Compare/MiMo-V2-Pro vs Kimi K2.5 (Non-reasoning)

MiMo-V2-ProvsKimi K2.5 (Non-reasoning)

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

Xiaomi

MiMo-V2-Pro

Input
$1/M
Output
$3/M
Speed
83 tok/s
TTFT
1.55s
Kimi

Kimi K2.5 (Non-reasoning)

Input
$0.6/M
Output
$3/M
Speed
33 tok/s
TTFT
1.40s

Winner by Category

Cheaper
Kimi K2.5 (Non-reasoning)
Faster (tok/s)
MiMo-V2-Pro
Lower Latency
Kimi K2.5 (Non-reasoning)
Benchmarks (7-0)
MiMo-V2-Pro

Pricing Comparison

MetricMiMo-V2-ProKimi K2.5 (Non-reasoning)
Input ($/M tokens)$1$0.6
Output ($/M tokens)$3$3
Cost for 1M input + 100K output tokens:
MiMo-V2-Pro$1.30
Kimi K2.5 (Non-reasoning)$0.90

Speed Comparison

Output Speed (tokens/s) — higher is better
MiMo-V2-Pro
83 tok/s
Kimi K2.5 (Non-reasoning)
33 tok/s
Time to First Token (seconds) — lower is better
MiMo-V2-Pro
1.55s
Kimi K2.5 (Non-reasoning)
1.40s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
49.237.3
Coding Index
41.425.8
Math Index
GPQA Diamond
87.0%78.9%
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
28.3%12.3%
SciCode
42.5%39.6%
IFBench
68.8%43.7%
TerminalBench
40.9%18.9%
MiMo-V2-Pro7 wins
0 winsKimi K2.5 (Non-reasoning)

Frequently Asked Questions

Which is cheaper, MiMo-V2-Pro or Kimi K2.5 (Non-reasoning)?

Kimi K2.5 (Non-reasoning) is cheaper overall. Its blended price (3:1 input/output ratio) is $1.20/M tokens vs $1.50/M for MiMo-V2-Pro.

Which model performs better on benchmarks?

MiMo-V2-Pro wins 7 out of 12 benchmarks compared to 0 for Kimi K2.5 (Non-reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

MiMo-V2-Pro generates tokens faster at 83 tok/s vs 33 tok/s. However, Kimi K2.5 (Non-reasoning) has lower time-to-first-token (1.40s vs 1.55s).

When should I use MiMo-V2-Pro vs Kimi K2.5 (Non-reasoning)?

Choose based on your priorities: Kimi K2.5 (Non-reasoning) for lower cost, MiMo-V2-Pro for stronger benchmark performance, and MiMo-V2-Pro for faster generation. For latency-sensitive apps, check the TTFT comparison above.