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Fundamentals

Speculative Decoding in Practice: When It Pays Off

Speculative decoding is standard in serving stacks now, but the speedup is workload-dependent. What decides whether it helps you, and how to tell.

· 9 min read
Fundamentals

Stop Sequences Explained: Ending Generation on Purpose

How stop sequences work, why they interact badly with tokenisation and streaming, and the finish_reason check most integrations forget to make.

· 8 min read
Fundamentals

Synthetic Training Data: What It Does and Where It Fails

How generated data is used to train modern models, what distillation and self-instruct pipelines look like, and what the model-collapse evidence actually supports.

· 9 min read
Fundamentals

Test-Time Compute: Buying Accuracy With Tokens Instead of Size

Spending more computation at inference can substitute for a larger model. How the trade works, where it pays off, and what it does to your latency budget.

· 9 min read
Fundamentals

The Lost-in-the-Middle Problem: Position Beats Relevance

Models retrieve facts from the start and end of a long prompt far more reliably than from the middle. Why that happens and how to arrange prompts around it.

· 8 min read
Fundamentals

Throughput vs Latency: The Trade-off Behind Your Bill

Serving more tokens per second and serving them faster are opposing goals. The knob that reconciles them is batch size, and it decides both speed and price.

· 9 min read
Fundamentals

Time to First Token: What It Measures and What Moves It

TTFT is dominated by prefill compute, queueing and network distance rather than by model speed. What each contributes, and how to measure it without fooling yourself.

· 9 min read
Fundamentals

Token Costs by Language: Why the Same Text Bills Differently

The same sentence costs more in some languages than in English, and code has its own profile. Where the multiplier comes from and how to measure yours.

· 9 min read
Fundamentals

Tokenizer Differences: Why the Same Text Costs Different Amounts

Two models quoting the same price per million tokens can cost different amounts for identical text. Why tokenizers vary and what it does to your bill.

· 8 min read
Fundamentals

Tokens Per Second Explained: Reading the Number Correctly

Tokens per second means different things depending on who is measuring. What drives generation speed, why quoted figures disagree, and how to measure yours.

· 9 min read
Fundamentals

Top-K Sampling Explained, and Why Top-P Replaced It

Top-k cuts the tail at a fixed count, which is right sometimes and wrong often. How nucleus sampling adapts, and which knob to actually touch.

· 8 min read
Fundamentals

Transformer Architecture Explained for Working Developers

What a transformer block actually contains, why the design won, and which parts of it explain the behaviour you observe when using a model.

· 9 min read

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