Compare/Claude Opus 5 (Adaptive Reasoning, Low Effort) vs GPT-5.6 Sol (xhigh)

Claude Opus 5 (Adaptive Reasoning, Low Effort)vsGPT-5.6 Sol (xhigh)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Anthropic

Claude Opus 5 (Adaptive Reasoning, Low Effort)

Input
$5/M
Output
$25/M
Speed
47 tok/s
TTFT
2.76s
OpenAI

GPT-5.6 Sol (xhigh)

Input
$5/M
Output
$30/M
Speed
64 tok/s
TTFT
31.00s

Winner by Category

Cheaper
Claude Opus 5 (Adaptive Reasoning, Low Effort)
Faster (tok/s)
GPT-5.6 Sol (xhigh)
Lower Latency
Claude Opus 5 (Adaptive Reasoning, Low Effort)
Benchmarks (0-7)
GPT-5.6 Sol (xhigh)

Pricing Comparison

MetricClaude Opus 5 (Adaptive Reasoning, Low Effort)GPT-5.6 Sol (xhigh)
Input ($/M tokens)$5$5
Output ($/M tokens)$25$30
Cost for 1M input + 100K output tokens:
Claude Opus 5 (Adaptive Reasoning, Low Effort)$7.50
GPT-5.6 Sol (xhigh)$8.00

Speed Comparison

Output Speed (tokens/s) — higher is better
Claude Opus 5 (Adaptive Reasoning, Low Effort)
47 tok/s
GPT-5.6 Sol (xhigh)
64 tok/s
Time to First Token (seconds) — lower is better
Claude Opus 5 (Adaptive Reasoning, Low Effort)
2.76s
GPT-5.6 Sol (xhigh)
31.00s

Editorial Analysis

Verdict. GPT-5.6 Sol (xhigh) takes the aggregate benchmark matchup 7–0 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, Low Effort) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Claude Opus 5 (Adaptive Reasoning, Low Effort) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Claude Opus 5 (Adaptive Reasoning, Low Effort) is strongest on GPQA Diamond (89%), Coding Index (66.9), Intelligence Index (50.6). GPT-5.6 Sol (xhigh) leads on GPQA Diamond (93%), Coding Index (78.3), IFBench (71%).

Speed. On throughput, GPT-5.6 Sol (xhigh) generates tokens at 64 tok/s versus 47 tok/s — about 27% faster. On time-to-first-token, Claude Opus 5 (Adaptive Reasoning, Low Effort) responds in 2763ms vs 31000ms, which matters most for chat-style UIs.

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, Low 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, Low 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, Low Effort) ≈ $3500/run, GPT-5.6 Sol (xhigh) ≈ $4000/run. Claude Opus 5 (Adaptive Reasoning, Low 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

  • GPT-5.6 Sol (xhigh) wins 7 more benchmarks than its opponent — a margin wide enough to call the comparison settled on benchmark terms alone.
  • Time-to-first-token differs by 11.2× — Claude Opus 5 (Adaptive Reasoning, Low Effort) responds in 2763ms vs 31000ms. For interactive chat UIs this can matter more than raw benchmark wins.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
50.657.7
Coding Index
66.978.3
Math Index
GPQA Diamond
88.9%93.1%
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
41.3%44.7%
SciCode
48.0%56.0%
IFBench
71.0%
TerminalBench
61.4%
Claude Opus 5 (Adaptive Reasoning, Low Effort)0 wins
7 winsGPT-5.6 Sol (xhigh)

Frequently Asked Questions

Which is cheaper, Claude Opus 5 (Adaptive Reasoning, Low Effort) or GPT-5.6 Sol (xhigh)?

Claude Opus 5 (Adaptive Reasoning, Low 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).

Which model performs better on benchmarks?

GPT-5.6 Sol (xhigh) wins 7 out of 12 benchmarks compared to 0 for Claude Opus 5 (Adaptive Reasoning, Low Effort). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

GPT-5.6 Sol (xhigh) generates tokens faster at 64 tok/s vs 47 tok/s. Claude Opus 5 (Adaptive Reasoning, Low Effort) also has lower time-to-first-token (2.76s vs 31.00s).

When should I use Claude Opus 5 (Adaptive Reasoning, Low Effort) vs GPT-5.6 Sol (xhigh)?

Choose based on your priorities: Claude Opus 5 (Adaptive Reasoning, Low 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.