Phi-4 Reasoning
Active14B reasoning-specialized Phi model with extended thinking.
Overview
Phi-4 Reasoning applies reinforcement learning on top of the Phi-4 base to produce a small model with chain-of-thought capabilities competitive with much larger models on math and science tasks.
History
Phi-4 Reasoning was released on 2025-04-01.
Training & availability
Weights are publicly available under the MIT license, making this an open-weight model suitable for on-prem deployment and fine-tuning.
Capabilities
-
Context window: 32K tokens.
-
Max output: 16K tokens.
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Input modalities: text.
Recommended for: open-source.
Limitations
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The context window (32K tokens) is modest by 2026 standards — unsuitable for processing long documents in a single request.
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Text-only — cannot process images, audio, or video inputs.
Quick start
Minimal example using the OpenRouter API. Copy, paste, replace the key.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="sk-or-...",
)
resp = client.chat.completions.create(
model="microsoft/phi-4-reasoning",
messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)Cost calculator
Estimate your monthly bill. Presets are typical workload sizes.
Integrations & tooling support
- Tool calling
- Not supported
- Structured outputs
- Not supported
Price vs quality
Priced low — good for high-volume tasks. Quality tier pending more benchmark coverage.
- Quality percentile
- —
- Effective price
- $0.244/1M
- Pricing breakdown
- $0.075/1M in
$0.3/1M out
Community ratings
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Comments
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