Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | DeepSeek V4 Pro (Reasoning, High Effort) | Llama 4 Maverick |
|---|---|---|
| Input ($/M tokens) | $0.435 | $0.27 |
| Output ($/M tokens) | $0.87 | $0.85 |
Verdict. DeepSeek V4 Pro (Reasoning, High Effort) wins the overall benchmark matchup 7–5 across 12 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, Llama 4 Maverick is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Llama 4 Maverick makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. DeepSeek V4 Pro (Reasoning, High Effort) is strongest on GPQA Diamond (91%), IFBench (71%), Coding Index (58.7). Llama 4 Maverick leads on MATH-500 (89%), MMLU-Pro (81%), GPQA Diamond (67%).
Speed. On throughput, Llama 4 Maverick generates tokens at 99 tok/s versus 73 tok/s — about 26% faster. On time-to-first-token, Llama 4 Maverick responds in 614ms vs 922ms, which matters most for chat-style UIs.
Provider. DeepSeek and Meta sell to overlapping but distinct developer audiences: DeepSeek tends to ship frontier reasoning models with premium positioning, while Meta 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 Pro (Reasoning, High Effort) costs $26.10 ($313/year); Llama 4 Maverick costs $20.85 ($250/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): DeepSeek V4 Pro (Reasoning, High Effort) ≈ $3.92/run, Llama 4 Maverick ≈ $3.05/run. At agent/realtime scale (200M input / 100M output per million requests): DeepSeek V4 Pro (Reasoning, High Effort) ≈ $174/run, Llama 4 Maverick ≈ $139/run. Llama 4 Maverick 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
Llama 4 Maverick is cheaper overall. Its blended price (3:1 input/output ratio) is $0.41/M tokens vs $0.54/M for DeepSeek V4 Pro (Reasoning, High Effort).
DeepSeek V4 Pro (Reasoning, High Effort) wins 7 out of 12 benchmarks compared to 5 for Llama 4 Maverick. See the detailed benchmark chart above for per-category results.
Llama 4 Maverick generates tokens faster at 99 tok/s vs 73 tok/s. However, Llama 4 Maverick has lower time-to-first-token (0.61s vs 0.92s).
Choose based on your priorities: Llama 4 Maverick for lower cost, DeepSeek V4 Pro (Reasoning, High Effort) for stronger benchmark performance, and Llama 4 Maverick for faster generation. For latency-sensitive apps, check the TTFT comparison above.