Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | MiMo-V2.5-Pro | Trinity Large Thinking |
|---|---|---|
| Input ($/M tokens) | $0.435 | $0.235 |
| Output ($/M tokens) | $0.87 | $0.875 |
Verdict. MiMo-V2.5-Pro wins the overall benchmark matchup 7–0 across 7 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, 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. MiMo-V2.5-Pro is strongest on GPQA Diamond (87%), IFBench (80%), Coding Index (60.2). Trinity Large Thinking leads on GPQA Diamond (75%), IFBench (56%), SciCode (36%).
Speed. On throughput, Trinity Large Thinking generates tokens at 169 tok/s versus 65 tok/s — about 61% faster. On time-to-first-token, Trinity Large Thinking responds in 489ms vs 2111ms, which matters most for chat-style UIs.
Provider. Xiaomi and Arcee AI sell to overlapping but distinct developer audiences: Xiaomi tends to ship frontier reasoning models with premium positioning, while Arcee AI 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); Trinity Large Thinking costs $20.18 ($242/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): MiMo-V2.5-Pro ≈ $3.92/run, Trinity Large Thinking ≈ $2.92/run. At agent/realtime scale (200M input / 100M output per million requests): MiMo-V2.5-Pro ≈ $174/run, Trinity Large Thinking ≈ $135/run. Trinity Large Thinking becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. If you want one safe default, take MiMo-V2.5-Pro — it dominates the benchmark table and the latency profile is 2.6× faster. Trinity Large Thinking only makes sense when you specifically need its pricing tier, an existing contract, or a feature difference that is not measured by the benchmarks above.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Trinity Large Thinking is cheaper overall. Its blended price (3:1 input/output ratio) is $0.40/M tokens vs $0.54/M for MiMo-V2.5-Pro.
MiMo-V2.5-Pro wins 7 out of 12 benchmarks compared to 0 for Trinity Large Thinking. See the detailed benchmark chart above for per-category results.
Trinity Large Thinking generates tokens faster at 169 tok/s vs 65 tok/s. However, Trinity Large Thinking has lower time-to-first-token (0.49s vs 2.11s).
Choose based on your priorities: Trinity Large Thinking for lower cost, MiMo-V2.5-Pro for stronger benchmark performance, and Trinity Large Thinking for faster generation. For latency-sensitive apps, check the TTFT comparison above.