Every THE D[AI]LY BRIEF article on LLM API pricing — enterprise AI analysis, benchmarks, vendor comparisons, and ROI frameworks for technology and business leaders. Updated as new coverage publishes.
An H100 running gpt-oss-120b at Lambda's $4.29 an hour must sustain 5,958 tokens per second every hour of the month to match a $0.20 blended API rate. Business-hours traffic leaves it at about twice the API's cost.
October 23, 2026 · 16 min read
Azure and Google now meter reserved model capacity at pay-as-you-go token weights, so a monthly term needs about 99% utilization to save money. Annual terms break even at 84% on Azure and 75% on Google; Bedrock publishes too little to compute.
October 22, 2026 · 15 min read
Claude Haiku 5.5 matches GPT-6 Luna at $0.10/$0.50 per million tokens and beats it on Anthropic's evals, but prompts over 100K tokens cost 5x and its tokenizer counts about 30% more tokens than Haiku 4.5. Short-prompt classification and routing get the big saving; compaction and long-context work get much less.
October 7, 2026 · 11 min read
Priced on one normalised agent workload, a month of inference costs $370 on GPT-5.6 Luna and $10,725 on Claude Opus 5. Output, reasoning and cache-read rates explain the gap, not the input price.
September 11, 2026 · 22 min read