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GPT-5.6 Sol input token pricing reduced by 20%, output by 33%

🔄 Updated 1h ago
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Key points

  • GPT-5.6 Sol input tokens reduced to $4 per million.
  • Output tokens reduced to $20 per million.
  • Promotional pricing valid through November 21, 2026.
  • Prompts over 272K tokens have higher rates.

Pricing Update for GPT-5.6 Sol

GPT-5.6 Sol, the frontier model within the GPT-5.6 family, has undergone a significant price reduction. Input tokens are now priced at $4 per million, a 20% decrease from previous rates. Output tokens have seen an even larger reduction, now costing $20 per million, which is a 33% decrease.

Model Details and Aliases

GPT-5.6 Sol corresponds to the unsuffixed model tier found in earlier GPT-5 families. The 'gpt-5.6' alias routes requests directly to GPT-5.6 Sol, simplifying access for users. The model supports various reasoning effort levels, including none, low, medium (default), high, xhigh, and max.

Promotional Period and Special Conditions

The new promotional pricing for GPT-5.6 Sol is guaranteed to be available at least through November 21, 2026. Users should note that prompts exceeding 272,000 input tokens will incur different rates, specifically 2x for input and 1.5x for output on the full request. Additionally, cache writes are billed at 1.25 times the uncached input token rate.

Impact on AI Development

This pricing adjustment makes the advanced capabilities of GPT-5.6 Sol more economically viable for a broader range of applications and developers. The reduced cost of both input and output tokens can lower operational expenses for AI-powered services and products, potentially encouraging wider adoption and experimentation with the model's features.

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Reporting from

The GPT-5.6 Sol model now costs $4 per million input tokens and $20 per million output tokens, representing a 20% reduction in input pricing and a 33% reduction in output pricing. This pricing change makes the frontier model in the GPT-5.6 family more accessible for developers and applications, impacting the cost-effectiveness of integrating advanced AI capabilities.