GPT-6.1 Sol (xhigh) vs GPT-6 Astra (high)

GPT-6.1 Sol (xhigh) and GPT-6 Astra (high) serve similar evaluation needs, but the useful difference is not the brand name. It is how the benchmark profile, latency, and token pricing line up with the work a reader actually wants to run.

What the benchmarks show

GPT-6.1 Sol (xhigh) has the stronger overall benchmark position in Franklin AI's current dataset, with an intelligence index of 51.0 compared with 50.9 for GPT-6 Astra (high). That makes GPT-6.1 Sol (xhigh) the clearer default when a workflow depends on the highest available reasoning score. The rest of the table still matters, because coding, math, and individual benchmark rows can point to a different choice for narrow use cases.

Speed and cost

Pricing and responsiveness can change the decision even when one model leads on the headline index. A model with a lower blended token cost may be easier to use at scale, while a model with faster first-token response can feel better in interactive products. The benchmark table below keeps those tradeoffs visible instead of reducing the comparison to one score.

Which model fits which workflow

Choose GPT-6.1 Sol (xhigh) when the work benefits from the stronger benchmark profile and the cost profile still fits the project. Choose GPT-6 Astra (high) when its provider ecosystem, latency, or pricing better matches the way the model will be used. The best choice is the one whose advantage appears in the rows that map to the actual workload.

Decision takeaway

For most readers, GPT-6.1 Sol (xhigh) is the stronger benchmark pick today. GPT-6 Astra (high) remains worth considering when budget, speed, provider preference, or a specific benchmark row matters more than the overall intelligence index.