CanRun

Phi-4 hardware requirements

Open license · MITChatReasoning

What is Phi-4?

Phi-4 is a 14B dense model from Microsoft Research, released in December 2024. It was trained on a blend of synthetic "textbook-like" data, filtered web data and academic books, with a focus on reasoning and logic such as math and coding. Microsoft aims it mainly at English, its context window is 16k tokens, and the MIT license allows commercial use.

Model card

About the model

Parameters
14.7B
Attention
Full attention
Max context
16,384 tokens
Released
2024-12-12

GGUF files

Tracked quantizations of Phi-4, smallest first
QuantFile sizeQualityPublished by
Q4_K_Mbaseline9.05 GBGood balanceCommunity GGUF · lmstudio-community
Q6_K12.03 GBNear-losslessCommunity GGUF · lmstudio-community
Q8_015.58 GBNear-losslessCommunity GGUF · lmstudio-community

Memory needed by quant and context

Graphics card memory in GB: weights loaded on the GPU + f16 KV cache + compute buffer. Add about 0.6 GB if the GPU also drives your display on Windows. Part of the file stays off the graphics card: llama.cpp keeps the input embedding table in system RAM. A Mac counts the whole file, so it needs a little more.
Quant4k8k16k
Q4_K_M10.111.012.8
Q6_K13.013.915.6
Q8_016.417.319.0

Which GPUs can run Phi-4?

How to read the verdicts

Runs great
Fully on the GPU at 20 tok/s or more
Runs well
Fully on the GPU at 8–20 tok/s; MoE experts in system RAM at 20 tok/s or more; or at least 90% on the GPU at 8 tok/s or more
Runs slowly
2–8 tok/s; CPU-only; less than 90% on the GPU; or MoE experts in system RAM below 20 tok/s
Won't run
Does not fit, or under 2 tok/s

Dense models split between GPU and CPU slow down sharply — the CPU side sets the pace. MoE models that keep only their experts in system RAM degrade far more gently.

Filter this list by budget, type and context in the calculator

Scroll sideways to see every column.

