Topic
Reasoning Models & Test-Time Compute
5 posts on reasoning models & test-time compute — part of glossary on the n4n AI blog.
What is test-time compute and why it matters
Test-time compute explained: what it is, how reasoning models use it, why it changes cost/latency tradeoffs, and what engineers get wrong about scaling inference.
What is a reasoning model?
A precise technical definition of reasoning models, how they use test-time compute, concrete examples with code, and the misconceptions engineers should avoid.
o3 vs GPT-5: what makes a reasoning model different
Technical comparison of o3 and GPT-5 reasoning models across capabilities, cost, latency, and ecosystem for engineers building LLM systems.
How Claude's extended thinking mode actually works
A practical guide to Claude's extended thinking mode — how it works, when to use it, and how to integrate it into production systems.
DeepSeek-R1 explained: how it thinks before answering
DeepSeek-R1 is a reasoning model that uses test-time compute to generate chain-of-thought before answering. Learn how it works, why it matters, and common misconceptions.
More topics in glossary
- Structured Outputs & JSON Mode19
- AI Agents Fundamentals12
- Hallucination in LLMs11
- Sampling Parameters: Top-p, Top-k & Penalties11
- Context Window & Context Length10
- Fine-Tuning Fundamentals9
- Foundation Models: Base vs Instruct vs Chat9
- Model Families & Naming Conventions: GPT-5, Claude, Gemini 3, Llama 4, Mistral, DeepSeek, Qwen, Grok9
- Grounding & Fact-Checking in AI8
- LLM Benchmarks: MMLU, HumanEval, SWE-bench & GPQA8
- Max Tokens, Stop Sequences & Output Truncation8
- Quantization Formats: GGUF, GPTQ, AWQ & INT4/INT88