DeepSeek R1 Distill 8B needs ~8.8 GB VRAM. RTX 4060 8GB has 8.0 GB. With Q4_K_M quantization, expect ~27 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
0.8 GB over capacity — needs offload or smaller quantization
Fit status
Very compromised (needs ~0.5 GB host RAM)
Decode
26.6 tok/s
TTFT
7270 ms
Safe context
9K
Memory
8.8 GB / 8.0 GB
Offload
10%
It fits through host-memory offload, and offload is the main reason performance drops.
CPU or host-memory offload is active
About 10% of the working set spills out of accelerator memory, which usually hurts latency and sustained decode throughput.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Remove offload with more accelerator memory
Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Increase host RAM if you keep offloading
This setup may need roughly 0.5 GB of extra host RAM just for the offloaded portion, before OS and other tools.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs with offload | 43.7 tok/s | 2414 ms | 9K |
| Coding | B | Very compromised (needs ~0.5 GB host RAM) | 26.6 tok/s | 7270 ms | 9K |
| Agentic Coding | F | Too heavy | 17.5 tok/s | 16102 ms | 9K |
| Reasoning | B | Very compromised (needs ~0.5 GB host RAM) | 26.6 tok/s | 8592 ms | 9K |
| RAG | F | Too heavy | 17.5 tok/s | 20127 ms | 9K |
How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on RTX 4060 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | A70 |
Q3_K_S | 3 | 3.9 GB | Low | B70 |
NVFP4 | 4 | 4.5 GB | Medium | B70 |
Q4_K_MBest for your GPU | 4 | 4.9 GB | Medium | B69 |
Q5_K_M | 5 | 5.8 GB | High | F0 |
Q6_K | 6 | 6.6 GB | High | F0 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Copy-paste commands to run DeepSeek R1 Distill 8B on your machine.
Run
ollama run deepseek-r1:8bアップグレードオプション
RTX 3060 12GBコスパ重視Removes host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 97%.
〜$329 MSRP
RTX 5060 Ti 16GBコスパ最良Removes host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 130%.
〜$449 MSRP
RTX 4060 Ti 16GBNVIDIAアップグレードRemoves host-memory offload, which is usually the single biggest latency and throughput win.
Raises estimated decode speed by about 74%.
〜$499 MSRP
Yes, RTX 4060 8GB can run DeepSeek R1 Distill 8B with a B grade (Very compromised (needs ~0.5 GB host RAM)). Expected decode speed: 26.6 tok/s.
DeepSeek R1 Distill 8B (8B parameters) requires approximately 8.8 GB of memory with Q4_K_M quantization.
The recommended quantization for DeepSeek R1 Distill 8B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4060 8GB, DeepSeek R1 Distill 8B achieves approximately 26.6 tokens per second decode speed with a time-to-first-token of 7270ms using Q4_K_M quantization.
For coding workloads, DeepSeek R1 Distill 8B on RTX 4060 8GB receives a B grade with 26.6 tok/s and 9K context.
On RTX 4060 8GB, DeepSeek R1 Distill 8B can safely use up to 9K tokens of context. The model's official context limit is 33K, but available memory constrains the safe maximum.
Remove offload with more accelerator memory. Prioritize a GPU or unified-memory tier that fits the whole model natively. Removing offload usually helps more than small compute gains.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/deepseek-r1-distill-8b-on-rtx-4060-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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