Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-5.6 Sol (max) | Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) |
|---|---|---|
| Input ($/M tokens) | $5 | $5 |
| Output ($/M tokens) | $30 | $25 |
Verdict. GPT-5.6 Sol (max) and Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Both models sit in the premium bracket for output-token pricing. At 1.2× the per-million-token cost, Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-5.6 Sol (max) is strongest on Coding Index (77.4), Intelligence Index (60.9). Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) leads on Coding Index (77.0), Intelligence Index (62.5).
Speed. Throughput is comparable — 65 tok/s vs 54 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.
Provider. OpenAI and Anthropic sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Anthropic often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GPT-5.6 Sol (max) costs $600.00 ($7200/year); Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) costs $525.00 ($6300/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.6 Sol (max) ≈ $85.00/run, Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) ≈ $75.00/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.6 Sol (max) ≈ $4000/run, Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) ≈ $3500/run. Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) is cheaper overall. Its blended price (3:1 input/output ratio) is $10.00/M tokens vs $11.25/M for GPT-5.6 Sol (max).
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
GPT-5.6 Sol (max) generates tokens faster at 65 tok/s vs 54 tok/s. However, Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) has lower time-to-first-token (40.50s vs 208.71s).
Choose based on your priorities: Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) for lower cost, both perform similarly on benchmarks, and GPT-5.6 Sol (max) for faster generation. For latency-sensitive apps, check the TTFT comparison above.