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microsoft · Open weights

Phi 4 Multimodal

Added Jul 26, 2025Open weights

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Phi 4 by Microsoft. A small multimodal model that can handle images and text.

Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.07
Output
$0.11

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
16.4K

Side by side

Phi 4 Multimodal compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Phi 4 MultimodalmicrosoftThis modelPhi 4 MinimicrosoftRemove
Providermicrosoftmicrosoft
Discovery tierOpen weightsOpen weights
AddedJul 26, 2025Jul 26, 2025
Limits
Context window128K128K
Max output16.38K16.38K
Average output—24 tokens
Pricing, USD per 1M tokens
Input$0.07Best$0.17
Output$0.11Best$0.68
Performance
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index5.86.3Best
Coding Index—3.8
Math Index—6.7
Capabilities
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Phi 4 Multimodal
  • Phi 4 Mini

Intelligence Index

  • Phi 4 Multimodal5.8
  • Phi 4 Mini6.3

Phi 4 Multimodal: Better than 3% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 3.8
  • Math Index

    Composite of the math evaluations

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 6.7

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 15.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Phi 4 Multimodal: 5.0%Top
    • Phi 4 Mini: 4.4%
  • GPQA Diamond

    Graduate-level science questions

    • Phi 4 Multimodal: 31.5%
    • Phi 4 Mini: 33.1%Top
  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Phi 4 Multimodal: 48.5%Top
    • Phi 4 Mini: 46.5%
  • IFBench

    Following precise output instructions

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 21.1%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Phi 4 Multimodal: 13.1%Top
    • Phi 4 Mini: 12.6%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 6.7%
  • AIME

    Competition mathematics

    • Phi 4 Multimodal: 9.3%Top
    • Phi 4 Mini: 3.0%
  • MATH-500

    Competition math problems

    • Phi 4 Multimodal: 69.3%
    • Phi 4 Mini: 69.6%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 0.0%
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 8.2%
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Phi 4 Multimodal: —
    • Phi 4 Mini: 15.3%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "phi-4-multimodal-instruct",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="phi-4-multimodal-instruct",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

microsoft

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