Claude Opus 5.5 or GPT-6 Astra: prices, index and agent session cost

"Claude Opus 5.5 or GPT-6 Astra" is the choice facing anyone who gives a flagship model their hardest work: long agent sessions, large codebases, multi-step analysis. Here we compare the two on price, cache and strength index, then work out what one long agent session costs on each.

The two models in numbers

Prices are US dollars per 1M tokens, Zukko price list as of October 6, 2026.

The strength index is the Artificial Analysis Intelligence Index, an aggregate score over a set of benchmarks, shown in the Zukko catalog. We have no other quality figures and won't invent any.

Models and prices change: current ones are at GET https://api.zukko.pro/v1/models or on the "Models" page in your dashboard.

What the table shows

On Zukko prices, Opus 5.5 is cheaper than Astra on all four components:

• input: $0.4 vs $0.62, Astra costs 55% more (0.62 / 0.4 = 1.55);
• output: $2 vs $3.05, 52.5% more (3.05 / 2 = 1.525);
• cache read: $0.038 vs $0.063, about 66% more (0.063 / 0.038 ≈ 1.66);
• cache write: $0.425 for Opus 5.5; Astra has no separate write charge, and the context being written is billed at its input price of $0.62 — about 46% more (0.62 / 0.425 ≈ 1.46).

Opus 5.5 also has the higher strength index: 58 vs 53. The index is an average across benchmarks, not a guarantee for your task, but on both parameters we have, Opus 5.5 is formally ahead.

Claude Opus 5.5 or GPT-6 Astra: cost of a long agent session

On every step an agent sends the model its whole accumulated context: system prompt, tool definitions, history, command output. So most of the input in a long session is re-sent context, and the cache read price matters more than the input price.

Session model

• 60 steps (model requests);
• the context is 30,000 tokens on step one and grows by 4,000 per step (model reply plus tool results);
• each step has 200 tokens of fresh input and 1,200 tokens of output.

Context at step k: 30,000 + 4,000 × (k − 1). At step 60 that is 266,000 tokens.

Volumes:

• Cache read. At step k the context of step k − 1 is read from cache. Sum over steps 2…60 = 59 × 30,000 + 4,000 × (0 + 1 + … + 58) = 1,770,000 + 4,000 × 1,711 = 8,614,000.
• Cache write. 30,000 on step one, then 4,000 on each of the remaining 59 steps: 30,000 + 59 × 4,000 = 266,000. Astra has no separate write: these tokens are billed at the input price.
• Fresh input: 60 × 200 = 12,000.
• Output: 60 × 1,200 = 72,000.

Calculation

Formula: fresh input × input price + cache read × read price + cache write × write price + output × output price (volumes in millions of tokens). For Astra there is no cache-write line: new context is billed at the input price.

Exactly: $0.589182 and $0.934642. The difference is $0.34546 per session, or about 59% more for Astra (0.934642 / 0.589182 ≈ 1.59).

Using the same cache profile for both models is a simplification. In practice the cache share depends on the client, the provider and pauses in work: GPT models are cached on the provider's side, and the real number of cached tokens shows in usage.prompt_tokens_details.cached_tokens. If a lot of time passes between steps, the cache goes cold and the context is written again, which costs more than reading.

Without cache

If all input is billed at the input price (which is what happens, for example, when Claude is called through the OpenAI format), session input is 12,000 + 8,614,000 + 266,000 = 8,892,000 tokens:

• Opus 5.5: 8.892 × $0.4 + 0.072 × $2 = $3.5568 + $0.144 = $3.7008;
• Astra: 8.892 × $0.62 + 0.072 × $3.05 = $5.51304 + $0.2196 = $5.73264.

For Opus 5.5 that is $3.70 vs $0.59 with cache. The practical takeaway: for Claude the cache discount comes only with the Anthropic format (/v1/messages, Claude Code, Anthropic SDK), where the gateway sees how much input came from cache. In the OpenAI format (/v1/chat/completions) all Claude input is billed at the input price. For GPT models the cache is visible in both formats.

API format

• Opus 5.5 in agents is best connected in the Anthropic format: Claude Code, the Anthropic SDK, OpenCode with the anthropic provider. For Claude Code and the Anthropic SDK the base URL is https://api.zukko.pro without /v1; they add it themselves. Setup is in the Claude Code docs↗.
• Astra is native to the OpenAI format: the OpenAI SDK, Codex, Cursor, Cline and other clients with base URL https://api.zukko.pro/v1.

The gateway converts formats, so any model can be called either way. But for Claude with a long context, pick the Anthropic format or you lose the cache discount.

Example: computing the cost of one Opus 5.5 step from usage:

from anthropic import Anthropic

client = Anthropic(base_url="https://api.zukko.pro", api_key="fetch_...")
PRICE = {"in": 0.4, "out": 2, "read": 0.038, "write": 0.425}  # $ per 1M, claude-opus-5-5

resp = client.messages.create(
    model="claude-opus-5-5",
    max_tokens=2048,
    messages=[{"role": "user", "content": "Review this module and suggest a refactor: ..."}],
)
u = resp.usage
cost = (u.input_tokens * PRICE["in"]
        + (u.cache_read_input_tokens or 0) * PRICE["read"]
        + (u.cache_creation_input_tokens or 0) * PRICE["write"]
        + u.output_tokens * PRICE["out"]) / 1_000_000
print(f"${cost:.6f}")

How to choose

On the figures we have, Opus 5.5 is both cheaper and higher on the index, so it is a sensible starting point. The reason to try Astra is your own results: the index averages many tests, and your task may differ from the average. A comparison of Opus 5.5 with the most expensive Claude model is in the article Claude Fable 5.1 or Opus 5.5↗.

The check takes an evening:

1. Take 10–20 real tasks from your work: bugs you have already fixed, documents you have already analysed. The right answer should be known.
2. Run each task on both models in the same agent or script.
3. Mark which tasks were solved and what each run cost. Actual charges are in the dashboard under "Usage" and in the spending history API↗.
4. Compare cost per solved task: the model's total spend over all runs divided by the number solved.

It is handy to create a separate key for the experiment in the dashboard↗ with a daily limit, so test spend doesn't mix with production.

FAQ

Which is cheaper, Opus 5.5 or Astra?

On Zukko prices, Opus 5.5: its input, output and cache read are cheaper, and its cache write ($0.425) is cheaper than Astra's input price ($0.62), at which Astra bills new context. In our 60-step session model that is $0.589 vs $0.935.

Does an index of 58 vs 53 mean Opus 5.5 is better at my task?

No. The index is an aggregate benchmark score. It is a useful reference, but decide by running your own tasks.

Can I call Astra through the Anthropic format?

Yes, the gateway converts. For GPT models the cache is visible in both formats, so the price doesn't change.

Why is an Opus 5.5 session about 6.3 times pricier without cache?

In a long session almost all input is repeated context. With cache it is billed at $0.038 per 1M, without it at $0.4. Hence $3.7008 vs $0.589182 in our calculation (3.7008 / 0.589182 ≈ 6.28).