Claude Opus 4.5 Reasoning vs GPT-5 High: Which Model Should Developers Choose?

Claude Opus 4.5 (Reasoning) is the stronger general intelligence signal, while GPT-5 (high) offers clearer API documentation and much lower cost. The Artificial Analysis snapshot reports Claude Opus 4.5 at 40.8 on its Intelligence Index, compared with 34.7 for GPT-5 (high). GPT-5 (high) leads the Math Index at 94.3 versus 91.3, but Claude has no comparable coding score in the supplied snapshot. Artificial Analysis provides the comparative data used here.

The practical choice depends on what developers value most. Claude has the higher broad capability score, and Anthropic documents text and image input, multilingual ability, and vision support. Anthropic’s model overview confirms those supported capabilities.

GPT-5 (high) presents a more explicit engineering contract. OpenAI documents a 400,000-token context window, a maximum output of 128,000 tokens, configurable reasoning effort, structured outputs, function calling, and streaming. OpenAI’s GPT-5 model documentation lists these details. Developers therefore face a tradeoff between stronger comparative intelligence evidence and better documented integration behavior.

Claude Opus 4.5 (Reasoning) is the better default for tasks where broad reasoning quality matters more than price certainty or API detail. Its Intelligence Index is 40.8, which is higher than GPT-5 (high)'s 34.7 in the supplied comparison. That result does not prove superiority on every production workload, because the two models do not have identical published evidence.

GPT-5 (high) is the more economical production option. Its blended price is $3.4375 per 1M tokens, compared with $10 for Claude Opus 4.5. OpenAI also publishes a stable gpt-5 alias, a fixed snapshot, supported endpoints, reasoning controls, and tool features. GPT-5 for developers describes GPT-5 as a model for coding, reasoning, and agentic tasks.

Claude’s public documentation leaves important selection questions unanswered. The supplied official material does not state a concrete API ID, context window, maximum output length, extension-thinking parameter, tool-calling parameter, or official benchmark result for Claude Opus 4.5. That absence makes implementation planning harder, even though the model appears in Anthropic’s current pricing table.

GPT-5 also has a material lifecycle concern. OpenAI marks the fixed snapshot gpt-5-2025-08-07 as Deprecated and describes GPT-5 as a previous-generation model, while still listing gpt-5 as callable. GPT-5 model documentation supports this distinction. Developers should therefore separate current alias availability from long-term snapshot stability.

Claude Opus 4.5 (Reasoning) has the stronger broad capability signal, while GPT-5 (high) has the stronger supplied mathematics signal. The Intelligence Index favors Claude at 40.8 versus 34.7. The Math Index favors GPT-5 at 94.3 versus Claude at 91.3. These results suggest different strengths, but they do not establish a universal winner for software development.

For general planning, multi-step analysis, and tasks that mix interpretation with judgment, Claude’s higher Intelligence Index is the more relevant signal. For mathematical reasoning or workloads with formal quantitative structure, GPT-5’s higher Math Index may matter more. The supplied data does not include a Claude coding score, so the comparison cannot honestly claim that one model is superior for coding benchmarks overall.

OpenAI publishes coding evidence for GPT-5, including 74.9% on SWE-bench Verified and 88% on Aider polyglot. GPT-5 for developers explains that the SWE-bench result excluded 23 problems from a set of 500 because they could not be passed reliably on OpenAI’s infrastructure, and that Aider used high reasoning effort. Those qualifications make the results useful but prevent a direct apples-to-apples comparison with Claude.

Latency does not separate the models in the supplied data. Both report 0.3 seconds median latency. Median output speed is unavailable for both models, so the evidence cannot answer which model feels faster during long generations, streaming responses, or agent loops. Developers should measure their own workload before promising response-time improvements.

GPT-5 (high) is the clear price leader, but Claude Opus 4.5 may still be cheaper for workflows that finish in fewer iterations. The supplied blended price is $3.4375 per 1M tokens for GPT-5 and $10 for Claude Opus 4.5. GPT-5 also costs $1.25 for input and $10 for output per 1M tokens, while Claude costs $5 for input and $25 for output. These prices strongly favor GPT-5 for high-volume workloads with comparable task completion rates.

The price gap becomes less decisive when a cheaper model needs more retries, longer repair loops, or additional verification calls. The data brief does not provide retry rates, token consumption by task, or production success rates. Evidence is therefore insufficient to convert the listed prices into a reliable total-cost-of-ownership winner for a specific application.

Claude’s prompt caching can change the economics of repeated context. Anthropic lists a 5-minute cache-write price of $6.25 per MTok, a 1-hour cache-write price of $10 per MTok, and a cache-hit price of $0.50 per MTok. Claude pricing documents these values. GPT-5’s model page lists cached input at $0.125 per 1M tokens. GPT-5 model documentation provides that figure.

Deployment geography also affects Claude’s bill. Anthropic states that regional and multi-region endpoints carry a 10% premium over global endpoints. Claude pricing identifies this as a deployment charge rather than a capability difference.

GPT-5 (high) is the safer first choice for cost-sensitive developer products with explicit tool orchestration requirements. OpenAI documents function calling, structured outputs, streaming, custom tools, reasoning effort settings, and verbosity controls. GPT-5 for developers and GPT-5 model documentation provide the relevant integration details. Its lower blended price also makes broad rollout and repeated agent calls easier to budget.

Claude Opus 4.5 (Reasoning) is the better candidate for teams prioritizing broad reasoning quality and multimodal interaction. Anthropic’s overview confirms text and image input, text output, multilingual capability, and vision support. Claude models overview supports that positioning. Claude’s higher Intelligence Index reinforces the case, although the supplied evidence does not prove better results for every coding workflow.

Choose Claude when the evaluation set rewards nuanced analysis, difficult interpretation, or image-aware reasoning. Choose GPT-5 when predictable API controls, documented context capacity, and lower token prices dominate the decision. For an agent that modifies an existing repository, require review gates for either model. A Reddit report describes GPT-5 as useful for small bug fixes, but also reports hallucinations or incorrect changes in complex existing codebases. The Reddit report is a single uncontrolled experience, not a stable community consensus.

Neither model should be selected solely from the supplied benchmark evidence. Claude lacks comparable official coding and context-window details in the brief. GPT-5 has clearer documentation, but its fixed snapshot is marked Deprecated. A representative private evaluation remains necessary before production commitment.

Claude Opus 4.5 (Reasoning) cannot be declared faster or more reliable from the supplied evidence because output-speed and controlled community data are missing. Both models show 0.3 seconds median latency, but that metric does not describe long-response throughput or end-to-end agent completion time.

GPT-5 (high) cannot be treated as a permanently stable version merely because the gpt-5 alias remains documented. OpenAI marks the fixed snapshot gpt-5-2025-08-07 as Deprecated. Claude Opus 4.5 also has unclear lifecycle details because the supplied Anthropic material does not provide a stable alias, concrete API ID, or retirement notice.

The practical conclusion is conditional. GPT-5 is easier to specify and cheaper to operate. Claude has the stronger broad intelligence score. Neither source set supplies enough controlled evidence to settle production reliability across arbitrary developer workloads.