Claude Opus 5.5 vs GPT-6 Astra: 2026 comparison

Claude Opus 5.5 and GPT-6 Astra in brief

Claude Opus 5.5 and GPT-6 Astra share a broad purpose: handling long inputs, reasoning and calling tools while accepting text, images and files. Their maximum output lengths match, but context capacity and token prices differ. Claude Opus 5.5 has lower listed input and output rates. GPT-6 Astra provides a slightly larger context window and higher scores on several supplied benchmarks. Those distinctions give you useful selection criteria, although neither the prices nor the benchmark results establish a universal winner.

Claude Opus 5.5 : Claude Opus 5.5 (Anthropic): $4 / $20 per million tokens, 1M context, benchmarks, verdict and alternatives. Checked October 25, 2026.

GPT-6 Astra : GPT-6 Astra (OpenAI): $10 / $50 per million tokens, 1.1M context, benchmarks, verdict and alternatives. Checked October 25, 2026.

Both meet the same need, which makes the comparison useful. We compare them on 11 verifiable criteria, using the same data as their profiles, collected from official sites, OpenRouter and Epoch AI.

Comparison table

Criterion by criterion

For each criterion: why it matters, each one's value and who has the edge. A criterion without data on both sides is not decided.

Capabilities (Epoch AI index)

Epoch AI's capabilities index rolls many benchmarks into one number: the higher, the better the model does on hard tasks. Claude Opus 5.5 : 168.8. GPT-6 Astra : 168.8. Edge: Claude Opus 5.5.

Shared benchmarks

On the benchmarks both models took, we count each one's wins. Claude Opus 5.5 : 0 of 6. GPT-6 Astra : 4 of 6. Edge: GPT-6 Astra.

Input price

The price of tokens sent to the model weighs heavily as soon as you send long documents or chat history. Claude Opus 5.5 : $4 / M tokens. GPT-6 Astra : $10 / M tokens. Edge: Claude Opus 5.5.

Output price

Generated tokens usually cost several times more; they dominate the bill for writing and code. Claude Opus 5.5 : $20 / M tokens. GPT-6 Astra : $50 / M tokens. Edge: Claude Opus 5.5.

Cost of a typical task

For a request of 2,000 input and 500 output tokens, repeated 30,000 times a month (1,000 a day). Claude Opus 5.5 : $540 per month. GPT-6 Astra : $1,350 per month. Edge: Claude Opus 5.5.

Context window

The context window sets how much text the model reads at once: useful for long documents and agents. Claude Opus 5.5 : 1M tokens. GPT-6 Astra : 1.1M tokens. Edge: GPT-6 Astra.

Max output

The maximum answer length matters to generate long code files or reports. Claude Opus 5.5 : 128K tokens. GPT-6 Astra : 128K tokens. A tie on this point.

Accepted inputs

Text, images, files, audio: the more formats accepted, the more cases covered without extra tools. Claude Opus 5.5 : 3. GPT-6 Astra : 3. A tie on this point.

Tool calling

Essential for an agent: the model can call functions, APIs or MCP servers. Claude Opus 5.5 : yes. GPT-6 Astra : yes. A tie on this point.

Open weights

Downloadable weights let you run the model yourself, without sending data to a provider. Claude Opus 5.5 : no. GPT-6 Astra : no. A tie on this point.

Release date

A newer model often has fresher data and better training techniques. Claude Opus 5.5 : September 22, 2026. GPT-6 Astra : September 4, 2026. Edge: Claude Opus 5.5.

In charts

Our analysis

Anthropic released Claude Opus 5.5 on 22 September 2026, while OpenAI released GPT-6 Astra on 4 September. Both list text, image and file inputs, reasoning support and tool calling. They can therefore be considered for applications combining document analysis with tool interaction. The supplied capabilities do not distinguish them by input modality or the presence of reasoning. Instead, the choice involves balancing context size, token spending and evaluation results. No response speed, deployment options or domain-specific performance figures are included. These gaps matter when translating a model specification into an application that must work with your documents and tools.

Claude Opus 5.5 lists a 1,000,000-token context window, compared with 1,050,000 for GPT-6 Astra. Both support up to 128,000 output tokens. Per million tokens, Claude costs USD 4 for input and USD 20 for output; GPT costs USD 10 and USD 50 respectively. GPT leads on GPQA, FrontierMath, SimpleQA and ARC2, while AIME and ARC1 are tied. The Epoch capability index nevertheless gives Claude 168.83 and GPT 168.81. These measures provide different perspectives rather than one clear ranking. The supplied records do not detail benchmark protocols, so the figures alone cannot establish which model will perform better in your application.

