Claude Opus 5 vs GPT-5 nano: Which Model Should Developers Choose?

Claude Opus 5 is the safer overall choice for developers who need documented availability and broad agentic capability evidence. Anthropic positions Claude Opus 5 for complex agentic coding and enterprise work, while the current OpenAI model directory does not list GPT-5 nano. Anthropic describes Claude Opus 5 as a model for complex agentic coding and enterprise work, while OpenAI’s current model documentation does not list GPT-5 nano.\n\nGPT-5 nano remains compelling for price-sensitive workloads, especially where mathematical performance matters. The available data gives GPT-5 nano an Artificial Analysis Math Index score of 83.7, but it does not provide a comparable Claude Opus 5 math score. Data provided by https://artificialanalysis.ai/

Claude Opus 5 offers stronger documented general capability, while GPT-5 nano offers a dramatically lower listed blended price and a higher available math score.\n\n| Decision factor | Claude Opus 5 | GPT-5 nano | What it means for developers | |—|—:|—:|—| | Artificial Analysis Intelligence Index | 60.7 | 19.9 | Claude has the stronger available general capability signal | | Artificial Analysis Coding Index | 78 | Not available | Claude has evidence for coding; GPT-5 nano cannot be ranked here | | Artificial Analysis Math Index | Not available | 83.7 | GPT-5 nano has a strong math signal, but there is no matched comparison | | Blended price per 1M tokens | $10 | $0.1375 | GPT-5 nano is the economical option if its availability is confirmed | | Median output speed | 60.088 tokens per second | Not available | Claude has a measured speed result; GPT-5 nano cannot be compared | | Latency | 0.3 seconds | 0.3 seconds | The available latency data is tied | \nClaude Opus 5 is documented as supporting text and image input, text output, multilingual use, vision, adaptive thinking, and several deployment channels. Anthropic’s model overview documents those capabilities and deployment options.\n\nGPT-5 nano has a weaker evidence position, not necessarily a weaker real-world capability profile. The current OpenAI documentation describes current models in general terms, but does not explicitly establish those details for GPT-5 nano. OpenAI’s model documentation provides only a general description of current model capabilities.\n\nThe central selection issue is therefore evidence quality. Claude Opus 5 can be evaluated as a current product. GPT-5 nano can be evaluated as a low-cost data point, but its current API status, limits, and dedicated behavior profile remain unconfirmed.

Claude Opus 5 is the stronger documented performance choice for broad software engineering and agentic workflows. Its Artificial Analysis Intelligence Index score is 60.7, compared with 19.9 for GPT-5 nano, and Claude Opus 5 also has a Coding Index score of 78. Anthropic reports leading results across several agentic and coding evaluations.\n\nThat gap should influence tasks that require planning, tool use, codebase navigation, verification, and sustained execution. A higher general capability signal can reduce the number of corrective turns and human interventions. The available evidence does not prove that every developer workflow will improve by the same amount. It does show that Claude Opus 5 has a broader documented case for complex work.\n\nGPT-5 nano has an Artificial Analysis Math Index score of 83.7. That result makes GPT-5 nano interesting for mathematical reasoning, numerical transformation, and workloads where the task distribution is narrow. It does not establish superiority for coding, general intelligence, tool use, or production agents. Claude Opus 5 has no math score in the supplied data, so the math comparison is incomplete.\n\nClaude Opus 5 reports a median output speed of 60.088 tokens per second. GPT-5 nano has no supplied output-speed value, so no speed winner can be established. Both models have a recorded latency of 0.3 seconds, which suggests that first-response timing alone does not separate them in the supplied snapshot.\n\nThe practical performance risk is behavioral. Anthropic documents longer default responses, more progress narration, more active delegation in multi-agent settings, and possible repeated verification. Anthropic documents these behavior changes and recommends keeping thinking enabled. Community reports describe similar concerns about verbosity, slow-feeling simple tasks, instruction drift, and overthinking, but those reports lack reproducible test methods. A Claude Code discussion reports these experiences without a standardized test.\n\nDevelopers should benchmark their own task mix before treating the general index as a universal result. The supplied materials do not answer whether GPT-5 nano produces better code per dollar, completes tool calls more reliably, or needs fewer retries in a controlled engineering test.

