RTX 5070 12GB经济之选12 GB VRAM (+1)672 GB/s (+188)
B
Raises estimated decode speed by about 48%.86.8 tok/s 解码
Raises estimated decode speed by about 48%.
~$549 MSRP
Can DeepSeek R1 Distill Llama 8B run on GTX 1080 Ti 11GB?
YES — Runs Great
B56Good
Estimated from fit model
DeepSeek R1 Distill Llama 8B needs ~8.1 GB VRAM. GTX 1080 Ti 11GB has 11.0 GB. With Q4_K_M quantization, expect ~59 tok/s.
Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: BasicBottleneck: Balanced
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) — 8.1 GB, 58.5 tok/s, Runs well
8.1 GB required11.0 GB available
74% VRAM used
Fit status
Runs well
Decode
58.5 tok/s
TTFT
3308 ms
Safe context
65K
Memory
8.1 GB / 11.0 GB
Memory breakdown
Weights4.9 GB
KV Cache0.9 GB
Runtime1.2 GB
Headroom1.1 GB
See how fast it feels
See how fast it feelsDeepSeek R1 Distill Llama 8B on GTX 1080 Ti 11GB
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: 58.5 tok/s decode · 3.3s TTFT (warm) · 146 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 58.5 tok/s | 1805 ms | 65K |
| Coding | B | Runs well | 58.5 tok/s | 3308 ms | 65K |
| Agentic Coding | C | Tight fit | 58.5 tok/s | 4812 ms | 65K |
| Reasoning | B | Runs well | 58.5 tok/s | 3910 ms | 65K |
| RAG | C | Tight fit | 58.5 tok/s | 6015 ms | 65K |
Quantization options
How DeepSeek R1 Distill Llama 8B (8B params) fits at each quantization level on GTX 1080 Ti 11GB (11.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 3.1 GB | Low | C50 |
Q3_K_S | 3 | 3.9 GB | Low | C52 |
NVFP4 | 4 | 4.5 GB | Medium | C53 |
Q4_K_M | 4 | 4.9 GB | Medium | C53 |
Q5_K_M | 5 | 5.8 GB | High | C53 |
Q6_KBest for your GPU | 6 | 6.6 GB | High | C52 |
Q8_0 | 8 | 8.6 GB | Very High | F0 |
F16 | 16 | 16.4 GB | Maximum | F0 |
Get started
Copy-paste commands to run DeepSeek R1 Distill Llama 8B on your machine.
Run
lms load hf-unsloth--deepseek-r1-distill-llama-8b-gguf && lms server start升级选项
能流畅运行 DeepSeek R1 Distill Llama 8B 的硬件
RTX 5070 12GB经济之选RTX 4070 Super 12GB最佳性价比12 GB VRAM (+1)504 GB/s (+20)
B
Raises estimated decode speed by about 36%.79.5 tok/s 解码
Raises estimated decode speed by about 36%.
~$599 MSRP
RTX 4070 12GBNVIDIA 升级12 GB VRAM (+1)504 GB/s (+20)
B
Raises estimated decode speed by about 32%.77.5 tok/s 解码
Raises estimated decode speed by about 32%.
~$599 MSRP
Frequently asked questions
Can GTX 1080 Ti 11GB run DeepSeek R1 Distill Llama 8B?
Yes, GTX 1080 Ti 11GB can run DeepSeek R1 Distill Llama 8B with a B grade (Runs well). Expected decode speed: 58.5 tok/s.
How much VRAM does DeepSeek R1 Distill Llama 8B need?
DeepSeek R1 Distill Llama 8B (8B parameters) requires approximately 8.1 GB of memory with Q4_K_M quantization.
What is the best quantization for DeepSeek R1 Distill Llama 8B?
The recommended quantization for DeepSeek R1 Distill Llama 8B is Q4_K_M, which balances quality and memory efficiency.
What speed will DeepSeek R1 Distill Llama 8B run at on GTX 1080 Ti 11GB?
On GTX 1080 Ti 11GB, DeepSeek R1 Distill Llama 8B achieves approximately 58.5 tokens per second decode speed with a time-to-first-token of 3308ms using Q4_K_M quantization.
Can GTX 1080 Ti 11GB run DeepSeek R1 Distill Llama 8B for coding?
For coding workloads, DeepSeek R1 Distill Llama 8B on GTX 1080 Ti 11GB receives a B grade with 58.5 tok/s and 65K context.
What context window can DeepSeek R1 Distill Llama 8B use on GTX 1080 Ti 11GB?
On GTX 1080 Ti 11GB, DeepSeek R1 Distill Llama 8B can safely use up to 65K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
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<iframe src="https://willitrunai.com/embed/hf-unsloth--deepseek-r1-distill-llama-8b-gguf-on-gtx-1080-ti-11gb" 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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