GPT-6 Sol
- Input / 1M tokens
- $2.00
- Output / 1M tokens
- $10.00
API models · Side by side
GPT-6 Sol vs GPT-6.1 Sol
An upgrade comparison for applications already using GPT-6 Sol. Compare the exact versions before replacing a model ID in a working integration.
GPT-6.1 Sol
- Input / 1M tokens
- $2.00
- Output / 1M tokens
- $10.00
The short answer
Similar capacity and pricing do not make a version change invisible. The important question is whether your prompts, tool calls and response contracts behave as expected with GPT-6.1 Sol.
Compare the details
Compare context, supported inputs and usage costs. Highlighted rows show a difference.
| Feature | GPT-6 Sol | GPT-6.1 Sol |
|---|---|---|
| Input formats | file, image, text | file, image, text |
| Output formats | text | text |
| Context / position limit | 1,050,000 | 1,050,000 |
| Maximum output tokens | 128,000 | 128,000 |
| Developer features | Reasoning output, Completion limit, Output limit, Reasoning controls, Thinking effort, Response format, Seed, Structured output, Tool selection, Tool calling, Response length | Reasoning output, Completion limit, Output limit, Reasoning controls, Thinking effort, Response format, Seed, Structured output, Tool selection, Tool calling, Response length |
| Cached input / 1M tokens | $0.20 | $0.10 |
| Cache write / 1M tokens | $2.50 | $2.50 |
| USD input / 1M tokens | $2.00 | $2.00 |
| USD output / 1M tokens | $10.00 | $10.00 |
| Model identifier | openai/gpt-6-sol | openai/gpt-6.1-sol |
API pricing
Prices are in USD per million tokens. Input is what you send; output is what the model generates. Claude and ChatGPT subscriptions are billed separately.
GPT-6 Sol: long-prompt rates
- Long-prompt threshold: 272,000 prompt tokens. Input: $4.00 / 1M. Output: $15.00 / 1M.
GPT-6.1 Sol: long-prompt rates
- Long-prompt threshold: 272,000 prompt tokens. Input: $4.00 / 1M. Output: $15.00 / 1M.
Tools, images and additional reasoning can add charges. The examples below cover input and output tokens only.
Compare local modelsWhat those prices mean in practice
Each example uses the same token budget for both models. These are calculations, not measured workloads. Cache discounts, media, tools and extra reasoning are excluded.
| Workload | GPT-6 Sol | GPT-6.1 Sol |
|---|---|---|
| 1,000 short requestsPer request: 2,000 input + 500 output tokens | $9.00 | $9.00 |
| 100 document summariesPer request: 20,000 input + 1,000 output tokens | $5.00 | $5.00 |
| 10 long-document requestsPer request: 300,000 input + 2,000 output tokens | $12.30 | $12.30 |
Estimate = requests × (input tokens × input price + output tokens × output price) ÷ 1,000,000. Long-prompt rates are applied where the pricing data provides them. Real requests can use different amounts of output.
Beyond the price tag
Keep the version explicit
A model identifier is part of the application configuration. Replacing GPT-6 Sol with GPT-6.1 Sol is a deliberate version choice, even when the pricing table shows the same base figures. Record which version produced a saved output so later debugging is not based on an ambiguous GPT label.
Review the output contract
For a summarizer, look at required headings and omitted material. For a tool workflow, examine function arguments and error handling. For structured output, verify the schema consumed by the next service. Those concrete requirements are more useful than assuming a later version is automatically better for every existing request.
Budget beyond the headline rate
Context limits, cached reads and long-prompt tiers form a more complete cost comparison than input price alone. The worked examples hold token counts constant. If the new model generates longer answers or uses additional reasoning, your actual bill can change even when those examples are equal.
Common questions
Are these monthly subscription prices?
No. The table compares token charges for using these models in an application. Consumer subscriptions have their own prices and usage rules.
Do the cost examples include everything?
They include input and output token charges under the stated assumptions. Media, tools, additional reasoning and cache operations can add different charges.