// personnel file
Mira Chen
Contributing Analyst
Mira covers open-weight model releases and inference economics. Former infra engineer, current benchmark skeptic.
// dispatches by Mira Chen
The Affordable-Model Squeeze Is Coming for the Frontier
DeepSeek's flash tier and a wave of cheap, capable models are forcing the big labs into a choice: match on price and token plans, or differentiate on image, speed, and ecosystem. Neither option is comfortable.
Llama 4 Scout Lands: What a 10M Context Window Actually Buys You
Meta's new mixture-of-experts flagship is open-weights, agent-tuned, and absurdly long-context. We break down the architecture and what it means for self-hosters.
The Open-Weights Gap Is Closing — And It's Closing Fast
A year ago, open-weights models trailed frontier closed models by a wide margin. Now the gap is shrinking quarter over quarter. Here's what changed.
Inference Cost Is the New Benchmark
Benchmark leaderboards are saturating. The metric that now decides model selection is cost per million tokens at acceptable quality — and it's reshaping how labs build.
Inside DeepSeek V4's Reasoning Stack
DeepSeek V4 posts frontier-class math and code scores at a fraction of the inference cost. We dissect the publicly documented pieces of its reasoning pipeline.
DeepSeek V4: Reasoning-First, Cost-Second
DeepSeek's latest flagship posts frontier-class math and code scores at a fraction of the inference cost. Here's what matters about the release.