AI大模型? (English)

Generated: 2026-06-20 13:16:42

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My biggest pitfall this year was fooling myself.

Can you believe it? At the beginning of the year, I got my hands on the Gemma 3 12B model, and I was thrilled—fast speed, low cost, deploying it was as easy as pie. I rushed it into production, bragging to the team: Look, we're doing top-notch work with minimal investment. And then? Two weeks. Just two weeks. I tested Qwen2.5 Coder 32B in the same scenario, and Gemma's response quality was utterly crushed. Worse, user feedback came in—they directly said our product had become dumber. Talk about a slap in the face, loud and clear.

See, this is the classic superstition about parameters. I used to think bigger parameters meant better, then I thought smaller meant cheaper, and ended up getting neither. Where's the real explosive track? Mid-size models—the 15B to 70B range. Look, Qwen2.5 Coder 32B (released in November 2024) opened up a whole new territory. Then Mistral Small 3 (24B) and Llama 4 Scout (17B) rushed in, each grabbing a huge share of the mind. And small models? Their share plummeted. Users are always waiting for the next big thing.

Here's the counterint