Both providers are listed as US-based, and neither model has open weights. No licence is specified in either record. These facts do not establish hosting locations, retention periods, whether submitted information is used for other purposes or which contractual terms apply. You therefore cannot compare privacy protections from this information alone. Closed weights also describe model openness rather than the route taken by your files or prompts. If you plan to process internal or sensitive material, the supplied data leaves those handling questions unresolved. Neither provider receives a demonstrated confidentiality advantage in this comparison on the basis of its country or weight availability.

In everyday work, GPT-6 Astra’s larger context window may matter when your inputs exceed Claude Opus 5.5’s stated capacity. Below that threshold, the additional space does not independently establish a practical advantage. Their matching output limits and shared input types also reduce differentiation on those dimensions. Claude’s lower token rates make the same stated input and output volumes less expensive. GPT’s stronger results on several benchmarks can guide your evaluation, but those tests do not describe your particular files or tool interactions. No latency figures or tool calling reliability measurements are supplied to resolve those operational questions.

Depending on your situation

The right choice depends on use. For a few common situations, here are the criteria that matter and who wins (Claude Opus 5.5 value / GPT-6 Astra value).

High request volume

Here, Claude Opus 5.5 has the edge: it wins 3 of the 3 criteria that matter in this situation, namely cost of a typical task ($540 per month / $1,350 per month), input price ($4 / M tokens / $10 / M tokens), and output price ($20 / M tokens / $50 / M tokens).

Hard tasks (reasoning, code)

Neither stands out on the criteria for this situation (capabilities (epoch ai index) (168.8 / 168.8), shared benchmarks (0 of 6 / 4 of 6), and max output (128K tokens / 128K tokens)): decide with a trial.

Agents and long documents

Here, GPT-6 Astra has the edge: it wins 1 of the 3 criteria that matter in this situation, namely tool calling (yes / yes), context window (1M tokens / 1.1M tokens), and accepted inputs (3 / 3).

Maximum privacy

Neither stands out on the criteria for this situation (open weights (no / no)): decide with a trial.

Which one to choose?

Choose Claude Opus 5.5 if…

• you value capabilities (epoch ai index) (168.8)
• you value input price ($4 / M tokens)
• you value output price ($20 / M tokens)
• you value cost of a typical task ($540 per month)
• you value release date (September 22, 2026)

Claude Opus 5.5 is a logical choice if token spending matters and a million-token context meets your needs. You retain reasoning, tool calling and the same maximum output length listed for GPT-6 Astra. Its marginally higher Epoch index adds context, but the small difference should not be treated as evidence of general superiority across your tasks.

Choose GPT-6 Astra if…

• you value shared benchmarks (4 of 6)
• you value context window (1.1M tokens)

GPT-6 Astra makes sense if you need its 1,050,000-token context or want to investigate the capabilities reflected in GPQA, FrontierMath, SimpleQA and ARC2. It leads Claude on those supplied results. You would be accepting higher input and output token prices, while receiving no listed increase in maximum output length over Claude Opus 5.5.

Strengths and limits of each

Claude Opus 5.5

• + Among the top 20% of models according to Epoch AI (ECI 168.8).
• + Very large context (1M tokens): long documents or a whole codebase fit in one request.
• + Agent-ready: tool calling and structured JSON output.
• − Expensive: costlier than 93 % of paid models.

GPT-6 Astra

• + Among the top 20% of models according to Epoch AI (ECI 168.8).
• + Very large context (1.1M tokens): long documents or a whole codebase fit in one request.
• + Agent-ready: tool calling and structured JSON output.
• − Expensive: costlier than 97 % of paid models.

The best test is still yours: take three real tasks from your day and give them to both for a week. The price calculator works out the gap on your own volume.

What about the others?

If neither suits you, look at GPT-6.1 Sol, Claude Fable 5.1, Gemini 4 Argon, Claude Sonnet 5.5, Claude Opus 5, and GPT-6 Sol.

Related comparisons:

• Claude Opus 5.5 vs GPT-6.1 Sol
• Claude Opus 5.5 vs Gemini 4 Argon
• Claude Opus 5.5 vs Muse Wonder
• GPT-6 Astra vs Gemini 4 Argon

Conclusion

Claude Opus 5.5 offers lower token prices; GPT-6 Astra offers more context and leads on four of the six listed benchmarks. Two tied tests and nearly identical Epoch scores argue against a blanket verdict. Base your decision on input size, token volume and evaluations relevant to your actual tasks. The supplied information does not determine which provides better privacy, lower latency or more reliable operation with your tools.