Migrate to GPT-5.5 now, or stay on 5.4?
GPT-5.6 Terra matches GPT-5.5 performance at half the price, while new enterprise plans charge full API token prices for GPT-5.5, exposing engineering teams to the full financial impact of token-intensive workflows.
The question
Should our engineering team migrate to GPT-5.5 immediately, stay on GPT-5.4 to preserve our cost line, or route by workload — accepting a 2× token-price hit on the calls that benefit from the new model?
Counsel's position
Route LLM calls by workload, prioritizing GPT-5.6 Terra for high-value tasks to gain performance at half the cost, while preserving GPT-5.4 for others.
Verdict
The verdict: Route LLM calls by workload, prioritizing GPT-5.6 Terra for high-value tasks to gain performance at half the cost, while preserving GPT-5.4 for others.
GPT-5.6 Terra matches GPT-5.5 performance at half the price
As you weigh the 2x price hit of GPT-5.5, OpenAI's newly announced Terra model offers a looming alternative for high-performance routing at GPT-5.4's cost level.
GPT-5.6 models report strong token-efficiency gains over GPT-5.5
As you consider the token-price hit of GPT-5.5, the upcoming GPT-5.6 family demonstrates that token efficiency is becoming a primary cost-control lever.
GPT-5.6 prompt caching offers a discount on subsequent reads
For engineering workloads that repeatedly pass massive codebases into the context window, prompt caching fundamentally alters the cost calculus of newer models.
Enterprise plans now charge full API token prices for GPT-5.5
You cannot rely on legacy enterprise seat discounts to absorb the 2x price increase of GPT-5.5.
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