Compare/DeepSeek V3.1 (Reasoning) vs MiMo-V2.5

DeepSeek V3.1 (Reasoning)vsMiMo-V2.5

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

DeepSeek

DeepSeek V3.1 (Reasoning)

Input
$0.59/M
Output
$1.69/M
Speed
TTFT
Xiaomi

MiMo-V2.5

Input
$0.36/M
Output
$1.8/M
Speed
88 tok/s
TTFT
2.03s

Winner by Category

Cheaper
MiMo-V2.5
Faster (tok/s)
MiMo-V2.5
Lower Latency
DeepSeek V3.1 (Reasoning)
Benchmarks (4-7)
MiMo-V2.5

Pricing Comparison

MetricDeepSeek V3.1 (Reasoning)MiMo-V2.5
Input ($/M tokens)$0.59$0.36
Output ($/M tokens)$1.69$1.8
Cost for 1M input + 100K output tokens:
DeepSeek V3.1 (Reasoning)$0.76
MiMo-V2.5$0.54

Speed Comparison

Output Speed (tokens/s) — higher is better
DeepSeek V3.1 (Reasoning)
MiMo-V2.5
88 tok/s
Time to First Token (seconds) — lower is better
DeepSeek V3.1 (Reasoning)
MiMo-V2.5
2.03s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
27.749.0
Coding Index
29.742.1
Math Index
89.7
GPQA Diamond
77.9%84.9%
MMLU-Pro
85.1%
LiveCodeBench
78.4%
AIME 2025
89.7%
MATH-500
Humanity's Last Exam
13.0%25.2%
SciCode
39.1%43.1%
IFBench
41.5%67.1%
TerminalBench
25.0%41.7%
DeepSeek V3.1 (Reasoning)4 wins
7 winsMiMo-V2.5

Frequently Asked Questions

Which is cheaper, DeepSeek V3.1 (Reasoning) or MiMo-V2.5?

MiMo-V2.5 is cheaper overall. Its blended price (3:1 input/output ratio) is $0.72/M tokens vs $0.86/M for DeepSeek V3.1 (Reasoning).

Which model performs better on benchmarks?

MiMo-V2.5 wins 7 out of 12 benchmarks compared to 4 for DeepSeek V3.1 (Reasoning). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

MiMo-V2.5 generates tokens faster at 88 tok/s vs 0 tok/s. DeepSeek V3.1 (Reasoning) also has lower time-to-first-token (0.00s vs 2.03s).

When should I use DeepSeek V3.1 (Reasoning) vs MiMo-V2.5?

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