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Tips, guides, and insights on AI teammates, smarter support, and building better teams.

StepFun Step 5 Preview review: is the cheap 600B model worth it?
My hands-on StepFun Step 5 Preview review: a 600B/27B MoE reasoning model at $1/$2.70 per 1M tokens. The pricing is real, the benchmarks are self-graded. Here is my verdict.

StepFun Step 5 Preview: what the new 600B model actually is
StepFun Step 5 Preview is a 600B/27B sparse MoE model with a 1M-token context, open weights due Oct 15. Here are the specs, pricing, benchmarks, and my take.

8 best Qwen Image 2.1 alternatives in 2026
Qwen Image 2.1 is a great open model with a license catch. Here are the 8 best Qwen Image 2.1 alternatives in 2026, with real API prices and who each is for.

Qwen Image 2.1 review: Alibaba's open image model, tested
A hands-on Qwen Image 2.1 review: what the 7B open-weight model does well, the native transparency trick, and the license catch nobody's mentioning.

Qwen Image 2.1: what's new, how to use it, and the license catch
Qwen Image 2.1 is Alibaba's new 7B open-weight image model with native transparency. Here's what changed, how to run it, the cost, and the license catch.

The 8 best Laya AI alternatives in 2026
Laya AI is a fast open-source decision model, but it needs fine-tuning and only classifies. Here are 8 Laya AI alternatives, from managed APIs to teammates that act.

Laya AI review: the open 33ms decision model, tested honestly
An honest Laya AI review: the open-source 421M decision model is genuinely fast and calibrated, but the headline accuracy hides a fine-tuning caveat. Here is where it wins, where it does not, and who should use it.

Laya AI: the open 33ms decision model that can't hallucinate
Laya AI is Convai's open-source, 421M System 1 decision model: 33ms typed answers with calibrated confidence, no text generation, and an honest zero-shot caveat.

Is Jev really ultrafast? TypeSafe's System One model, tested
TypeSafe calls Jev an ultrafast System One model at 70-500ms a decision. Here is what the speed claim really means, where it holds up, and where it does not.
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