# FastVLM vs Gemma 4 / Gemma 3n

Apple FastVLM compared with Google’s on-device Gemma 4 (E2B/E4B, April 2026) and Gemma 3n: modalities, context, browser and MLX support, licenses and which to choose.

Canonical URL: https://aiidelist.com/blog/fastvlm-vs-gemma

Language: en

Published: 2026-09-24

Updated: 2026-09-24

FASTVLM VS GEMMA 4 / GEMMA 3N

Gemma 4 (April 2026) and Gemma 3n (2025) are Google’s general multimodal models for phones and laptops; FastVLM is a vision-first model. The difference in scope matters more than any score: Gemma answers with audio, long context and agent tooling, FastVLM concentrates on fast, high-resolution image understanding.

[All comparisons](/fastvlm#comparisons)

| Feature | FastVLM | Gemma 4 (E2B / E4B) | Gemma 3n (E2B / E4B) |
| --- | --- | --- | --- |
| Developer · release | Apple · 2025 | Google · 2 April 2026 | Google · 2025 |
| On-device sizes | 0.5B · 1.5B · 7B | E2B · E4B (larger 12B, 26B-A4B, 31B for workstations) | E2B · E4B (effective parameters) |
| Modalities | Image + text | Image, video as frames, text; audio on E2B/E4B | Image, audio, text |
| Context window | Short prompts; not a long-context model | 128K tokens (E2B/E4B, Google) | 32K tokens (Google) |
| Browser | 0.5B via Transformers.js (this site) | Runtime-dependent (LiteRT / MediaPipe style deployments) | Runtime-dependent (Google AI Edge) |
| MLX / Apple Silicon | Official MLX app | Community mlx-vlm conversions | Community mlx-vlm conversions |
| License | Apple ML Research license | Gemma Terms of Use | Gemma Terms of Use |

Checked 2026-09-17

## Decision summary

- Gemma is the choice for assistants that need speech, long documents or video alongside images.
- FastVLM is the choice when the whole job is “look at this high-resolution image and answer quickly”, particularly inside Apple apps.
- Neither vendor publishes a comparison against the other; treat modality and runtime fit as the deciding factors.

## Choose FastVLM when

- Image-only input at high resolution
- Browser demo without a vendor runtime
- Apple-first deployment

## Choose Gemma when

- Audio or video input
- Long context and tool-using agents
- Android and cross-platform runtimes from Google AI Edge

## How to read this table

Gemma sizes are “effective” parameter counts (E2B ≈ 2.3B dense-equivalent memory) and their multimodal benchmarks use Google’s harness; FastVLM’s numbers come from Apple’s. The table records documented capabilities, not measured quality.

## Questions

**Can Gemma 4 run in Transformers.js?**

Check the current Transformers.js model list; Google’s reference path for browsers and phones is its own AI Edge runtime. FastVLM-0.5B already has an ONNX build you can try here.

## Sources

- [Gemma 4 model card](https://ai.google.dev/gemma/docs/core/model_card_4)
- [Gemma 3n documentation](https://ai.google.dev/gemma/docs/gemma-3n)
- [FastVLM paper](https://arxiv.org/abs/2412.13303)

## Continue

- [On-device VLM hub](/blog/on-device-vlm-comparison)
- [FastVLM vs SmolVLM2](/blog/fastvlm-vs-smolvlm2)