GPT-5.6 Sol
OpenAIUpdated October 2026. GPT-5.6 Sol by OpenAI: $4.00/M cache-miss input, $20.00/M output tokens. Cached input: $0.4/M. Explicit cache writes: $5.00/M. Long-context pricing at or above 272K input tokens: $8.00/M input, $30.00/M output. 1.1M context, 128K max output. Vision & Function Calling. Free calculator + compare 40+ models.
Input Price
$4.00
cache miss / 1M tokens · Promotional through at least 2026-11-21
Cached Input
$0.4
per 1M tokens · Promotional through at least 2026-11-21
Output Price
$20.00
per 1M tokens · Promotional through at least 2026-11-21
Context Window
1.1M
tokens
Specifications
| Provider | OpenAI |
| Model ID | gpt-5.6-sol |
| Input Price | $4.00 / 1M cache-miss tokens |
| Cached Input Price | $0.4 / 1M tokens |
| Explicit Cache Write Price | $5.00 / 1M tokens |
| Output Price | $20.00 / 1M tokens · Promotional through at least 2026-11-21 |
| Long Context Threshold | 272K input tokens |
| Long Context Pricing | $8.00 / 1M cache-miss input, $0.8 / 1M cached input, $10.00 / 1M explicit cache writes, $30.00 / 1M output |
| Context Window | 1.1M tokens |
| Max Output | 128K tokens |
| Capabilities | textvisionfunction_callingstructured_output |
| Release Date | 2026-07-09 |
| Pricing Source | Official OpenAI pricing |
| Price Verified | 2026-10-02 · GPT-6.1 Sol is $2/$10 with $0.10/M cached input (half GPT-6 Sol). GPT-6 Astra also offers Ultrafast at 6x Standard. GPT-5.6 Sol promotional $4/$20 pricing lasts at least through 2026-11-21. |
| Notes | Previous-generation flagship. The gpt-5.6 alias routes to Sol. Promotional pricing is available at least through 2026-11-21; explicit cache writes cost 1.25x uncached input and requests above 272K input tokens use long-context pricing. |
Monthly Cost Estimates
Estimated monthly costs based on different daily usage levels (assuming 50% input / 50% output split). Input estimates use cache-miss pricing, so cache-heavy workloads can be lower.
| Daily Tokens | Monthly Cost | Annual Cost |
|---|---|---|
| 10K | $3.60 | $43.20 |
| 50K | $18.00 | $216.00 |
| 100K | $36.00 | $432.00 |
| 500K | $180.00 | $2160.00 |
| 1.0M | $360.00 | $4320.00 |
About GPT-5.6 Sol
GPT-5.6 Sol is a large language model by OpenAI. It features a 1.1M token context window with up to 128K tokens of output per request. The model supports 4 capabilities: text, vision, function_calling, structured_output.
At $4.00 per million cache-miss input tokens and $20.00 per million output tokens, GPT-5.6 Sol is positioned as a mid-range option in the OpenAI lineup. Repeated prefix input can be charged at $0.4 per million cached tokens. Use our Token Counter to estimate how many tokens your prompts use, and our Pricing Calculator to compare costs across all models.
GPT-5.6 Sol Key Details
- Pricing: $4.00/M cache-miss input tokens, $0.4/M cached input tokens, $5.00/M explicit cache writes, $20.00/M output tokens
- Context window: 1.1M tokens — one of the largest available
- Max output: 128K tokens per response
- Capabilities: text, vision, function_calling, structured_output
- Highlights: Previous-generation flagship. The gpt-5.6 alias routes to Sol. Promotional pricing is available at least through 2026-11-21; explicit cache writes cost 1.25x uncached input and requests above 272K input tokens use long-context pricing.
- Released: 2026-07-09
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FAQ
How much does GPT-5.6 Sol cost?
GPT-5.6 Sol costs $4.00 per million cache-miss input tokens and $20.00 per million output tokens. Cached input costs $0.4 per million tokens. For a typical workload of 100K input tokens/day and 50K output tokens/day, expect approximately $42.00/month before cache-hit savings.
What is GPT-5.6 Sol's context window?
GPT-5.6 Sol supports a context window of 1.1M tokens. This means your combined input prompt and output response can be up to 1.1M tokens. The maximum output per response is 128K tokens.
Is GPT-5.6 Sol good for my use case?
GPT-5.6 Sol supports text, vision, function_calling, structured_output. As a mid-range model, it balances capability and cost for most production use cases. Use our Pricing Calculator to compare with alternatives.