OpenAI GPT-5.6 Sol (1M) vs Google Gemini 3.6 Flash (1M)
Side-by-side comparison of pricing, context window, capabilities, and a real-cost sample workload.
Option A
OpenAI GPT-5.6 Sol (1M)
by OpenAI
Context:1M
Input:$12.00 / 1M
Output:$72.00 / 1M
Released:2026-07
Option B
Google Gemini 3.6 Flash (1M)
by Google
Context:1M
Input:$0.50 / 1M
Output:$3.00 / 1M
Released:2026-07
Detailed Comparison
| Dimension | OpenAI GPT-5.6 Sol (1M) | Google Gemini 3.6 Flash (1M) |
|---|---|---|
| Provider | OpenAI | |
| Context window TieTie | 1M | 1M |
| Input price ($/1M) Winner | $12.00 | $0.50 |
| Output price ($/1M) Winner | $72.00 | $3.00 |
| Sample workload cost Winner 1M input + 500K output tokens | $48.00 | $2.00 |
| Released TieTie | 2026-07 | 2026-07 |
| Tokenizer | o200k_base | gemini |
The verdict
On the dimensions we measured, Google Gemini 3.6 Flash (1M) wins more often - particularly on cost-effectiveness for a typical 1M+0.5M workload.
OpenAI GPT-5.6 Sol (1M) - Key features
OpenAI's Sol tier for GPT-5.6: a long-thinking configuration that spends far more reasoning tokens per request and tops OpenAI's own agentic and math evaluations. Priced as a premium reasoning endpoint.
- Extended reasoning by default
- ~1M token context window
- 128K max output tokens
- Parallel tool calling
- Priority processing tier
Google Gemini 3.6 Flash (1M) - Key features
The fast, cheap tier of Gemini 3.6. Flash keeps a 1M token window and multimodal input while running several times faster than Pro, which makes it the default choice for high-volume production traffic.
- 1M token context window
- Very high throughput
- Multimodal input (text, image, audio, video)
- Context caching
- Thinking budget control
How to choose
- Pick the cheaper model if your workload is mostly straightforward classification, extraction, or summarization.
- Pick the bigger context if you process long documents, large codebases, or multi-document research.
- Pick the more recent release if you need state-of-the-art reasoning quality and don't mind paying a bit more.
- Use both via a routing layer - send simple tasks to the cheaper one and complex tasks to the smarter one. This is the highest-ROI optimization in production AI.
Estimate the real cost of either model for your prompts using our Token Calculator.