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.
How the criteria decide
3 of 3 criteria resolved on cited evidence.
| Criterion | Favours | Evidence |
|---|---|---|
| GPT-5.5 vs GPT-5.4 migration trade-offs | Route by workload | GPT-5.6 Terra matches GPT-5.5 performance at half the price Offering the performance of the previous generation frontier model at half the price shows that OpenAI is no longer just competing in the "who makes the best model" race Artificial Intelligence on Medium GPT-5.6 models report strong token-efficiency gains over GPT-5.5 OpenAI says Terra matches GPT-5.5 at half the price, and the GPT-5.6 family is making strong token-efficiency claims. Enterprise plans now charge full API token prices for GPT-5.5 as of April 2026 the “Enterprise” cost for both OpenAI Codex and Anthropic Claude Code/Cowork is the same as the listed API price. |
| per-workload LLM routing strategies | Route by workload | GPT-5.6 Terra matches GPT-5.5 performance at half the price Offering the performance of the previous generation frontier model at half the price shows that OpenAI is no longer just competing in the "who makes the best model" race Artificial Intelligence on Medium GPT-5.6 models report strong token-efficiency gains over GPT-5.5 OpenAI says Terra matches GPT-5.5 at half the price, and the GPT-5.6 family is making strong token-efficiency claims. GPT-5.6 prompt caching offers a discount on subsequent reads Developers can now implement explicit cache breakpoints, backed by a guaranteed 30-minute minimum cache lifetime. |
| OpenAI token-pricing economics at $30K/mo+ scale | Route by workload | GPT-5.6 Terra matches GPT-5.5 performance at half the price Offering the performance of the previous generation frontier model at half the price shows that OpenAI is no longer just competing in the "who makes the best model" race Artificial Intelligence on Medium GPT-5.6 models report strong token-efficiency gains over GPT-5.5 OpenAI says Terra matches GPT-5.5 at half the price, and the GPT-5.6 family is making strong token-efficiency claims. GPT-5.6 prompt caching offers a discount on subsequent reads Developers can now implement explicit cache breakpoints, backed by a guaranteed 30-minute minimum cache lifetime. |
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.
Read another verdict
- Which process should we point AI at first?
- Put one person in charge of AI — or is a Head of AI premature for us?
- Buy a tool for this process, or build around our own knowledge?
- Centralize AI strategy under CEO or distribute ownership?
- Adopt new AI ROI tools or refine existing methods?
- Invest in pre-build costing or post-deployment ROI tracking?
- Our documents are a mess. Clean them up before AI, or after?
- How do we measure the return on an AI workflow — and what baseline is honest?