At standard API rates, GPT-5.6 Sol and Claude Opus 5.5 cost exactly the same. GPT-6.1 Sol costs half as much per token. The catch is that context length, caching, and throughput are three different things. A model advertising a million-token context window is not promising you a million tokens of free usage—or a million tokens per minute.
Put the prices on the same receipt
These are standard USD prices per one million billed tokens as of October 25, 2026.
| Model | Input | Output | Cached input |
|---|---|---|---|
| GPT-5.6 Sol | $4 | $20 | $0.40 |
| Claude Opus 5.5 | $4 | $20 | $0.20 |
| GPT-6.1 Sol | $2 | $10 | $0.10 |
| GPT-6 Astra | $10 | $50 | $1.00 |
| Claude Fable 5.1 | $10 | $50 | $0.25 |
Opus 5.5 halves the cost of cache hits compared with GPT-5.6 Sol, while GPT-6.1 Sol halves ordinary input and output prices compared with either of them. Astra and Fable 5.1 occupy the same premium price bracket.
Equal per-token rates do not guarantee equal bills for identical text. The providers tokenize text differently, and the amount of billed reasoning or repeated work can change. Anthropic specifically notes that its newer tokenizer produces more tokens for equivalent text than older Claude generations. A published rate card is a price per unit, not a stopwatch or a quality benchmark.
What does a 12-language publishing job cost?
Imagine an article workflow using 10,000 input and 3,000 output tokens per language, repeated across 12 languages. Assume no cache hits, tools, long-context surcharges, or rework. This is a mathematical example, not observed spending.
| Model | One language | 12 languages |
|---|---|---|
| GPT-5.6 Sol / Claude Opus 5.5 | $0.10 | $1.20 |
| GPT-6.1 Sol | $0.05 | $0.60 |
| GPT-6 Astra / Claude Fable 5.1 | $0.25 | $3.00 |
The moment you ask the model to redo a translation, check citations, or ingest a lengthy editorial guide, your total changes. The AI may finish the draft in seconds; the invoice does not charge by how impressed you were.
Context window versus rate limit: two different meters
OpenAI lists a 1,050,000-token context window and up to 128,000 output tokens for these Sol/Astra models. Claude Opus 5.5 and Fable 5.1 list a 1,000,000-token context window and the same 128,000 output-token maximum. That's roughly how much the model can handle in one request, not its allowance per minute.
For GPT-5.6 Sol and GPT-6.1 Sol, requests with more than 272,000 input tokens are charged 2× for all input and 1.5× for output across the entire request. For Opus 5.5 and Fable 5.1, standard per-token pricing extends across the full million-token context window. If you routinely send very large repositories, the cheapest model on a short prompt might not be the cheapest on a giant one.
Now the speed limits: OpenAI's initial paid Build tier lists up to 5,000 requests/minute and 1 million tokens/minute for Astra/Sol, with a $500 monthly usage cap. Anthropic's Start tier lists 1,000 requests/minute, 2 million input tokens/minute and 400,000 output tokens/minute for Opus 5.5, also with a $500 monthly cap. Those counters are defined differently. Cache behavior, shared limits and your organization's actual settings matter more than a misleading addition of the two numbers.
Caching, batching, and the bill that sneaks up on you
With a reusable long prompt, include both the cost to write a cache entry and the cost to read it. Opus 5.5 charges $5 per million tokens for a five-minute cache write, $8 for a one-hour write, and $0.20 for a hit. GPT-6.1 Sol charges $2.50 for a write and $0.10 for a hit. The number and timing of reuses decide whether caching pays off.
Both providers offer 50% off standard input and output prices through their Batch APIs for work that can run asynchronously. A bulk translation job is an obvious candidate. API billing is separate from ChatGPT or Claude chat subscriptions.
The real winner is the completed result
For ordinary token-heavy generation, GPT-6.1 Sol leads on sticker price. GPT-5.6 Sol and Opus 5.5 tie on uncached standard rates. Opus 5.5 has an advantage on huge prompts without a long-context price jump. Astra and Fable 5.1 tie per billed token in the premium bracket.
But if the cheaper model needs three rewrites, it may be more expensive to finish the job. Measure billed input, billed output, retries, tools, and review work per accepted article. Selecting an AI model turns out to be less like buying a brain and more like interviewing an employee. The lowest salary on the sheet is not always the lowest cost of getting the work done.
Official sources (checked October 25, 2026): OpenAI pricing · GPT-6.1 Sol · OpenAI rate limits · Claude pricing · Claude rate limits · Claude context windows
