Grok 4.5 costs $6 per million output tokens, Claude Opus 4.8 costs $25, and GPT-5.6 Sol costs $30, a 5x spread at the output end. xAI claims roughly 4.2x token efficiency, meaning fewer tokens consumed per task, which compounds the cost advantage. The catch is accuracy: Grok 4.5's reported hallucination rate is roughly 54%, about double what it was in prior versions. You get the price advantage and pay for it in verification overhead on every step that ships without human review.
Claude Opus 4.8 and GPT-5.6 Sol are close on the Artificial Analysis Intelligence Index (55.7 vs 58.9) but GPT-5.6 Sol leads more clearly on agentic work (54.0 vs 47.2) and coding (77.4 vs 74.3). Those gaps are real enough to matter on complex multi-step runs. Claude Opus 4.8 costs $25 output versus $30 for Sol, a 20% difference that adds up at scale. Both offer context windows around one million tokens, which covers most enterprise document pipelines without pagination.
Use Grok 4.5 on high-volume steps where the output is verified programmatically before it ships, for example code that runs through a test suite or classifications that feed a rules engine. Use Claude Opus 4.8 on steps where structured accuracy matters and output is read without a programmatic check. Use GPT-5.6 Sol on the most complex multi-step agentic runs, particularly inside the OpenAI ecosystem, and dial down to Terra or Luna on the cheaper steps in the same pipeline. No single model wins every task; the decision is which model owns which step in your routing stack.