Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-5.3 Codex (xhigh) | Claude Sonnet 4.6 (Non-reasoning, High Effort) |
|---|---|---|
| Input ($/M tokens) | $1.75 | $3 |
| Output ($/M tokens) | $14 | $15 |
Verdict. GPT-5.3 Codex (xhigh) wins the overall benchmark matchup 1–0 across 1 overlapping categories, but raw benchmark score is only one input to the decision.
Pricing. Both models sit in the mid-tier / premium bracket for output-token pricing. At 0.9× the per-million-token cost, GPT-5.3 Codex (xhigh) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-5.3 Codex (xhigh) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-5.3 Codex (xhigh) is strongest on Intelligence Index (45.5). Claude Sonnet 4.6 (Non-reasoning, High Effort) leads on Intelligence Index (36.8).
Speed. On throughput, GPT-5.3 Codex (xhigh) generates tokens at 132 tok/s versus 43 tok/s — about 67% faster. On time-to-first-token, Claude Sonnet 4.6 (Non-reasoning, High Effort) responds in 1360ms vs 64930ms, which matters most for chat-style UIs.
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-5.3 Codex (xhigh) costs $262.50 ($3150/year); Claude Sonnet 4.6 (Non-reasoning, High Effort) costs $315.00 ($3780/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.3 Codex (xhigh) ≈ $36.75/run, Claude Sonnet 4.6 (Non-reasoning, High Effort) ≈ $45.00/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.3 Codex (xhigh) ≈ $1750/run, Claude Sonnet 4.6 (Non-reasoning, High Effort) ≈ $2100/run. GPT-5.3 Codex (xhigh) 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
GPT-5.3 Codex (xhigh) is cheaper overall. Its blended price (3:1 input/output ratio) is $4.81/M tokens vs $6.00/M for Claude Sonnet 4.6 (Non-reasoning, High Effort).
GPT-5.3 Codex (xhigh) wins 1 out of 12 benchmarks compared to 0 for Claude Sonnet 4.6 (Non-reasoning, High Effort). See the detailed benchmark chart above for per-category results.
GPT-5.3 Codex (xhigh) generates tokens faster at 132 tok/s vs 43 tok/s. However, Claude Sonnet 4.6 (Non-reasoning, High Effort) has lower time-to-first-token (1.36s vs 64.93s).
Choose based on your priorities: GPT-5.3 Codex (xhigh) for lower cost, GPT-5.3 Codex (xhigh) for stronger benchmark performance, and GPT-5.3 Codex (xhigh) for faster generation. For latency-sensitive apps, check the TTFT comparison above.