model directly tops the FutureX leaderboard (a benchmark by ByteDance and Stanford for predicting the accuracy of large models’ future predictions)! Now it can run locally.
The model is post-trained on Qwen3.5-35B-A3B, achieving 71.5 points on BrowseComp (AI Agent web browsing capability test), approaching flagship model level. And it’s small enough—my MacStudio runs at 70 tps+.
I was curious about the difference between DeepResearch fine-tuned models and regular models, so I used this skill to integrate Apodex’s single-agent DeepResearch framework and specifically tested it to see if the DeepResearch fine-tuned model is just hype:
#Apodex #DeepResearch #ReAct #DiscoverativeIntelligence #FutureX
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