GPT-5.6 Sol vs GPT-5 Pro

GPT-5.6 Sol is the better all-round choice, scoring 66/100 against GPT-5 Pro (54). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GPT-5.6 Sol is cheaper at $4.00 input / $20.00 output per million tokens (official OpenAI API price). GPT-5 Pro costs $15.00 input / $120.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $8.00 per million tokens for GPT-5.6 Sol versus $41.25 for GPT-5 Pro (5.2× as much).

GPT-5.6 Sol scores higher on the Capabilities Index (ECI): GPT-5.6 Sol 161.8 (#8 of 148) and GPT-5 Pro 150.3 (#46 of 148). Their confidence ranges do not overlap (159.3–165.3 vs 148.5–152.8), so the gap is a real one. On individual benchmarks: FrontierMath Tiers 1–3 — GPT-5.6 Sol 89.1%, GPT-5 Pro 55.8%.

There are no published SWE-bench Verified results for GPT-5.6 Sol and GPT-5 Pro yet, so there is no like-for-like coding score. On overall capability, GPT-5.6 Sol leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-5.6 Sol has the largest context window at 1,050,000 tokens, against 400,000 for GPT-5 Pro. Maximum output per response: GPT-5.6 Sol up to 128,000, GPT-5 Pro up to 272,000 tokens.

GPT-5.6 Sol accepts text, images and PDFs; GPT-5 Pro accepts text and images. GPT-5.6 Sol handles the widest range of inputs.

No. GPT-5.6 Sol and GPT-5 Pro are proprietary and only available through APIs and apps.

GPT-5.6 Sol is the newest, released Jul 9, 2026. GPT-5 Pro came out Oct 6, 2025. Knowledge cutoff: GPT-5.6 Sol Feb 16, 2026, GPT-5 Pro Sep 30, 2024.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.