A 7B model that thinks for thirty seconds can outscore a 70B model that answers instantly. Test-time compute is the lever that makes this possible, and it is quietly rewriting the economics of model design.
Training a frontier model is a one-time expense measured in millions. Serving it to users is a perpetual expense measured in billions of tokens per day. For most organisations, inference is already the larger number, and the gap …
A guardrail is a classifier sandwich wrapped around your model, and every layer you add buys coverage with latency and false refusals. Here is how the layer actually works, what it costs, and where it breaks.
o3, R1 and Claude extended thinking are a real capability shift on a narrow slice of tasks. They are also being shoved into product surfaces that punish every property reasoning models exhibit - and the bill is starting to arrive.
For years, sparse attention was a bolt-on applied after training to shrink the KV cache. NSA, MoBA, and DeepSeek's DSA flip that order, training the sparsity end to end and reporting up to 11x faster decoding without losing accuracy.