Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | DeepSeek V4 Pro (Reasoning, Max Effort) | MiMo-V2.5-Pro |
|---|---|---|
| Input ($/M tokens) | $0.43 | $0.43 |
| Output ($/M tokens) | $0.87 | $0.87 |
Verdict. DeepSeek V4 Pro (Reasoning, Max Effort) and MiMo-V2.5-Pro 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, MiMo-V2.5-Pro is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). MiMo-V2.5-Pro makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. DeepSeek V4 Pro (Reasoning, Max Effort) is strongest on Coding Index (59.4), Intelligence Index (45.3). MiMo-V2.5-Pro leads on Coding Index (60.2), Intelligence Index (42.9).
Speed. On throughput, DeepSeek V4 Pro (Reasoning, Max Effort) generates tokens at 78 tok/s versus 47 tok/s — about 40% faster. On time-to-first-token, DeepSeek V4 Pro (Reasoning, Max Effort) responds in 1780ms vs 3320ms, which matters most for chat-style UIs.
Provider. DeepSeek and Xiaomi sell to overlapping but distinct developer audiences: DeepSeek tends to ship frontier reasoning models with premium positioning, while Xiaomi 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, Max Effort) costs $25.95 ($311/year); MiMo-V2.5-Pro costs $25.95 ($311/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): DeepSeek V4 Pro (Reasoning, Max Effort) ≈ $3.89/run, MiMo-V2.5-Pro ≈ $3.89/run. At agent/realtime scale (200M input / 100M output per million requests): DeepSeek V4 Pro (Reasoning, Max Effort) ≈ $173/run, MiMo-V2.5-Pro ≈ $173/run.
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
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
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 Pro (Reasoning, Max Effort) generates tokens faster at 78 tok/s vs 47 tok/s. DeepSeek V4 Pro (Reasoning, Max Effort) also has lower time-to-first-token (1.78s vs 3.32s).
Choose based on your priorities: both are similarly priced, both perform similarly on benchmarks, and DeepSeek V4 Pro (Reasoning, Max Effort) for faster generation. For latency-sensitive apps, check the TTFT comparison above.