GPT-5.5 vs GPT-5.6 Sol — Side-by-side pricing
Side-by-side API pricing and tokenizer details for GPT-5.5 (OpenAI) and GPT-5.6 Sol (OpenAI).
Side-by-side pricing
| Feature | GPT-5.5 | GPT-5.6 Sol |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Input (per 1M tokens) | $5.00 | $5.00 |
| Output (per 1M tokens) | $30.00 | $30.00 |
| Long-context pricing | Over 272K tokens: $10.00 in / $45.00 out | Over 272K tokens: $10.00 in / $45.00 out |
| Context caching | Yes — 90% off cached tokens | Yes — 90% off cached tokens |
| Batch API discount | 50% off | 50% off |
| Context window | 1.1M tokens | 1.1M tokens |
| Tokenizer | o200k_base (tiktoken) | o200k_base (tiktoken) |
Real-world cost example
1,000 API requests per month, each with 500 input tokens and 200 output tokens (500K input + 200K output total).
GPT-5.5
$8.5000
Input: $2.5000 +Output: $6.0000
GPT-5.6 Sol
$8.5000
Input: $2.5000 +Output: $6.0000
Frequently asked questions
Both models cost the same for this workload ($8.5000).
GPT-5.5 supports a 1.1M token context window. GPT-5.6 Sol supports a 1.1M token context window. A larger context window lets you include more text — documents, conversation history, or code — in a single API call.
GPT-5.5 supports context caching (90% off repeated tokens). It offers a 50% Batch API discount. GPT-5.6 Sol supports context caching (90% off repeated tokens). It offers a 50% Batch API discount.
Yes, both GPT-5.5 and GPT-5.6 Sol use the o200k_base (tiktoken). The same text produces identical token counts on both models, so any cost difference is purely due to the rate each provider charges per token.
GPT-5.5 (OpenAI): $5 input / $30 output per 1M tokens. GPT-5.6 Sol (OpenAI): $5 input / $30 output per 1M tokens. Rates shown before caching or batch discounts.
Both models cost the same for an 80% output / 20% input workload: $25.0000 per 1M total tokens. For your exact ratio, paste a real prompt into the calculator above.
GPT-5.5 has a 1.1M-token context window — approximately 788K words or ~3K pages of standard text. GPT-5.6 Sol has a 1.1M-token context window — approximately 788K words or ~3K pages. (Estimates assume ~0.75 words per token.)
Calculate costs for your actual prompt
Paste your prompt into the calculator and get exact token counts using each model's real tokenizer — all in your browser.
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