Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-5.6 Luna (high) | Solar Pro 4 |
|---|---|---|
| Input ($/M tokens) | $0.2 | $0.3 |
| Output ($/M tokens) | $1.2 | $1.2 |
Verdict. GPT-5.6 Luna (high) wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, Solar Pro 4 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Solar Pro 4 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-5.6 Luna (high) is strongest on Coding Index (63.3), Intelligence Index (32.4). Solar Pro 4 leads on Coding Index (52.7), Intelligence Index (28.2).
Speed. On throughput, GPT-5.6 Luna (high) generates tokens at 102 tok/s versus 76 tok/s — about 26% faster. On time-to-first-token, Solar Pro 4 responds in 1990ms vs 8380ms, which matters most for chat-style UIs.
Provider. OpenAI and Upstage sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Upstage 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 Luna (high) costs $24.00 ($288/year); Solar Pro 4 costs $27.00 ($324/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.6 Luna (high) ≈ $3.40/run, Solar Pro 4 ≈ $3.90/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.6 Luna (high) ≈ $160/run, Solar Pro 4 ≈ $180/run. GPT-5.6 Luna (high) 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.
Data from Artificial Analysis API — 12 benchmarks
GPT-5.6 Luna (high) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.45/M tokens vs $0.53/M for Solar Pro 4.
GPT-5.6 Luna (high) wins 2 out of 12 benchmarks compared to 0 for Solar Pro 4. See the detailed benchmark chart above for per-category results.
GPT-5.6 Luna (high) generates tokens faster at 102 tok/s vs 76 tok/s. However, Solar Pro 4 has lower time-to-first-token (1.99s vs 8.38s).
Choose based on your priorities: GPT-5.6 Luna (high) for lower cost, GPT-5.6 Luna (high) for stronger benchmark performance, and GPT-5.6 Luna (high) for faster generation. For latency-sensitive apps, check the TTFT comparison above.