Can Gemma 4 E4B run on Galaxy S26 FE?
Galaxy S26 FE is not officially announced yet — chip and RAM below are consistent leaked specs. This page updates the moment official specs land.
YES — Runs, barely
Formula estimate
What this means
The checked Q4_0 version should run, but there is very little memory left for the operating system and other apps. The smaller Q3_K_M version is the safer choice.
Download the Q3_K_M version, which is about 4.1 GB. We expect it to use about 5.2 GB of the roughly 6 GB available to a model on this phone.
At the estimated speed, a roughly 300-word answer may take about 48 seconds to finish.
This result is calculated from the phone and model specifications. It has not been measured on this exact phone and setup.
7.2tokens/s
estimated · reading pace
5.9GB
needed at Q4_0
Q4_0
quant checked
needs 5.9 GBusable 6 GB
Exynos 25008 GB RAMCPU / GPU
Make it bearable
1
Drop to Q3_K_M (4.1 GB) — it runs comfortably here at ~8.4 tokens/s. Recommended over Q4_0.
2
Drop context to 2K — saves ~0.2 GB of KV cache and a little speed.
3
Close every other app before loading — the 0.1 GB headroom is real; Android may kill the app otherwise.
4
Expect throttling after ~10 min of sustained generation on a phone chassis.
See how fast it feels
Estimated at 7.2 tokens/s — reading pace. A ~300-word reply takes about 56 seconds on this phone.
Where the memory goes
| Component | Detail | GB |
|---|---|---|
| Model weights | Q4_0 GGUF (4.8 GB) + mmap overhead | 5 |
| KV cache | 4K context window | 0.3 |
| Runtime | llama.cpp + app overhead | 0.6 |
| Total needed | at Q4_0, 4K context | 5.9 |
| Working budget | 8 GB RAM − Android system reserve | 6 |
| Headroom | remaining inside the working budget | 0.1 |
Pick your quant
| Quant | Download | Verdict | Speed |
|---|---|---|---|
| Q3_K_M BEST HERE | 4.1 GB | ✓ Runs great | ~8.4 tokens/s |
| IQ4_XS | 4.7 GB | ! Runs, barely | ~7.4 tokens/s |
| Q4_0 | 4.8 GB | ! Runs, barely | ~7.2 tokens/s |
| Q4_K_S | 4.8 GB | ! Runs, barely | ~7.2 tokens/s |
| Q4_K_M | 5 GB | ✕ Won't fit | won't fit |
| Q5_K_M | 5.5 GB | ✕ Won't fit | won't fit |
| Q6_K | 7.1 GB | ✕ Won't fit | won't fit |
| Q8_0 | 8.2 GB | ✕ Won't fit | won't fit |
Get your first offline chat working
Recommended app: PocketPal. Follow the point-and-click steps below. The speed above is an estimate, not a measurement from this exact app and phone.
1
Install or update PocketPal from Google Play. It is free and does not require an account. Use a current version so its loader supports newer model architectures.
2
Open the exact model. In PocketPal, go to Models → + → Add from Hugging Face, then paste
unsloth/gemma-4-E4B-it-GGUF.3
Choose the Q3_K_M GGUF file. The download is about 4.1 GB, so use Wi-Fi and keep the app open. Choose the main GGUF weights, not a vision projector, mmproj, or other helper file.
4
Tap Download, then Load. Start with a 4K (4096-token) context. Keep the app’s default Android backend for the first run.
5
Send a simple first prompt. Try “Explain why the sky is blue in three sentences.” This page estimates about 8.4 tokens/s, but that number is not a PocketPal measurement unless it carries a ✓ Verified label.
6
Confirm it is really offline. After the first reply, turn on airplane mode and ask a second question. If it still answers, the model is running on your phone.
If it does not work
- Model not listed: update PocketPal and paste the exact repository
unsloth/gemma-4-E4B-it-GGUF. - App closes while loading: close other apps, restart the phone, and try 2K context. If it still closes, choose a smaller model.
- No offline reply: confirm that the Q3_K_M GGUF file is loaded in the chat rather than a remote model.
Related checks
More on Galaxy S26 FE
Gemma 4 E4B on other phones