Can the AMD Radeon RX 9070 run DeepSeek V4 Pro 1.6T-A49B?
- FP16
- Q8_0
- Q6_K
- Q5_K_M
- Q4_K_M
- Q3_K_M
- Q2_K
No. Even at Q4_K_M, DeepSeek V4 Pro 1.6T-A49B needs about 971.2 GB, but the AMD Radeon RX 9070 has 16 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 16 GB the AMD Radeon RX 9070 can use.
| Quant | Quality | Memory | Fits? | Speed | |
|---|---|---|---|---|---|
| FP16 | Full quality | 3201.2 GB | Too big | — | |
| Q8_0 | Near-lossless | 1701.2 GB | Too big | — | |
| Q6_K | Excellent | 1313.2 GB | Too big | — | |
| Q5_K_M | Very good | 1139.2 GB | Too big | — | |
| Q4_K_M | Good, most popular | 971.2 GB | Too big | — | |
| Q3_K_M | Noticeably degraded | 783.2 GB | Too big | — | |
| Q2_K | Heavily degraded | 601.2 GB | Too big | — |
Measured speed from real Radeon RX 9070 owners
Tokens per second that people measured on their own AMD Radeon RX 9070, next to our estimate.
No one has measured DeepSeek V4 Pro 1.6T-A49B on the AMD Radeon RX 9070 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.
Have a Radeon RX 9070? Add your real speed
One command times DeepSeek V4 Pro 1.6T-A49B 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 AMD Radeon RX 9070 run DeepSeek V4 Pro 1.6T-A49B?
No. Even at Q4_K_M, DeepSeek V4 Pro 1.6T-A49B needs about 971.2 GB, but the AMD Radeon RX 9070 has 16 GB usable. You could offload some layers to system RAM, but it will be very slow.
How much VRAM does DeepSeek V4 Pro 1.6T-A49B need?
About 971.2 GB at Q4_K_M with 8,192 tokens of context, and about 3201.2 GB at full FP16 precision.
How fast is DeepSeek V4 Pro 1.6T-A49B on the AMD Radeon RX 9070?
It does not fit in the AMD Radeon RX 9070's memory, so most layers would run from system RAM and generation would be very slow.