GPT-6.1 Sol pricing: OpenAI's frontier tier at a mid-tier rate card

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$2 / $10

per million tokens in / out, OpenAI Standard rates for short-context requests

60%

below Claude Opus 5 on both input ($5) and output ($25). Level with Claude Sonnet 5.5

$0.10

per million cached input tokens, 5% of the uncached input rate

GPT-6.1 Sol costs $2 per million input tokens and $10 per million output as of October 1, 2026. That matches Claude Sonnet 5.5 exactly and is 60% below Claude Opus 5. Cached input bills at $0.10 per million, 5% of the uncached rate.

How much does GPT-6.1 Sol cost?

$2 per million input tokens, $10 per million output, and $0.10 per million for cached input (OpenAI pricing). These are Standard rates for short-context requests, verified October 1, 2026. The API model id is gpt-6.1-sol.

What the rate card does to one request

Take a request with 10,000 input tokens and 2,000 output tokens. On GPT-6.1 Sol that is $0.020 of input plus $0.020 of output, $0.040 in total. The same token counts cost $0.040 on Claude Sonnet 5.5, $0.100 on Claude Opus 5 and $0.200 on Claude Fable 5. This is arithmetic on list prices, not a measurement. Models write different amounts for the same prompt, so a real bill depends on each model's verbosity for your prompts. We have not metered Sol; our Verbosity Index covers the models we have.

Sol vs the market

List prices per million tokens from prices.json, where each entry carries its own verification date. Measured per-task bills for the Claude models are in the market breakdown; we have none for GPT-6.1 Sol.

When Sol is the right buy

Price is one column. Against Sonnet 5.5 the rate cards are identical, so the choice comes down to which model clears your failure cases and which one writes fewer tokens doing it. If your stack is OpenAI-native and your prompts are tuned to the family, staying put is cheaper than a migration. The expensive mistake is the same one everywhere on this ladder: paying frontier rates on the large share of traffic that a volume tier handles identically. That allocation problem is the one we publish benchmark scores on.

GPT-6.1 Sol pricing questions, answered

No. Sol lists at $2 input and $10 output per million tokens; Opus 5 lists at $5 and $25. On the same token counts Sol costs 60% less. Full bills also depend on how many tokens each model writes for your prompts, which is why measured task costs beat rate-card math.

Cached input bills at $0.10 per million tokens, 5% of the $2 uncached rate. An 8,000-token system prompt served from cache costs $0.0008 per request instead of $0.016. Stable system prompts and shared context get the most out of it.

The list rates are identical: $2 input and $10 output per million tokens. Cached reads differ: $0.10 per million on Sol, $0.20 on Sonnet 5.5. With rates tied, the deciding factors are quality on your traffic and how many tokens each model writes.

Sol is OpenAI's frontier tier at $2/$10 per million tokens. GPT-6 Luna is the volume tier at $0.10/$0.50, one twentieth of Sol's rates. Routine classification and extraction belong on Luna, with escalation to Sol for the requests Luna gets wrong.

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