Microsoft: Phi 4 Mini Instruct

microsoft/phi-4-mini-instruct

Phi-4-mini-instruct is a lightweight open model built upon synthetic data and filtered publicly available websites - with a focus on high-quality, reasoning dense data. The model belongs to the Phi-4 model family and supports 128K token context length. The model underwent an enhancement process, incorporating both supervised fine-tuning and direct preference optimization to support precise instruction adherence and robust safety measures.

Model weights

Modalities

In / Out Price

Low

$0.08 / $0.35per 1M

Context

Avg

131K

Released

Oct 17, 2025

Providers

This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Pricing

List price is the headline rate per million tokens. Effective price is what you actually pay after prompt caching is applied — for repeated context, this can be 60–80% cheaper. The chart below shows the rolling effective price over the past 30 days.

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows where this model lands among all models on OpenRouter.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

Uptime

Percent of requests that succeeded over the last 30 days. OpenRouter monitors every provider continuously and automatically retries on the next-best provider when one returns an error.

Quick Start

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.