Can the NVIDIA RTX 5060 run DeepSeek V4.1 Flash?

RTX 5060 × DeepSeek V4.1 Flash8K context
NoDoes not fit in memory
Memory at Q4_K_M463.4 GB of 8 GB
Weights 462.6 GBKV cache 0.2 GBRuntime 0.6 GB
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

No. Even at Q4_K_M, DeepSeek V4.1 Flash needs about 463.4 GB, but the NVIDIA RTX 5060 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 8 GB the NVIDIA RTX 5060 can use.

QuantQualityMemoryFits?Speed
FP16Full quality1526.8 GBToo big—
Q8_0Near-lossless811.5 GBToo big—
Q6_KExcellent626.4 GBToo big—
Q5_K_MVery good543.5 GBToo big—
Q4_K_MGood, most popular463.4 GBToo big—
Q3_K_MNoticeably degraded373.7 GBToo big—
Q2_KHeavily degraded286.9 GBToo big—

Measured speed from real RTX 5060 owners

Tokens per second that people measured on their own NVIDIA RTX 5060, next to our estimate.

No one has measured DeepSeek V4.1 Flash on the NVIDIA RTX 5060 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 5060? Add your real speed

One command times DeepSeek V4.1 Flash in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh

Windows (PowerShell)

irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

Frequently asked questions

Can NVIDIA RTX 5060 run DeepSeek V4.1 Flash?

No. Even at Q4_K_M, DeepSeek V4.1 Flash needs about 463.4 GB, but the NVIDIA RTX 5060 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.

How much VRAM does DeepSeek V4.1 Flash need?

About 463.4 GB at Q4_K_M with 8,192 tokens of context, and about 1526.8 GB at full FP16 precision.

How fast is DeepSeek V4.1 Flash on the NVIDIA RTX 5060?

It does not fit in the NVIDIA RTX 5060's memory, so most layers would run from system RAM and generation would be very slow.