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Compare/Phi-4 Mini Instruct vs MiMo-V2.5-Pro

Phi-4 Mini InstructvsMiMo-V2.5-Pro

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

Microsoft

Phi-4 Mini Instruct

Input
$0/M
Output
$0/M
Speed
45 tok/s
TTFT
0.86s
Xiaomi

MiMo-V2.5-Pro

Input
$0.43/M
Output
$0.87/M
Speed
41 tok/s
TTFT
6.14s

Winner by Category

Cheaper
Phi-4 Mini Instruct
Faster (tok/s)
Phi-4 Mini Instruct
Lower Latency
Phi-4 Mini Instruct
Benchmarks (0-2)
MiMo-V2.5-Pro

Pricing Comparison

MetricPhi-4 Mini InstructMiMo-V2.5-Pro
Input ($/M tokens)$0$0.43
Output ($/M tokens)$0$0.87
Cost for 1M input + 100K output tokens:
Phi-4 Mini Instruct$0.00
MiMo-V2.5-Pro$0.52

Speed Comparison

Output Speed (tokens/s) — higher is better
Phi-4 Mini Instruct
45 tok/s
MiMo-V2.5-Pro
41 tok/s
Time to First Token (seconds) — lower is better
Phi-4 Mini Instruct
0.86s
MiMo-V2.5-Pro
6.14s

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. Phi-4 Mini Instruct is strongest on Intelligence Index (6.3), Coding Index (3.8). MiMo-V2.5-Pro leads on Coding Index (60.2), Intelligence Index (26.4).

Speed. Throughput is comparable — 45 tok/s vs 41 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.

Provider. Microsoft and Xiaomi sell to overlapping but distinct developer audiences: Microsoft 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): Phi-4 Mini Instruct 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): Phi-4 Mini Instruct ≈ $0.00/run, MiMo-V2.5-Pro ≈ $3.89/run. At agent/realtime scale (200M input / 100M output per million requests): Phi-4 Mini Instruct ≈ $0/run, MiMo-V2.5-Pro ≈ $173/run. Phi-4 Mini Instruct 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

  • Time-to-first-token differs by 7.1× — Phi-4 Mini Instruct responds in 860ms vs 6140ms. For interactive chat UIs this can matter more than raw benchmark wins.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
6.326.4
Coding Index
3.860.2
Math Index
——
GPQA Diamond
——
MMLU-Pro
——
LiveCodeBench
——
AIME 2025
——
MATH-500
——
Humanity's Last Exam
——
SciCode
——
IFBench
——
TerminalBench
——
Phi-4 Mini Instruct0 wins
2 winsMiMo-V2.5-Pro

Frequently Asked Questions

Which is cheaper, Phi-4 Mini Instruct or MiMo-V2.5-Pro?

Phi-4 Mini Instruct 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 Phi-4 Mini Instruct. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Phi-4 Mini Instruct generates tokens faster at 45 tok/s vs 41 tok/s. Phi-4 Mini Instruct also has lower time-to-first-token (0.86s vs 6.14s).

When should I use Phi-4 Mini Instruct vs MiMo-V2.5-Pro?

Choose based on your priorities: Phi-4 Mini Instruct for lower cost, MiMo-V2.5-Pro for stronger benchmark performance, and Phi-4 Mini Instruct for faster generation. For latency-sensitive apps, check the TTFT comparison above.