Compare/Command A+ vs MiMo-V2.5-Pro

Command A+vsMiMo-V2.5-Pro

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Cohere

Command A+

Input
$0/M
Output
$0/M
Speed
207 tok/s
TTFT
0.38s
Xiaomi

MiMo-V2.5-Pro

Input
$0.43/M
Output
$0.87/M
Speed
59 tok/s
TTFT
3.18s

Winner by Category

Cheaper
Command A+
Faster (tok/s)
Command A+
Lower Latency
Command A+
Benchmarks (0-2)
MiMo-V2.5-Pro

Pricing Comparison

MetricCommand A+MiMo-V2.5-Pro
Input ($/M tokens)$0$0.43
Output ($/M tokens)$0$0.87
Cost for 1M input + 100K output tokens:
Command A+$0.00
MiMo-V2.5-Pro$0.52

Speed Comparison

Output Speed (tokens/s) — higher is better
Command A+
207 tok/s
MiMo-V2.5-Pro
59 tok/s
Time to First Token (seconds) — lower is better
Command A+
0.38s
MiMo-V2.5-Pro
3.18s

Editorial Analysis

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. Command A+ is strongest on Coding Index (27.8), Intelligence Index (22.8). MiMo-V2.5-Pro leads on Coding Index (60.2), Intelligence Index (42.9).

Speed. On throughput, Command A+ generates tokens at 207 tok/s versus 59 tok/s — about 72% faster. On time-to-first-token, Command A+ responds in 380ms vs 3180ms, which matters most for chat-style UIs.

Provider. Cohere and Xiaomi sell to overlapping but distinct developer audiences: Cohere 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): Command A+ 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): Command A+ ≈ $0.00/run, MiMo-V2.5-Pro ≈ $3.89/run. At agent/realtime scale (200M input / 100M output per million requests): Command A+ ≈ $0/run, MiMo-V2.5-Pro ≈ $173/run. Command A+ 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.

Head-to-head deltas

  • On throughput, Command A+ is 3.53× faster (207 tok/s vs 59 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.
  • Time-to-first-token differs by 8.4× — Command A+ responds in 380ms vs 3180ms. For interactive chat UIs this can matter more than raw benchmark wins.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
22.842.9
Coding Index
27.860.2
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Command A+0 wins
2 winsMiMo-V2.5-Pro

Frequently Asked Questions

Which is cheaper, Command A+ or MiMo-V2.5-Pro?

Command A+ 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.

Which model performs better on benchmarks?

MiMo-V2.5-Pro wins 2 out of 12 benchmarks compared to 0 for Command A+. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Command A+ generates tokens faster at 207 tok/s vs 59 tok/s. Command A+ also has lower time-to-first-token (0.38s vs 3.18s).

When should I use Command A+ vs MiMo-V2.5-Pro?

Choose based on your priorities: Command A+ for lower cost, MiMo-V2.5-Pro for stronger benchmark performance, and Command A+ for faster generation. For latency-sensitive apps, check the TTFT comparison above.