Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) | GPT-5.6 Sol (xhigh) |
|---|---|---|
| Input ($/M tokens) | $5 | $5 |
| Output ($/M tokens) | $25 | $30 |
Verdict. GPT-5.6 Sol (xhigh) takes the aggregate benchmark matchup 4–3 across 7 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the premium bracket for output-token pricing. At 0.8× 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. Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) is strongest on GPQA Diamond (94%), Coding Index (77.0), Intelligence Index (60.1). GPT-5.6 Sol (xhigh) leads on GPQA Diamond (93%), Coding Index (78.3), IFBench (71%).
Speed. Throughput is comparable — 60 tok/s vs 64 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.
Provider. Anthropic and OpenAI sell to overlapping but distinct developer audiences: Anthropic tends to ship frontier reasoning models with premium positioning, while OpenAI 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): Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) costs $525.00 ($6300/year); GPT-5.6 Sol (xhigh) costs $600.00 ($7200/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) ≈ $75.00/run, GPT-5.6 Sol (xhigh) ≈ $85.00/run. At agent/realtime scale (200M input / 100M output per million requests): Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) ≈ $3500/run, GPT-5.6 Sol (xhigh) ≈ $4000/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 (xhigh).
GPT-5.6 Sol (xhigh) wins 4 out of 12 benchmarks compared to 3 for Claude Opus 5 (Adaptive Reasoning, Xhigh Effort). See the detailed benchmark chart above for per-category results.
GPT-5.6 Sol (xhigh) generates tokens faster at 64 tok/s vs 60 tok/s. Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) also has lower time-to-first-token (22.56s vs 31.00s).
Choose based on your priorities: Claude Opus 5 (Adaptive Reasoning, Xhigh Effort) for lower cost, GPT-5.6 Sol (xhigh) for stronger benchmark performance, and GPT-5.6 Sol (xhigh) for faster generation. For latency-sensitive apps, check the TTFT comparison above.