Can Granite 4.2 8B run on Redmi Note 15 Pro+ 5G?

YESRuns, barely
Formula estimate

What this means

Our estimate says Granite 4.2 8B should fit, but replies are likely to arrive slowly.

Download the Q4_K_M version, which is about 5.3 GB. We expect it to use about 6.7 GB of the roughly 9 GB available to a model on this phone.

At the estimated speed, a roughly 300-word answer may take about 3 minutes to finish.

This result is calculated from the phone and model specifications. It has not been measured on this exact phone and setup.

2.2tokens/s
estimated · slower than you read
6.7GB
needed at Q4_K_M
Q4_K_M
quant checked
needs 6.7 GBusable 9 GB
Snapdragon 7s Gen 412 GB RAMCPU / GPU

Make it bearable

1
Drop context to 2K — saves ~0.3 GB of KV cache and a little speed.
2
Close every other app before loading — the 2.3 GB headroom is real; Android may kill the app otherwise.
3
Expect throttling after ~10 min of sustained generation on a phone chassis.

See how fast it feels

Estimated at 2.2 tokens/s — slower than you read. A ~300-word reply takes about 182 seconds on this phone.

Live demo · 2.2 tokens/s

Where the memory goes

ComponentDetailGB
Model weightsQ4_K_M GGUF (5.3 GB) + mmap overhead5.6
KV cache4K context window0.6
Runtimellama.cpp + app overhead0.6
Total neededat Q4_K_M, 4K context6.7
Working budget12 GB RAM Android system reserve9
Headroomremaining inside the working budget2.3

Pick your quant

QuantDownloadVerdictSpeed
Q2_K 3.4 GB! Runs, barely~3.4 tokens/s
Q3_K_M 4.3 GB! Runs, barely~2.7 tokens/s
Q4_0 5.1 GB! Runs, barely~2.3 tokens/s
Q4_K_S 5.1 GB! Runs, barely~2.3 tokens/s
Q4_K_M BEST HERE5.3 GB! Runs, barely~2.2 tokens/s
Q5_K_M 6.3 GB! Runs, barely~1.8 tokens/s
Q6_K 7.2 GB! Runs, barely~1.6 tokens/s
Q8_0 9.3 GB Won't fitwon'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 ibm-granite/granite-4.2-8b-GGUF.
3
Choose the Q4_K_M GGUF file. The download is about 5.3 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 2.2 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 ibm-granite/granite-4.2-8b-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 Q4_K_M GGUF file is loaded in the chat rather than a remote model.

Related checks

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