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text model · Gemma · Windows

Can I run Gemma 3n E4B on Nvidia GeForce GTX 1070 (8GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs GPU accelerated ~39 tok/s est.

Yes. Gemma 3n E4B runs on Nvidia GeForce GTX 1070 (8GB) at Q4_K_M (~5.7 GB of ~7 GB usable).

Needs ~5.7 GB Device usable ~7 GB

Runs at Q4_K_M using ~5.7 GB of ~7 GB usable.

That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce GTX 1070 (8GB) leaves ~1.3 GB of headroom.

Q4_K_M needed
~5.7 GB
Usable on device
~7 GB
Device memory
8 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~7 GB usable
Q2_K
~4.9 GB
Q3_K_M
~5.4 GB
Q4_K_M
~5.7 GB
Q5_K_M
~7.2 GB
Q6_K
~8.1 GB
Q8_0
~8.4 GB
FP16
~15.2 GB
The line marks Nvidia GeForce GTX 1070 (8GB)'s ~7 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~150 W
Electricity / 1M tokens
~$0.16
Pays for itself after
~1,115M tok

At ~$0.15/kWh and the estimated ~39 tok/s, a million generated tokens costs about $0.16 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$379 Nvidia GeForce GTX 1070 (8GB) pays for itself after roughly 1,115 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands Windows

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama
$ ollama run gemma3n:e4b
llama.cpp
$ llama-cli -hf unsloth/gemma-3n-E4B-it-GGUF:Q4_K_M
LM Studio
$ lms get unsloth/gemma-3n-E4B-it-GGUF
Model Gemma
Parameters
8B
Q4_K_M size
4.23 GB
Q8_0 size
6.85 GB
Context
32k
Ollama tag
gemma3n:e4b
Full Gemma 3n E4B requirements →
Device Windows
Memory
8 GB vram
Usable for weights
~7 GB
Power draw
~150 W
Best runtime
llama.cpp CUDA (Pascal, no tensor cores)
Best models for Nvidia GeForce GTX 1070 (8GB) →

You could also run

Run Gemma 3n E4B on other hardware

FAQ

Can Nvidia GeForce GTX 1070 (8GB) run Gemma 3n E4B?

Yes. Gemma 3n E4B runs on Nvidia GeForce GTX 1070 (8GB) at Q4_K_M (~5.7 GB of ~7 GB usable).

How much memory does Gemma 3n E4B need?

Nvidia GeForce GTX 1070 (8GB) has room to spare. At Q4_K_M the weights are ~4.23 GB; with KV cache and runtime overhead, budget ~5.7 GB at a 4k context.

What is the best tool to run Gemma 3n E4B on Windows?

LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

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Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.