58 GPUs, Macs and CPU setups at Q4_K_M with 8k context, sorted by verdict and speed
HardwareVerdictSpeedQuantMemoryRuns asContextNotesPrice
GeForce RTX 5090
Runs great
est. 116.9 tok/s102.9–131.0calibrated estimate ±12%
Q4_K_M11.6 / 32.0 GBFull GPUup to 16k—$4,200 street (as of 2026-08-09)
NVIDIA RTX PRO 6000 Blackwell
Runs great
est. 116.9 tok/s102.9–131.0calibrated estimate ±12%
Q4_K_M11.6 / 96.0 GBFull GPUup to 16k——
NVIDIA RTX PRO 6000 Blackwell Max-Q
Runs great
est. 116.9 tok/s102.9–131.0calibrated estimate ±12%
Q4_K_M11.6 / 96.0 GBFull GPUup to 16k——
Radeon RX 7900 XTX
Runs great
est. 68.0 tok/s59.8–76.2calibrated estimate ±12%
Q4_K_M11.6 / 24.0 GBFull GPUup to 16k—$999 launch MSRP
GeForce RTX 3090 Ti
Runs great
est. 65.8 tok/s57.9–73.7calibrated estimate ±12%
Q4_K_M11.6 / 24.0 GBFull GPUup to 16k—$1,999 launch MSRP
GeForce RTX 4090
Runs great
est. 65.8 tok/s57.9–73.7calibrated estimate ±12%
Q4_K_M11.6 / 24.0 GBFull GPUup to 16k—$2,755 street (as of 2026-08-09)
Apple M5 Ultra · 96 GB
Runs great
est. 65.2 tok/s52.2–78.3calibrated estimate ±20%
Q4_K_M11.3 / 67.2 GBUnified memoryup to 16k——
GeForce RTX 5080
Runs great
est. 62.6 tok/s55.1–70.2calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$1,256 street (as of 2026-08-09)
GeForce RTX 3090
Runs great
est. 61.1 tok/s53.7–68.4calibrated estimate ±12%
Q4_K_M11.6 / 24.0 GBFull GPUup to 16k—$1,050 street (as of 2026-08-09)
GeForce RTX 3080 12GB
Runs great
est. 59.5 tok/s52.4–66.7calibrated estimate ±12%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k—$799 launch MSRP
GeForce RTX 5070 Ti
Runs great
est. 58.5 tok/s51.4–65.5calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$949 street (as of 2026-08-09)
GeForce RTX 5080 Laptop
Runs great
est. 58.5 tok/s51.4–65.5calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k——
GeForce RTX 5090 Laptop
Runs great
est. 58.5 tok/s51.4–65.5calibrated estimate ±12%
Q4_K_M11.6 / 24.0 GBFull GPUup to 16k——
Radeon RX 7900 XT
Runs great
est. 56.7 tok/s49.9–63.5calibrated estimate ±12%
Q4_K_M11.6 / 20.0 GBFull GPUup to 16k—$899 launch MSRP
GeForce RTX 4080 Super
Runs great
est. 48.0 tok/s42.3–53.8calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$999 launch MSRP
GeForce RTX 4080
Runs great
est. 46.8 tok/s41.2–52.4calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$1,199 launch MSRP
Radeon RX 9070
Runs great
est. 45.7 tok/s40.2–51.2calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$639 street (as of 2026-08-09)
Radeon RX 9070 XT
Runs great
est. 45.7 tok/s40.2–51.2calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$689 street (as of 2026-08-09)
Radeon RX 7800 XT
Runs great
est. 44.2 tok/s38.9–49.5calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$499 launch MSRP
GeForce RTX 4070 Ti Super
Runs great
est. 43.8 tok/s38.6–49.1calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$799 launch MSRP
GeForce RTX 5070
Runs great
est. 43.8 tok/s38.6–49.1calibrated estimate ±12%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k—$629 street (as of 2026-08-09)
GeForce RTX 5070 Ti Laptop
Runs great
est. 43.8 tok/s38.6–49.1calibrated estimate ±12%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k——
Apple M3 Ultra · 96 GB
Runs great
est. 43.5 tok/s34.8–52.2calibrated estimate ±20%
Q4_K_M11.3 / 67.2 GBUnified memoryup to 16k——
Apple M5 Max (40-core GPU) · 48 GB
Runs great
est. 43.5 tok/s34.8–52.2calibrated estimate ±20%
Q4_K_M11.3 / 33.6 GBUnified memoryup to 16k——
Apple M2 Ultra · 64 GB
Runs great
est. 42.5 tok/s34.0–51.0calibrated estimate ±20%
Q4_K_M11.3 / 44.8 GBUnified memoryup to 16k——
Apple M4 Max (40-core GPU) · 48 GB
Runs great
est. 38.7 tok/s30.9–46.4calibrated estimate ±20%
Q4_K_M11.3 / 33.6 GBUnified memoryup to 16k——
GeForce RTX 4090 Laptop
Runs great
est. 37.6 tok/s33.1–42.1calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k——
GeForce RTX 4070
Runs great
est. 32.9 tok/s28.9–36.8calibrated estimate ±12%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k—$599 launch MSRP
GeForce RTX 4070 Super
Runs great
est. 32.9 tok/s28.9–36.8calibrated estimate ±12%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k—$599 launch MSRP
Apple M5 Max (32-core GPU) · 36 GB
Runs great
est. 32.6 tok/s26.1–39.1calibrated estimate ±20%
Q4_K_M11.3 / 25.2 GBUnified memoryup to 16k——
GeForce RTX 5060 Ti 16GB
Runs great
est. 29.2 tok/s25.7–32.7calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$569 street (as of 2026-08-09)
Apple M4 Max (32-core GPU) · 36 GB
Runs great
est. 29.0 tok/s23.2–34.9calibrated estimate ±20%
Q4_K_M11.3 / 25.2 GBUnified memoryup to 16k——
GeForce RTX 4080 Laptop
Runs great
est. 28.2 tok/s24.8–31.6calibrated estimate ±12%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k——
Intel Arc B580
Runs great
est. 25.1 tok/s20.1–30.1calibrated estimate ±20%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k—$290 street (as of 2026-08-09)
GeForce RTX 3060 12GB
Runs great
est. 23.5 tok/s20.7–26.3calibrated estimate ±12%
Q4_K_M11.6 / 12.0 GBFull GPUup to 8k—$250 street (as of 2026-08-09)
Radeon RX 9060 XT 16GB
Runs great
est. 22.8 tok/s20.1–25.5calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 8k—$449 street (as of 2026-08-09)
Apple M5 Pro · 24 GB
Runs great
est. 21.7 tok/s17.4–26.1calibrated estimate ±20%
Q4_K_M11.3 / 16.8 GBUnified memoryup to 8k——
GeForce RTX 2080 Ti
Runs well
est. 21.6 tok/s17.3–25.9calibrated estimate ±20%
Q4_K_M11.0 / 11.0 GB + 0.9 GB RAMPartial offloadup to 8k
  • Not fully on the GPU — Runs great needs the whole model in GPU memory
$999 launch MSRP
NVIDIA DGX Spark · 128 GB
Runs well
est. 19.8 tok/s15.9–23.8calibrated estimate ±20%
Q4_K_M11.3 / 116.9 GBUnified memoryup to 16k—$3,999 launch MSRP (128 GB)
Ryzen AI Max+ 395 (Strix Halo) · 32 GB
Runs well
est. 19.6 tok/s15.7–23.5calibrated estimate ±20%
Q4_K_M11.3 / 22.4 GBUnified memoryup to 16k—$1,999 launch MSRP (128 GB)
Apple M4 Pro · 24 GB
Runs well
est. 19.3 tok/s15.5–23.2calibrated estimate ±20%
Q4_K_M11.3 / 16.8 GBUnified memoryup to 16k——
GeForce GTX 1080 Ti
Runs well
est. 19.1 tok/s13.4–24.8theoretical estimate ±30%
Q4_K_M11.0 / 11.0 GB + 0.9 GB RAMPartial offloadup to 8k—$699 launch MSRP
GeForce RTX 4060 Ti 16GB
Runs well
est. 18.8 tok/s16.5–21.0calibrated estimate ±12%
Q4_K_M11.6 / 16.0 GBFull GPUup to 16k—$499 launch MSRP
Apple M6 · 24 GB
Runs well
est. 12.1 tok/s9.7–14.5calibrated estimate ±20%
Q4_K_M11.3 / 16.8 GBUnified memoryup to 16k——
Apple M5 · 24 GB
Runs well
est. 10.9 tok/s8.7–13.1calibrated estimate ±20%
Q4_K_M11.3 / 16.8 GBUnified memoryup to 16k——
Apple M4 · 24 GB
Runs well
est. 8.5 tok/s6.8–10.2calibrated estimate ±20%
Q4_K_M11.3 / 16.8 GBUnified memoryup to 8k——
GeForce RTX 3080 10GB
Runs slowly
est. 15.1 tok/s12.1–18.1calibrated estimate ±20%
Q4_K_M10.0 / 10.0 GB + 1.9 GB RAMPartial offloadup to 16k
  • Less than 90% on the GPU — a GPU/CPU split is capped at Runs slowly
$699 launch MSRP
GeForce RTX 3070
Runs slowly
est. 8.1 tok/s6.5–9.8calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k
  • Less than 90% on the GPU — a GPU/CPU split is capped at Runs slowly
$499 launch MSRP
GeForce RTX 5060
Runs slowly
est. 8.1 tok/s6.5–9.8calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k
  • Less than 90% on the GPU — a GPU/CPU split is capped at Runs slowly
$339 street (as of 2026-08-09)
GeForce RTX 5060 Ti 8GB
Runs slowly
est. 8.1 tok/s6.5–9.8calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k
  • Less than 90% on the GPU — a GPU/CPU split is capped at Runs slowly
$429 street (as of 2026-08-09)
GeForce RTX 4060 Ti 8GB
Runs slowly
est. 7.5 tok/s6.0–9.0calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k—$399 launch MSRP
GeForce RTX 4060
Runs slowly
est. 7.4 tok/s5.9–8.9calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k—$299 launch MSRP
GeForce RTX 4060 Laptop
Runs slowly
est. 7.3 tok/s5.8–8.7calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k——
GeForce RTX 4070 Laptop
Runs slowly
est. 7.3 tok/s5.8–8.7calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k——
GeForce RTX 3050 8GB
Runs slowly
est. 7.0 tok/s5.6–8.4calibrated estimate ±20%
Q4_K_M8.0 / 8.0 GB + 3.9 GB RAMPartial offloadup to 16k—$249 launch MSRP
DDR5-6000 dual-channel CPU · 16 GB
Runs slowly
est. 4.5 tok/s3.6–5.4calibrated estimate ±20%
Q4_K_M10.7 GB RAMCPU onlyup to 8k——
DDR5-5600 dual-channel CPU · 16 GB
Runs slowly
est. 4.2 tok/s3.3–5.0calibrated estimate ±20%
Q4_K_M10.7 GB RAMCPU onlyup to 8k——
DDR4-3200 dual-channel CPU · 16 GB
Runs slowly
est. 2.4 tok/s1.9–2.9calibrated estimate ±20%
Q4_K_M10.7 GB RAMCPU onlyup to 8k——

