Platforms
Speculative Decoding: The Inference Trick Behind Faster Model Responses
How speculative decoding pairs a small draft model with a large one to cut generation latency, and when it actually delivers a real speedup.
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PlatformsPrompt Caching Explained: Cutting Inference Costs Without Cutting Quality
How prompt caching actually works at the API level, when it saves real money, and the setup mistakes that silently disable it.
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PlatformsLocal AI Inference Servers Compared: Ollama, LM Studio, and the Rest
How the main local inference tools actually differ, what hardware really limits you, and when running models locally beats calling a hosted API.
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PlatformsAI Answer Engines Cite Three Sources. How to Be One
Retrievable, parseable, quotable — in that order. Plus why your analytics will never show you a citation.
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ToolsLLM Observability Tools: Adopt Them When You Ship Agents
Step-level traces are the product. Cost per request is the metric teams add last and regret not adding first.
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PlatformsGPU Cloud Platforms in 2026: Three Tiers, Three Tradeoffs
Storage, egress, and idle time routinely beat the hourly rate. Plus why spot capacity is wrong for serving.
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ModelsMixture-of-Experts vs Dense Models: Which Fits Your Hardware
MoE gives you a small model's speed with an enormous model's memory footprint. That tradeoff decides more deployments than quality does.
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ModelsOpen-Weight vs Closed Models: The Decision Isn't Capability
Benchmark parity is real for routine work. The choice turns on residency, version pinning, and where your cost curves cross.
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PlatformsLLM Gateways Reviewed: Adopt One at Your Second Provider
Routing, failover, caching, and the spend attribution nobody else provides — against a new single point of failure.
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ToolsLLM Eval Tooling: Four Categories, and the Two That Matter
A held-out task set and twenty assertions beat any platform bought without one. Plus the judge biases that invalidate scores.
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PlatformsInference Providers Compared: Price Is the Wrong First Question
Rate limits and p99 latency decide more deployments than per-token pricing. Plus why identical weights serve differently.
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ModelsAI Image Generation Models Compared: Speed, Control, and Cost
How current image models differ on prompt adherence, editing control, and what a batch of images actually costs. Model Drop breaks down what actually matters.