GPT-5.6 Sol
- Context
- 1,050,000
- Max output
- 128,000
- Input / MTok
- $4.00
- Cached / MTok
- $0.40
- Output / MTok
- $20.00
- Input types
- text + image
OPENAI UPGRADE PATH / VERIFIED 2026-10-04
Compare successive Sol generations on verified context, knowledge cutoff, reasoning controls and Standard API economics.
LIVE VERIFIED FACTS
DECISION FACTORS
Both publish a 1,050,000-token context window.
Both list image, text as input types.
For 100K uncached input + 10K output tokens, GPT-6 Sol is lower at $0.3 vs $0.6 (2.0× difference).
HOW TO DECIDE
Context, modalities and direct token economics are comparable from official sources. Coding quality, latency, reliability and agent success should be measured on your own acceptance tests before production routing.
Use representative prompts, files, tools and expected outputs from the workload you plan to ship.
Include retries, cached tokens, long-context rules and tool charges—not only headline input price.
Record hallucinations, tool errors, timeout behavior and human corrections alongside pass rate.
A portfolio can outperform a one-model policy when different task classes have different cost and capability needs.
INDEPENDENT EVALUATIONS
SXF does not infer quality from specifications or compare benchmark scores across different evaluator versions/configurations.
WHAT CHANGED
No post-baseline factual changes recorded for GPT-5.6 Sol, GPT-6 Sol since 2026-09-27.
QUICK ANSWERS
Both publish a 1,050,000-token context window.
For 100K uncached input + 10K output tokens, GPT-6 Sol is lower at $0.3 vs $0.6 (2.0× difference).
No. This page compares source-backed specifications and economics. Quality, latency and task success require workload-specific evaluation evidence.