Cheapest GPUs that run it

  • Runs greatGeForce RTX 3060 12GB$250 street (as of 2026-08-09), est. 23.5 tok/s (20.7–26.3, calibrated estimate ±12%).

Measured results for Phi-4

No public measurements for this model yet.

Frequently asked questions

How much VRAM does Phi-4 need?

At Q4_K_M the file is 9.05 GB; with 8k context a graphics card needs about 11.0 GB (weights 8.76 GB, KV cache 1.7 GB, compute buffer 0.6 GB). Part of the file stays off the graphics card: llama.cpp keeps the input embedding table in system RAM. A Mac counts the whole file, so it needs a little more.

What is the cheapest GPU that runs Phi-4 well?

Cheapest that runs it great: GeForce RTX 3060 12GB at $250 (street price as of 2026-08-09), est. 23.5 tok/s (20.7–26.3, calibrated estimate ±12%).

Can Phi-4 run on an 8 GB, 16 GB or 24 GB GPU?

At Q4_K_M with 8k context: GeForce RTX 4060 — Runs slowly, est. 7.4 tok/s (5.9–8.9, calibrated estimate ±20%); GeForce RTX 5060 Ti 16GB — Runs great, est. 29.2 tok/s (25.7–32.7, calibrated estimate ±12%); GeForce RTX 3090 — Runs great, est. 61.1 tok/s (53.7–68.4, calibrated estimate ±12%).

Speeds are estimates from memory bandwidth, calibrated against public benchmarks, and each one comes with an error band and a confidence label. Real results vary with drivers, backend, context length and thermals.