text model · Phi-4 · Windows
Can I run Phi-4-reasoning on Nvidia GeForce GTX 1070 (8GB)?
No. Phi-4-reasoning needs ~10.1 GB even at Q4_K_M, but Nvidia GeForce GTX 1070 (8GB) only has ~7 GB usable.
Needs ~10.1 GB even at Q4_K_M, but only ~7 GB is usable.
That figure is at a 4k context and moves about ±15% as context length changes.
The gap is about 3.1 GB: Phi-4-reasoning needs roughly 10.1 GB at Q4_K_M and Nvidia GeForce GTX 1070 (8GB) leaves only about 7 GB usable for a model. The lightest tracked hardware that runs Phi-4-reasoning is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Phi-4-reasoning on Nvidia GeForce RTX 3060 (12GB).
Too big for Nvidia GeForce GTX 1070 (8GB)'s VRAM, but you could offload some layers to system RAM and still run it at roughly ~11 tok/s, far slower than a model that fits. How this is estimated.
- Q4_K_M needed
- ~10.1 GB
- Usable on device
- ~7 GB
- Device memory
- 8 GB
Which quant fits
- Parameters
- 14B
- Q4_K_M size
- 8.43 GB
- Q8_0 size
- 14.51 GB
- Context
- 32k
- Ollama tag
- phi4-reasoning:14b
- Memory
- 8 GB vram
- Usable for weights
- ~7 GB
- Power draw
- ~150 W
- Best runtime
- llama.cpp CUDA (Pascal, no tensor cores)
What you can run instead
Run Phi-4-reasoning on other hardware
FAQ
Can Nvidia GeForce GTX 1070 (8GB) run Phi-4-reasoning?
No. Phi-4-reasoning needs ~10.1 GB even at Q4_K_M, but Nvidia GeForce GTX 1070 (8GB) only has ~7 GB usable.
How much memory does Phi-4-reasoning need?
Nvidia GeForce GTX 1070 (8GB) does not have enough memory. At Q4_K_M the weights are ~8.43 GB; with KV cache and runtime overhead, budget ~10.1 GB at a 4k context.
What is the best tool to run Phi-4-reasoning 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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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/phi-4-reasoning/nvidia-gtx-1070-8gb) 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.