Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | MiMo-V2.5-Pro | DeepSeek V4 Pro (Reasoning, Max Effort) |
|---|---|---|
| Input ($/M tokens) | $0.435 | $0.435 |
| Output ($/M tokens) | $0.87 | $0.87 |
Verdict. DeepSeek V4 Pro (Reasoning, Max Effort) takes the aggregate benchmark matchup 4–3 across 7 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, DeepSeek V4 Pro (Reasoning, Max Effort) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). DeepSeek V4 Pro (Reasoning, Max Effort) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. MiMo-V2.5-Pro is strongest on GPQA Diamond (87%), IFBench (80%), Coding Index (60.2). DeepSeek V4 Pro (Reasoning, Max Effort) leads on GPQA Diamond (89%), IFBench (76%), Coding Index (59.4).
Speed. Throughput is comparable — 65 tok/s vs 71 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.
Provider. Xiaomi and DeepSeek sell to overlapping but distinct developer audiences: Xiaomi tends to ship frontier reasoning models with premium positioning, while DeepSeek 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): MiMo-V2.5-Pro costs $26.10 ($313/year); DeepSeek V4 Pro (Reasoning, Max Effort) costs $26.10 ($313/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): MiMo-V2.5-Pro ≈ $3.92/run, DeepSeek V4 Pro (Reasoning, Max Effort) ≈ $3.92/run. At agent/realtime scale (200M input / 100M output per million requests): MiMo-V2.5-Pro ≈ $174/run, DeepSeek V4 Pro (Reasoning, Max Effort) ≈ $174/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.
DeepSeek V4 Pro (Reasoning, Max Effort) wins 4 out of 12 benchmarks compared to 3 for MiMo-V2.5-Pro. See the detailed benchmark chart above for per-category results.
DeepSeek V4 Pro (Reasoning, Max Effort) generates tokens faster at 71 tok/s vs 65 tok/s. However, DeepSeek V4 Pro (Reasoning, Max Effort) has lower time-to-first-token (1.02s vs 2.11s).
Choose based on your priorities: both are similarly priced, DeepSeek V4 Pro (Reasoning, Max Effort) for stronger benchmark performance, and DeepSeek V4 Pro (Reasoning, Max Effort) for faster generation. For latency-sensitive apps, check the TTFT comparison above.