GPT-6.1 Sol vs Claude Opus 5.5: API pricing, caching, and long prompts
Sol halves the base token bill for prompts up to 272,000 input tokens. Above that boundary, compare the full request again because its higher rates bring it much closer to Opus.
Sol costs half as much at base rates, but its long-prompt surcharge narrows the gap.
GPT-6.1 Sol charges half of Claude Opus 5.5's base input and output rates. That makes Sol the cheaper starting point for the same billed token counts, but it doesn't settle which model costs less per completed task. Retries, reasoning output, and prompt length can change the result. This comparison separates those workload choices from the published token prices and uses the same input, output, and cache assumptions for both models.
By TechCompare · Updated
Cost Comparison
Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.Prices are fetched live from OpenRouter and may include temporary promotional discounts not accounted for in our article and comparison figures.
Side-by-side specs
| Spec | GPT-6.1 Sol | Claude Opus 5.5 |
|---|---|---|
| Standard input per 1M tokens | $2.00 up to 272K input (better on this spec) | $4.00 |
| Standard output per 1M tokens | $10.00 up to 272K input (better on this spec) | $20.00 |
| Cache reads per 1M tokens | $0.10 up to 272K input (better on this spec) | $0.20 |
| 100K input + 5K output, no cache hits | $0.25 (better on this spec) | $0.50 |
| 100K input + 5K output, 50% cached input | $0.155 (better on this spec) | $0.31 |
| 300K input + 5K output, no cache hits | $1.275 (better on this spec) | $1.30 |
| Input / output above 272K input, per 1M | $4.00 / $15.00 | $4.00 / $20.00 |
| Context window | 1,050,000 tokens | 1,000,000 tokens |
| Provider Batch API discount | 50% | 50% |
How they differ
Standard input costs $2 per million tokens on Sol and $4 on Opus. Output costs $10 and $20, while cache reads cost $0.10 and $0.20. For 100,000 input tokens and 5,000 output tokens, the uncached totals are $0.25 and $0.50. With half the input read from cache, the token estimate becomes $0.155 on Sol and $0.31 on Opus. Sol changes tiers above 272,000 input tokens, applying double input and cache rates and 1.5 times the output rate to the whole request. Opus keeps standard rates within its 1M context window. At 300,000 input and 5,000 output tokens without cache hits, that brings Sol to $1.275 and Opus to $1.30. These examples exclude cache writes and tool fees. The embedded calculator uses live OpenRouter rates, which can depend on provider routing.
Verdict
Start by testing both models on a fixed set of your own tasks. Sol has a clear price advantage on short and medium prompts, including cached input. Opus needs to save enough failed calls, review time, or extra steps to offset that difference. For large prompts, the gap can be small enough that completion quality matters more than the headline input rate. Compare billed usage for successful results rather than assuming both models generate the same amount of reasoning.
Which should you pick?
Choose GPT-6.1 Sol
Use Sol when your evaluations show that it completes the required work reliably and most prompts stay at or below 272,000 input tokens. A workflow that reuses a stable prompt prefix keeps its lower cache-read rate useful. Include all model calls in the budget, including retries and follow-up tool turns, before deciding how much traffic to route to it.
Choose Claude Opus 5.5
Use Opus when your tested workflow completes with fewer errors or less manual review on it, or when you're processing large document sets within the Claude context window. Standard token rates stay flat across that window. Existing Claude integrations can also reduce migration work, but that convenience should be evaluated separately from the API token bill.