microsoft · Open weights
Phi 4 Multimodal
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.
| Phi 4 MultimodalmicrosoftThis model | Phi 4 MinimicrosoftRemove | |
|---|---|---|
| Provider | microsoft | microsoft |
| Discovery tier | Open weights | Open weights |
| Added | Jul 26, 2025 | Jul 26, 2025 |
| Limits | ||
| Context window | 128K | 128K |
| Max output | 16.38K | 16.38K |
| 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 Index | 5.8 | 6.3Best |
| 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
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.
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
Related models
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