Author's Description
Phi-4 Multimodal Instruct is a versatile 5.6B parameter foundation model that combines advanced reasoning and instruction-following capabilities across both text and visual inputs, providing accurate text outputs. The unified architecture enables efficient, low-latency inference, suitable for edge and mobile deployments. Phi-4 Multimodal Instruct supports text inputs in multiple languages including Arabic, Chinese, English, French, German, Japanese, Spanish, and more, with visual input optimized primarily for English. It delivers impressive performance on multimodal tasks involving mathematical, scientific, and document reasoning, providing developers and enterprises a powerful yet compact model for sophisticated interactive applications. For more information, see the [Phi-4 Multimodal blog post](https://azure.microsoft.com/en-us/blog/empowering-innovation-the-next-generation-of-the-phi-family/).
Key Specifications
Supported Parameters
This model supports the following parameters:
Features
This model supports the following features:
Performance Summary
Microsoft's Phi-4 Multimodal Instruct, a 5.6B parameter model, demonstrates competitive response times, ranking in the 48th percentile for speed across benchmarks. Its pricing is a significant strength, consistently offering among the most competitive rates, placing it in the 90th percentile. The model also exhibits strong reliability, with few technical issues, achieving the 82nd percentile. While excelling in cost-efficiency and reliability, its accuracy across various benchmarks is generally lower. It struggles in Coding (22nd percentile), Instruction Following (29th percentile), Reasoning (22nd percentile), and General Knowledge (18th percentile). Although its Email Classification accuracy is 92.0%, its percentile rank (23rd) suggests other models perform better. A notable weakness is its exceptionally long duration for the Ethics benchmark (4th percentile). Overall, Phi-4 Multimodal Instruct is a cost-effective and reliable option, particularly suited for edge and mobile deployments, but its current performance in complex reasoning and knowledge-based tasks indicates room for improvement in accuracy.
Model Pricing
Current Pricing
Feature | Price (per 1M tokens) |
---|---|
Prompt | $0.05 |
Completion | $0.1 |
Price History
Available Endpoints
Provider | Endpoint Name | Context Length | Pricing (Input) | Pricing (Output) |
---|---|---|---|---|
DeepInfra
|
DeepInfra | microsoft/phi-4-multimodal-instruct | 131K | $0.05 / 1M tokens | $0.1 / 1M tokens |
Benchmark Results
Benchmark | Category | Reasoning | Free | Executions | Accuracy | Cost | Duration |
---|
Other Models by microsoft
|
Released | Params | Context |
|
Speed | Ability | Cost |
---|---|---|---|---|---|---|---|
Microsoft: Phi 4 Reasoning Plus | May 01, 2025 | ~14B | 32K |
Text input
Text output
|
★ | ★★★ | $$$$ |
Microsoft: MAI DS R1 | Apr 20, 2025 | — | 163K |
Text input
Text output
|
★★★★ | ★★★★★ | $$ |
Microsoft: Phi 4 | Jan 09, 2025 | ~14B | 16K |
Text input
Text output
|
★★★★ | ★★★★ | $$ |
Microsoft: Phi-3.5 Mini 128K Instruct | Aug 20, 2024 | ~3.8B | 128K |
Text input
Text output
|
★ | ★★ | $$ |
Microsoft: Phi-3 Mini 128K Instruct | May 25, 2024 | ~3.8B | 128K |
Text input
Text output
|
★★★ | ★★★ | $$ |
Microsoft: Phi-3 Medium 128K Instruct | May 23, 2024 | ~14B | 128K |
Text input
Text output
|
★★ | ★ | $$$$ |
WizardLM-2 8x22B | Apr 15, 2024 | 22B | 65K |
Text input
Text output
|
★★★ | ★★ | $$$ |