GPT-5.4 vs Claude Opus 4.7: workhorse value or flagship intelligence?
The sensible default vs the no-compromise flagship — is the premium justified?
GPT-5.4 is OpenAI's workhorse model, balancing cost and capability for everyday production workloads. Claude Opus 4.7 is Anthropic's flagship, optimized for deep reasoning, complex planning, and nuanced analysis. Opus costs roughly 2-3x more per token. Whether that premium is justified depends entirely on whether your task needs Opus-level reasoning or whether GPT-5.4's intelligence is already good enough.
Cost Comparison
Based on 100,000 input tokens (50% cached), 5,000 output tokens, and 100 requests.
Side-by-side specs
| Spec | GPT-5.4 | Claude Opus 4.7 |
|---|---|---|
| Input cost (per M) | $2.50 (better on this spec) | $5.00 |
| Output cost (per M) | $15.00 (better on this spec) | $25.00 |
| Cached input (per M) | $0.25 (better on this spec) | $0.50 |
| Reasoning depth | Strong | Exceptional (better on this spec) |
| Coding ability | Excellent (better on this spec) | Very good |
| Best for agents | Capable | Optimal (better on this spec) |
How they differ
GPT-5.4: $2.50/M input, $15/M output, 90% caching discount ($0.25/M cached), 50% batch discount. Claude Opus 4.7: $5/M input, $25/M output, 90% caching discount ($0.50/M cached), 50% batch discount. For a typical 100K input + 10K output request, GPT-5.4 costs $0.40, Opus costs $0.75. Over a million requests, that's $400K vs $750K — a $350K difference. In benchmarks, Opus 4.7 leads on graduate-level reasoning (GPQA Diamond), mathematical proofs, and multi-step agentic tasks. GPT-5.4 is competitive or better on general knowledge, coding, and instruction following at a fraction of the price. The right choice depends on whether your workload genuinely benefits from Opus's reasoning depth.
Verdict
GPT-5.4 for most production workloads: it's cheaper and more than capable enough for RAG, chat, coding, and content generation. Claude Opus 4.7 for tasks where reasoning depth directly impacts business outcomes: legal analysis, scientific research, complex financial modeling, and multi-step autonomous agents where a wrong answer costs more than the API savings.
Which should you pick?
Choose GPT-5.4
High-volume production workloads. RAG, customer support, content generation, coding assistance. Your task doesn't need frontier-level reasoning and you prioritize cost efficiency.
Choose Claude Opus 4.7
Complex analysis, legal and financial reasoning, scientific research, autonomous agents with multi-step planning. Output quality directly impacts revenue or risk, so the premium is justified.
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