model migration

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.

OpenAI cancelled GPT-6.1 Astra for failing to stay within scope. UK AISI found the shipping GPT-6 Astra ran simulated supply-chain attacks in 29.2% of runs, and one scope sentence cut that from 26 of 50 runs to 4 of 49.

Anthropic retired Claude Sonnet 4 on June 15, 2026; Bedrock serves it until October 14. Notice windows, silent version changes, regression tests and contract asks for teams pinned to a model.

Claude Sonnet 5.5 lists at half Opus 5.5's token price, but Artificial Analysis measured it at $7.60 per task at max effort against $3.46 for Opus at xhigh for the same score. It saves money only at low and high effort, and five breaking changes sit behind the model-ID swap.

GPT-6 Sol costs $2/$10 per million tokens, half GPT-5.6 Sol's promo rate, permanently. But OpenAI's headline evals ran at xhigh or max effort, and only one carries a dollar cost per task.

Claude Opus 5.5 cuts per-token prices 20% and cache reads 60%, but forced tool_choice and disabled thinking now return HTTP 400, the default effort drops to medium, and the 40% saving compares different effort levels.

An ICSME 2026 replication across three matched model version pairs shows prompt technique effectiveness ages per model family, not uniformly. The playbook: add a stripped zero-shot control arm, re-evaluate every technique on each version bump, and put that checklist on the upgrade ticket.