gemini-3.5-flash vs gpt-5.6-sol

Capability for the money

gemini-3.5-flash is 3.3× cheaper than gpt-5.6-sol and scores higher on tool use (τ²-bench) — there is no case for paying more here.

1. Following instructions

   extraction, classification, sticking to a format

   IFBench
   gemini-3.5-flash76.3%

   gpt-5.6-sol72.7%

   gemini-3.5-flash +3.6

2. Tool use

   multi-step agent work against real tools

   τ²-bench
   gemini-3.5-flash95.3%

   gpt-5.6-sol85.1%

   gemini-3.5-flash +10.2

3. Hard reasoning

   graduate-level science and multi-step analysis

   GPQA Diamond
   gemini-3.5-flash92.2%

   gpt-5.6-sol94.1%

   gpt-5.6-sol +1.9

Averaged over the benchmarks both models sat, gemini-3.5-flash returns 26.1 points of pass rate per dollar of blended price against 7.5 — the ratio that decides whether the dearer model earns its rate.

Each figure is a pass rate: the share of that test set the model answered correctly, measured by a third party rather than self-reported by the lab. Rows are different tests of different difficulty, so compare a model against the other model, not one row against the next. No published coding score for one of these models, so that lens is omitted. And a benchmark is not your workload — it narrows the shortlist, it does not pick for you.