Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Olmo 3.1 32B Think | MiMo-V2.5-Pro |
|---|---|---|
| Input ($/M tokens) | $0 | $0.43 |
| Output ($/M tokens) | $0 | $0.87 |
Verdict. MiMo-V2.5-Pro takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Pricing varies significantly between these models — check the table above for the exact per-token rates. Many production workloads actually surface input-token cost (retrieval-augmented prompts, code-context windows), so factor both directions.
Strengths. Olmo 3.1 32B Think is strongest on Intelligence Index (7.9). MiMo-V2.5-Pro leads on Coding Index (60.2), Intelligence Index (42.9).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Allen Institute for AI and Xiaomi sell to overlapping but distinct developer audiences: Allen Institute for AI 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): Olmo 3.1 32B Think costs $0.00 ($0/year); MiMo-V2.5-Pro costs $25.95 ($311/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Olmo 3.1 32B Think ≈ $0.00/run, MiMo-V2.5-Pro ≈ $3.89/run. At agent/realtime scale (200M input / 100M output per million requests): Olmo 3.1 32B Think ≈ $0/run, MiMo-V2.5-Pro ≈ $173/run. Olmo 3.1 32B Think 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
Olmo 3.1 32B Think is cheaper overall. Its blended price (3:1 input/output ratio) is $0.00/M tokens vs $0.54/M for MiMo-V2.5-Pro.
MiMo-V2.5-Pro wins 2 out of 12 benchmarks compared to 0 for Olmo 3.1 32B Think. See the detailed benchmark chart above for per-category results.
MiMo-V2.5-Pro generates tokens faster at 59 tok/s vs — tok/s. However, MiMo-V2.5-Pro has lower time-to-first-token (3.18s vs —s).
Choose based on your priorities: Olmo 3.1 32B Think for lower cost, MiMo-V2.5-Pro for stronger benchmark performance, and MiMo-V2.5-Pro for faster generation. For latency-sensitive apps, check the TTFT comparison above.