GPT-5 nano is the clear cost winner in the supplied data, but its low price is useful only if developers can confirm a supported production endpoint. Its blended price is $0.1375 per 1M tokens, compared with $10 for Claude Opus 5. Its input price is $0.05, compared with $5, while its output price is $0.4, compared with $25.\n\nThose prices change the architecture that makes economic sense. GPT-5 nano can support higher-volume classification, extraction, routing, draft generation, and mathematical subroutines if its quality is adequate. Claude Opus 5 is easier to justify for tasks where a failed run triggers human review, tool retries, long debugging cycles, or operational delay. A cheap request can become expensive when it requires more orchestration and correction.\n\nClaude Opus 5 also supports prompt caching. Anthropic lists prompt caching prices and a minimum cacheable prompt length of 512 tokens. Caching can improve the economics of repeated instructions, repository context, policy text, or other stable prompts. The supplied materials do not provide an equivalent GPT-5 nano caching price.\n\nOpenAI’s current pricing page lists gpt-5.4-nano at $0.20 input, $0.02 cached input, and $1.25 output per 1M tokens, but the brief explicitly states that these are not GPT-5 nano prices. The current OpenAI pricing page does not list gpt-5-nano. Developers should not substitute the newer model’s price into this comparison.\n\nThe missing information is decisive: the materials do not establish GPT-5 nano’s current endpoint, rate limits, output limits, or billing behavior. The price advantage is therefore a strong economic signal, not a complete procurement conclusion.

Claude Opus 5 is the default recommendation for production agents, complex coding, and enterprise workflows that need a documented current model. Anthropic lists Claude Opus 5 as Active and does not list a deprecation date, with a tentative availability horizon no earlier than 2027-07-24. Anthropic’s deprecation documentation describes the model as Active.\n\nChoose Claude Opus 5 when the model must inspect a large codebase, coordinate tools, maintain a long task plan, or produce a reviewed implementation. Its available Coding Index score of 78 and Intelligence Index score of 60.7 provide direct evidence for this choice. Its support across the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry also reduces deployment friction for teams with existing enterprise cloud requirements. Anthropic documents these access paths.\n\nChoose GPT-5 nano for cost-sensitive experiments or narrowly defined mathematical workloads, but only after confirming that the intended API identifier is callable. Its Math Index score of 83.7 is the strongest specialized result in the supplied comparison. Its $0.1375 blended price can make it attractive for high-volume work. The current official OpenAI model directory does not confirm that GPT-5 nano remains available, and it does not provide dedicated limits or parameters.\n\nA sensible routing policy is to use GPT-5 nano as a candidate low-cost worker and Claude Opus 5 as the escalation model. That policy still requires a controlled test of correctness, retries, tool-call validity, output length, and human review time. The supplied research does not contain those measurements.\n\nDo not disable Claude Opus 5 thinking casually. Anthropic warns that disabled thinking can cause tool calls to appear as ordinary text and can expose internal XML tags. The official Opus 5 documentation describes this failure mode. Security teams should also account for Anthropic’s restrictions on binary vulnerability scanning, penetration testing, and exploit generation. Anthropic documents those cyber safety limits.

Claude Opus 5 is the better default when the purchase decision prioritizes documented availability, broad capability evidence, and agentic coding. GPT-5 nano is more attractive when price or mathematical specialization dominates, but its current product status is uncertain.\n\nThe most important unresolved question is whether GPT-5 nano’s supplied price and benchmark entry describe a currently callable production model. The research materials do not confirm that point. Developers should verify the endpoint, model identifier, quotas, and limits before building around it.