Can the NVIDIA RTX 4060 run DeepSeek V4.1 Flash?
- FP16
- Q8_0
- Q6_K
- Q5_K_M
- Q4_K_M
- Q3_K_M
- Q2_K
No. Even at Q4_K_M, DeepSeek V4.1 Flash needs about 463.4 GB, but the NVIDIA RTX 4060 has 8 GB usable. You could offload some layers to system RAM, but it will be very slow.
Run it in the cloud
Too big for the NVIDIA RTX 4060? Run DeepSeek V4.1 Flash on a rented GPU instead.
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Memory needed by quantization
At 8,192 tokens of context. The black line marks the 8 GB the NVIDIA RTX 4060 can use.
| Quant | Quality | Memory | Fits? | Speed | |
|---|---|---|---|---|---|
| FP16 | Full quality | 1526.8 GB | Too big | — | |
| Q8_0 | Near-lossless | 811.5 GB | Too big | — | |
| Q6_K | Excellent | 626.4 GB | Too big | — | |
| Q5_K_M | Very good | 543.5 GB | Too big | — | |
| Q4_K_M | Good, most popular | 463.4 GB | Too big | — | |
| Q3_K_M | Noticeably degraded | 373.7 GB | Too big | — | |
| Q2_K | Heavily degraded | 286.9 GB | Too big | — |
Measured speed from real RTX 4060 owners
Tokens per second that people measured on their own NVIDIA RTX 4060, next to our estimate.
No one has measured DeepSeek V4.1 Flash on the NVIDIA RTX 4060 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.
Have an RTX 4060? 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 | shWindows (PowerShell)
irm https://gpufit.dev/bench.ps1 | iexFrequently asked questions
Can NVIDIA RTX 4060 run DeepSeek V4.1 Flash?
No. Even at Q4_K_M, DeepSeek V4.1 Flash needs about 463.4 GB, but the NVIDIA RTX 4060 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 4060?
It does not fit in the NVIDIA RTX 4060's memory, so most layers would run from system RAM and generation would be very slow.