Ted

Ted

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@MV33Racing Who cares. It's fake racing.

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@MV33Racing @stevelamotte01 Fake racing.

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@MV33Racing @Motor_Sport I made it 4 laps into the sprint. Fake racing it not for me. My F1 weekend is over. Hello, Tour de France!

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I gave OpenAI Codex and several local AI models the same messy spreadsheet job: turn three sales Excel files into an executive workbook.

Codex finished best of course. It built the workbook and flagged the key issue: no ProductID in the sales files, so exact SKU-level margin was not possible.

The local models were mixed. qwen-Coder (19GB) got stuck. qwen3.6 (23GB) got surprisingly far but needed review. It would have saved about 80% of human time. qwen3-next (50GB), though much larger, did less well than qwen3.6.

Why this test? Because some company/client data should not go to a cloud model, depending on the situation. If that is the constraint, local AI is worth testing but you have to test it against the actual job, not a generic prompt. And bigger isn’t necessarily better.
https://t.co/1sgp4ymF7D

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@jordan_ross_8F LFG

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@petergyang It can optimize dumb very fast.

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Tested GPT-OSS-20B vs Qwen3.6 locally on a 96GB Mac Studio.

Same prompts. Same machine. Real assistant tasks.

GPT-OSS was fast.
Qwen was deeper.

That’s not a leaderboard; that’s the agent lesson:
the right system routes the right task to the right model.

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@HermesAgentTips mostly desktop now but cli still relevant

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@TimRunsHisMouth Give me a fist fight on the White House lawn. It's timely metaphor for how America was born.

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OpenAI has been quiet, relatively. Thinking they are in the kitchen cooking a banger meal.

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@mikefutia seo

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@AlfieJCarter agents

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@lr_mvcreative Omni

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@ianmiles

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@BBC_TopGear It's in a league of it's own.

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@AlmorTech They forgot to update the badge.

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@WSJ

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@SawyerMerritt

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@Polymarket