Claude Opus 5 (Adaptive Reasoning, Max Effort) vs GPT-5.5 (xhigh): The Ultimate Performance & Pricing Comparison

Claude Opus 5 is the stronger default for developers who prioritize measured coding and general intelligence at a lower blended cost. Artificial Analysis gives Claude Opus 5 an intelligence index of 60.7 and a coding index of 78, compared with 54.8 and 74.9 for GPT-5.5 (xhigh). The same snapshot lists a blended price of $10 per 1M tokens for Claude Opus 5 and $11.25 for GPT-5.5. Data provided by https://artificialanalysis.ai/.

That result supports a default, not a universal winner. Anthropic positions Claude Opus 5 for complex agentic coding and enterprise work, with adaptive thinking and broad deployment options across its documented platforms. Anthropic’s launch announcement and model overview support that positioning. OpenAI positions GPT-5.5 for complex professional work, tool-heavy agents, long-context retrieval, and workflows that convert product specifications into plans. OpenAI’s GPT-5.5 guide describes the same model as a high-execution option for coding and knowledge work.

Lifecycle evidence also differs. Claude Opus 5 is listed as Active, with no deprecation date currently shown in Anthropic’s lifecycle documentation. Anthropic’s model deprecations page provides that explicit status. OpenAI’s current model directory has moved its front-facing recommendation toward GPT-5.6, while GPT-5.5 still has dedicated model and pricing documentation and no cited deprecation announcement. OpenAI’s model directory and GPT-5.5 model documentation show that mixed status. Developers should therefore treat Opus as the clearer current default, while validating GPT-5.5 when OpenAI-specific tooling changes the economics or implementation effort.

Claude Opus 5 is the better value-performance choice, while GPT-5.5 is the more natural fit for teams already invested in OpenAI’s tool and API stack.

The comparison points toward Claude Opus 5 for teams seeking a strong general-purpose coding agent with lower measured usage cost. The Artificial Analysis snapshot supports that conclusion, but it does not explain how either index maps to a specific repository, tool policy, or acceptance test.

GPT-5.5 retains a meaningful architectural advantage for OpenAI-native applications. Its documentation covers Responses, Chat Completions, Batch, structured outputs, function calling, file search, hosted shell, Computer Use, Skills, and MCP. The GPT-5.5 model page documents that surface. Claude Opus 5 supports text and image input, text output, long-context work, adaptive thinking, and several deployment providers. Anthropic’s model overview describes those capabilities. The evidence is insufficient to rank the two platforms by total engineering effort without knowing the tools, permissions, and hosting path already present in a team’s stack.

Claude Opus 5 is the measured performance winner in this snapshot, but GPT-5.5 remains credible for tool-heavy work.

The coding and intelligence gaps shown in the comparison matter most when the model must maintain a plan, inspect a repository, reason across dependencies, and produce an accepted change. They do not prove that Claude Opus 5 will complete every coding task more accurately. Artificial Analysis provides a useful directional signal, while Anthropic’s official announcement and OpenAI’s official announcement report different vendor-selected benchmark suites. Anthropic highlights agentic coding, desktop interaction, automation, and scientific tasks. OpenAI highlights terminal work, software engineering, browsing, computer use, tool use, mathematics, and cyber evaluation. The task definitions and evaluation conditions are not identical, so vendor results cannot create a clean head-to-head ranking by themselves.

The reported latency metric is tied at 0.3 seconds, so the supplied data does not identify a latency winner. Claude Opus 5 has a median output speed of 60.088 tokens per second, but GPT-5.5 has no comparable value in the snapshot. The evidence is therefore insufficient for a complete streaming-speed conclusion. A developer building an interactive editor should measure time to first useful action, tool-call cadence, interruption behavior, and total wall-clock completion on representative tasks.

Community evidence points in opposite directions. Some Claude Code users describe Opus 5 as strong on complex work and long workflows, while others report excessive verbosity, slow progress, overthinking, and scope expansion. The Claude Code discussion and the Claude AI discussion contain those conflicting experiences without reproducible test methods. GPT-5.5 users report useful architecture and debugging help, but also terse explanations and fragile implementation choices. The Codex discussion supports that warning. These reports are useful for test design, not for declaring a universal winner.

Claude Opus 5 is the cost winner for the blended workload represented by the snapshot, but workload shape can reverse the budget decision.

The key signal is the $10 versus $11.25 blended price. Input pricing is tied, so the difference comes from output economics. That favors Claude Opus 5 for agents that produce long plans, extensive explanations, or repeated code changes. It does not guarantee a lower invoice if the cheaper model causes more retries, larger tool traces, or additional human review.

The pricing structures also reward different application designs. Claude Opus 5 offers separate prompt-cache write and cache-hit economics, plus a minimum prompt length for creating a cache entry. Anthropic’s pricing page and Opus API notes make those constraints relevant for applications with stable system prompts. GPT-5.5 has no separate cache-write price, but its pricing documentation distinguishes Standard, Batch, Flex, and Fast modes. Long-context sessions can also trigger documented pricing multipliers. OpenAI’s pricing page explains those rules.

Platform availability can alter the practical price. Claude fast mode is a research preview and is not available through every documented provider. GPT-5.5 exposes separate service modes and OpenAI-native tools that may reduce integration work for an existing OpenAI deployment. Conversely, moving a Claude workflow to a different provider may introduce operational changes even if token prices appear attractive.

The right cost test is therefore not a static price lookup. Replay a representative mix of short answers, tool calls, repository edits, retries, cached context, and long outputs. Track accepted task completion, total tokens, human corrections, and wall-clock time. The supplied data establishes Opus as the cheaper blended option, but it does not establish which model produces the lower total cost of ownership for a specific application.

Claude Opus 5 is the recommended first trial for most teams choosing between these two models.

The reasoning controls are also not interchangeable. Claude Opus 5 defaults to adaptive thinking in the documented API behavior, with effort controls that affect how much reasoning the system attempts. GPT-5.5 exposes reasoning.effort, and xhigh is a parameter setting rather than a separate model identity. Anthropic’s Opus notes and OpenAI’s GPT-5.5 guide support that distinction. Treating Max Effort and xhigh as equivalent would make the comparison less reliable.

A constrained pilot should give both models the same repository state, tools, permissions, stop conditions, test commands, and acceptance criteria. OpenAI explicitly recommends defining reuse requirements, delegation rules, testing expectations, and stopping behavior for coding agents. The GPT-5.5 guide supports that practice. Anthropic’s documented behavior changes also make output length and tool behavior important test dimensions. The Opus release notes describe longer responses, more progress narration, and more active delegation.

Choose Claude Opus 5 first unless OpenAI-native tools, existing deployment contracts, or a measured product requirement makes GPT-5.5 materially easier to operate. Keep the final choice conditional on accepted work, not on benchmark prestige or anecdotal speed.

Claude Opus 5 is the cleaner pre-FAQ recommendation because the public comparison favors its quality and blended cost, while speed and task-specific behavior remain undermeasured.

The supplied snapshot establishes a quality and price direction, but it does not provide a shared tool-use benchmark, a complete GPT-5.5 output-speed value, or a total-cost model for retries and human review. Artificial Analysis supplies the comparative figures. The vendor announcements use different benchmark suites, and community discussions lack standardized test methods. Anthropic’s announcement and OpenAI’s announcement should therefore be read as context, not as a substitute for a controlled pilot.