Compare
Phi-4-multimodal-instruct vs Phi 3.5 MoE Instruct
Put two to four models side by side on the fields that decide a deployment: context, price, region, license, languages, hosting, and what is verified.
| Phi-4-multimodal-instruct | Phi 3.5 MoE Instruct | |
|---|---|---|
| Provider | Microsoft | Microsoft |
| Parameters | 5.57B | 41.9B |
| Context window | 131k | Not verified: the provider has not documented this claim. |
| License | mit | mit |
| Modalities | text, vision, audio | text |
| Release date | 24 Feb 2025 | 17 Aug 2024 |
| Languages | Strong: en, de, fr, es, it, pt Adequate: nl, pl, sv, da, fi, cs, ru, uk, ar, zh, ja, ko, hi, tr | Strong: — Adequate: nlp |
| Open weights | yes | yes |
| Tasks | Vision, Summarisation, Multilingual support, Low cost | Reasoning, Multilingual support |
Where two models differ, this table shows the difference and stops. LLM EU publishes no winner badge without a documented score for that task, and a missing figure stays missing instead of becoming a zero.
When to use it
Phi-4-multimodal-instruct
Strengths
- text, image and speech input at 5.6B parameters
- 128K-token context for document batches
- MIT licence
- 23 declared languages including most large EU languages
Limits
- modality-specific quality is below dedicated single-modality models
- English-centric training data
- no evaluation has been run by LLM EU
Tasks
Phi 3.5 MoE Instruct
Strengths
- open weights are published on Hugging Face and can be downloaded without a vendor agreement
- mit licence, so commercial self-hosting is permitted without a separate agreement
- instruction-tuned checkpoint with a chat template in the repository
Limits
- catalogue only — LLM EU does not run this model, and nothing on this card implies an LLM EU endpoint
- no evaluation has been run by LLM EU
- the published configuration records no context window, so the card carries none
- at 41.9B parameters, self-hosting needs a high-memory accelerator
Tasks
Tasks: Multilingual support