HomeCan I run it?R1 Distill 70BR1 Distill 70B on dual RTX 3090s
No. R1 Distill 70B at Q4_K_M needs about 50.2 GB, and dual RTX 3090s have 48.0 GB usable at a ~4k context.
Can I run R1 Distill 70B on dual RTX 3090s?
R1 Distill 70B at Q4_K_M needs about 50.2 GB, and dual RTX 3090s have 48.0 GB usable. Two cards add memory, not decode speed; the speed estimate uses one RTX 3090’s 936 GB/s. A 70B DeepSeek-R1 distill on Llama. Memory need matches Llama 3.3 70B; it is not the full DeepSeek-R1. These are estimates from our formula, not measured benchmarks.
- Quant that fits
- None of Q4, Q8 or FP16 needs 50.2 GB
- Memory needed
- 50.2 GB at Q4_K_M, ~4k context
- Usable VRAM
- 48.0 GB of 48 GB VRAM
- Est. tokens/sec
- n/a does not fit
Memory at each quant
| Quant | Need vs 48.0 GB | Verdict |
|---|---|---|
| Q4_K_M | 50.2 GB | Q4Won’t fit |
| Q8_0 | 87.2 GB | Q8Won’t fit |
| FP16 | 163.3 GB | FP16Won’t fit |
Estimated tokens per second
No speed estimate: R1 Distill 70B does not fit in the 48.0 GB this machine can use, so we do not publish a tokens/sec figure for CPU offload.
Context headroom
Even at a short ~4k context, the weights do not fit. Extending context would only increase the gap.
| Context | KV cache (FP16) | Total at Q4_K_M | Verdict |
|---|---|---|---|
| 4k | 1.3 GB | 50.2 GB | Won’t fit |
| 8k | 2.7 GB | 51.5 GB | Won’t fit |
| 16k | 5.4 GB | 54.2 GB | Won’t fit |
| 32k | 10.7 GB | 59.6 GB | Won’t fit |
| 64k | 21.5 GB | 70.3 GB | Won’t fit |
| 128k | 42.9 GB | 91.8 GB | Won’t fit |
What to do instead
- Run R1 Distill 32B instead (23.8 GB at Q4). It is a different model, not a drop-in, but it does fit this machine.
- To hold R1 Distill 70B at Q4, you need about 50.2 GB. The MacBook Pro M5 Max 128GB has 96.0 GB usable ($6699 Apple list price, 14-inch M5 Max 18C CPU/40C GPU, 128GB/2TB).
- Our estimate is only 2.2 GB over this machine’s usable memory, so a tighter quant or a shorter context may work in practice. We still mark it as a no under the published formula.
- CPU offload can load the weights anyway, but it is slow. We do not publish an offload tokens/sec figure.
- See the best GPU for this model family and the DeepSeek-R1-Distill-Llama-70B model page.
Other hardware for R1 Distill 70B
- R1 Distill 70B on an RTX 4090Won’t fit
- R1 Distill 70B on an RTX 5090Won’t fit
- R1 Distill 70B on a Mac mini 64GBWon’t fit
- R1 Distill 70B on a Mac Studio 256GBFits
- R1 Distill 70B on an RTX 3090Won’t fit
Other models on dual RTX 3090s
- Llama 3.3 70B on dual RTX 3090sWon’t fit
- gpt-oss-120b on dual RTX 3090sWon’t fit
- Qwen3-235B on dual RTX 3090sWon’t fit
- DeepSeek-R1 on dual RTX 3090sWon’t fit
- Mixtral 8x22B on dual RTX 3090sWon’t fit
- GLM-4.5-Air on dual RTX 3090sWon’t fit
Quick answers
- Can I run R1 Distill 70B on dual RTX 3090s?
- No. R1 Distill 70B at Q4_K_M needs about 50.2 GB, and dual RTX 3090s have 48.0 GB usable.
- How much VRAM does R1 Distill 70B need?
- About 50.2 GB at Q4_K_M, 87.2 GB at Q8_0 and 163.3 GB at FP16, estimated for a ~4k context.
- How fast is R1 Distill 70B on dual RTX 3090s?
- We do not estimate tokens/sec when the model does not fit. CPU offload is possible but slow.
- What context length can I use?
- The weights already do not fit, so longer context is not the limiting factor.