Can the NVIDIA RTX 4070 Super run Kimi K3.1 Pro 2.8T-A104B?
- FP16
- Q8_0
- Q6_K
- Q5_K_M
- Q4_K_M
- Q3_K_M
- Q2_K
No. Even at Q4_K_M, Kimi K3.1 Pro 2.8T-A104B needs about 1698.3 GB, but the NVIDIA RTX 4070 Super has 12 GB usable. You could offload some layers to system RAM, but it will be very slow.
Run it in the cloud
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Memory needed by quantization
At 8,192 tokens of context. The black line marks the 12 GB the NVIDIA RTX 4070 Super can use.
| Quant | Quality | Memory | Fits? | Speed | |
|---|---|---|---|---|---|
| FP16 | Full quality | 5600.8 GB | Too big | — | |
| Q8_0 | Near-lossless | 2975.8 GB | Too big | — | |
| Q6_K | Excellent | 2296.8 GB | Too big | — | |
| Q5_K_M | Very good | 1992.3 GB | Too big | — | |
| Q4_K_M | Good, most popular | 1698.3 GB | Too big | — | |
| Q3_K_M | Noticeably degraded | 1369.3 GB | Too big | — | |
| Q2_K | Heavily degraded | 1050.8 GB | Too big | — |
Measured speed from real RTX 4070 Super owners
Tokens per second that people measured on their own NVIDIA RTX 4070 Super, next to our estimate.
No one has measured Kimi K3.1 Pro 2.8T-A104B on the NVIDIA RTX 4070 Super yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.
Have an RTX 4070 Super? Add your real speed
One command times Kimi K3.1 Pro 2.8T-A104B 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 4070 Super run Kimi K3.1 Pro 2.8T-A104B?
No. Even at Q4_K_M, Kimi K3.1 Pro 2.8T-A104B needs about 1698.3 GB, but the NVIDIA RTX 4070 Super has 12 GB usable. You could offload some layers to system RAM, but it will be very slow.
How much VRAM does Kimi K3.1 Pro 2.8T-A104B need?
About 1698.3 GB at Q4_K_M with 8,192 tokens of context, and about 5600.8 GB at full FP16 precision.
How fast is Kimi K3.1 Pro 2.8T-A104B on the NVIDIA RTX 4070 Super?
It does not fit in the NVIDIA RTX 4070 Super's memory, so most layers would run from system RAM and generation would be very slow.