32 GB VRAM (+8)1792 GB/s (+1492)
B
Raises estimated decode speed by about 160%.112 tok/s decode
Raises estimated decode speed by about 160%.
Adds memory headroom for longer context windows and future model growth.
~$1,999 MSRP
Can DeepSeek R1 Distill 8B run on NVIDIA L4 24GB?
YES — Runs Great
B65Good
○Estimated from fit model
DeepSeek R1 Distill 8B needs ~10.4 GB VRAM. NVIDIA L4 24GB has 24.0 GB. With Q4_K_M quantization, expect ~40 tok/s.
Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: Balanced
Share:
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 10.4 GB, 43.0 tok/s, Runs well
10.4 GB required24.0 GB available
43% VRAM used
Fit status
Runs well
Decode
43.0 tok/s
TTFT
4507 ms
Safe context
33K
Memory
10.4 GB / 24.0 GB
Memory breakdown
Weights4.9 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom2.4 GB
See how fast it feels
See how fast it feelsDeepSeek R1 Distill 8B on NVIDIA L4 24GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 43.0 tok/s decode · 4.5s TTFT (warm) · 107 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 40.0 tok/s | 2643 ms | 33K |
| Coding | B | Runs well | 40.0 tok/s | 4845 ms | 33K |
| Agentic Coding | B | Runs well | 40.0 tok/s | 7047 ms | 33K |
| Reasoning | B | Runs well | 40.0 tok/s | 5726 ms | 33K |
| RAG | B | Runs well | 40.0 tok/s | 8809 ms | 33K |
Quantization options
How DeepSeek R1 Distill 8B (8B params) fits at each quantization level on NVIDIA L4 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | B61 |
Q3_K_S | 3 | 3.9 GB | Low | B61 |
NVFP4 | 4 |
Get started
Copy-paste commands to run DeepSeek R1 Distill 8B on your machine.
Run
ollama run deepseek-r1:8bUpgrade options
Hardware that runs DeepSeek R1 Distill 8B well
32 GB VRAM (+8)896 GB/s (+596)
B
Raises estimated decode speed by about 160%.112 tok/s decode
Raises estimated decode speed by about 160%.
Adds memory headroom for longer context windows and future model growth.
~$2,499 MSRP
32 GB VRAM (+8)576 GB/s (+276)
B
Raises estimated decode speed by about 136%.101.5 tok/s decode
Raises estimated decode speed by about 136%.
Adds memory headroom for longer context windows and future model growth.
~$4,000 MSRP