Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | DeepSeek V4.1 Flash (Reasoning, Max Effort) | GPT-5.6 Luna (low) |
|---|---|---|
| Input ($/M tokens) | $0.3 | $0.2 |
| Output ($/M tokens) | $1.2 | $1.2 |
Verdict. DeepSeek V4.1 Flash (Reasoning, Max Effort) and GPT-5.6 Luna (low) 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 budget bracket for output-token pricing. At 1.0× the per-million-token cost, GPT-5.6 Luna (low) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-5.6 Luna (low) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. DeepSeek V4.1 Flash (Reasoning, Max Effort) is strongest on Intelligence Index (39.5). GPT-5.6 Luna (low) leads on Coding Index (44.2), Intelligence Index (21.5).
Speed. On throughput, DeepSeek V4.1 Flash (Reasoning, Max Effort) generates tokens at 223 tok/s versus 101 tok/s — about 55% faster. On time-to-first-token, DeepSeek V4.1 Flash (Reasoning, Max Effort) responds in 1190ms vs 2220ms, which matters most for chat-style UIs.
Provider. DeepSeek and OpenAI sell to overlapping but distinct developer audiences: DeepSeek 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): DeepSeek V4.1 Flash (Reasoning, Max Effort) costs $27.00 ($324/year); GPT-5.6 Luna (low) costs $24.00 ($288/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): DeepSeek V4.1 Flash (Reasoning, Max Effort) ≈ $3.90/run, GPT-5.6 Luna (low) ≈ $3.40/run. At agent/realtime scale (200M input / 100M output per million requests): DeepSeek V4.1 Flash (Reasoning, Max Effort) ≈ $180/run, GPT-5.6 Luna (low) ≈ $160/run. GPT-5.6 Luna (low) 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-5.6 Luna (low) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.45/M tokens vs $0.53/M for DeepSeek V4.1 Flash (Reasoning, Max Effort).
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
DeepSeek V4.1 Flash (Reasoning, Max Effort) generates tokens faster at 223 tok/s vs 101 tok/s. DeepSeek V4.1 Flash (Reasoning, Max Effort) also has lower time-to-first-token (1.19s vs 2.22s).
Choose based on your priorities: GPT-5.6 Luna (low) for lower cost, both perform similarly on benchmarks, and DeepSeek V4.1 Flash (Reasoning, Max Effort) for faster generation. For latency-sensitive apps, check the TTFT comparison above.