RX 7600 XT 16GBコスパ重視
16 GB VRAM (+4)
C
Adds memory headroom for longer context windows and future model growth.19.6 tok/sデコード
Adds memory headroom for longer context windows and future model growth.
〜$329 MSRP
Can DeepSeek R1 Distill Qwen 14B run on RX 6750 XT 12GB?
YES — With Offload
C49Usable
Estimated from fit model
DeepSeek R1 Distill Qwen 14B needs ~12.3 GB VRAM. RX 6750 XT 12GB has 12.0 GB. With Q4_K_M quantization, expect ~19 tok/s.
Runtime: llama.cppCapacity: OffloadBandwidth: LowStack: StandardBottleneck: 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) — 12.3 GB, 19.2 tok/s, Runs with offload (needs ~0.2 GB host RAM)
12.3 GB required12.0 GB available
103% VRAM needed
0.3 GB over capacity — needs offload or smaller quantization
Fit status
Runs with offload (needs ~0.2 GB host RAM)
Decode
19.2 tok/s
TTFT
10108 ms
Safe context
13K
Memory
12.3 GB / 12.0 GB
Memory breakdown
Weights8.5 GB
KV Cache1.6 GB
Runtime0.9 GB
Headroom1.2 GB
See how fast it feels
See how fast it feelsDeepSeek R1 Distill Qwen 14B on RX 6750 XT 12GB
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: 19.2 tok/s decode · 10.1s TTFT (warm) · 48 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
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.
Best improvement path
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | C | Runs with offload | 26.8 tok/s | 3939 ms | 13K |
| Coding | C | Runs with offload (needs ~0.2 GB host RAM) | 19.2 tok/s | 10108 ms | 13K |
| Agentic Coding | D | Very compromised (needs ~1.2 GB host RAM) | 14.7 tok/s | 19144 ms | 13K |
| Reasoning | C | Runs with offload (needs ~0.2 GB host RAM) | 19.2 tok/s | 11946 ms | 13K |
| RAG | D | Very compromised (needs ~1.2 GB host RAM) | 14.7 tok/s | 23930 ms | 13K |
Quantization options
How DeepSeek R1 Distill Qwen 14B (14B params) fits at each quantization level on RX 6750 XT 12GB (12.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C53 |
Q3_K_S | 3 | 6.9 GB | Low | C52 |
NVFP4 | 4 | 7.8 GB | Medium | C52 |
Q4_K_MBest for your GPU | 4 | 8.5 GB | Medium | C52 |
Q5_K_M | 5 | 10.1 GB | High | F0 |
Q6_K | 6 | 11.5 GB | High | F0 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Get started
Copy-paste commands to run DeepSeek R1 Distill Qwen 14B on your machine.
Run
lms load hf-unsloth--deepseek-r1-distill-qwen-14b-gguf && lms server startアップグレードオプション
DeepSeek R1 Distill Qwen 14Bを快適に動かすハードウェア
RX 9060 XT 16GBコスパ最良
16 GB VRAM (+4)
C
Adds memory headroom for longer context windows and future model growth.23.6 tok/sデコード
Adds memory headroom for longer context windows and future model growth.
〜$349 MSRP
RX 9070 16GBAMDアップグレード
16 GB VRAM (+4)640 GB/s (+208)
C
Raises estimated decode speed by about 142%.46.5 tok/sデコード
Raises estimated decode speed by about 142%.
Adds memory headroom for longer context windows and future model growth.
〜$479 MSRP
Frequently asked questions
Can RX 6750 XT 12GB run DeepSeek R1 Distill Qwen 14B?
Yes, RX 6750 XT 12GB can run DeepSeek R1 Distill Qwen 14B with a C grade (Runs with offload (needs ~0.2 GB host RAM)). Expected decode speed: 19.2 tok/s.
How much VRAM does DeepSeek R1 Distill Qwen 14B need?
DeepSeek R1 Distill Qwen 14B (14B parameters) requires approximately 12.3 GB of memory with Q4_K_M quantization.
What is the best quantization for DeepSeek R1 Distill Qwen 14B?
The recommended quantization for DeepSeek R1 Distill Qwen 14B is Q4_K_M, which balances quality and memory efficiency.
What speed will DeepSeek R1 Distill Qwen 14B run at on RX 6750 XT 12GB?
On RX 6750 XT 12GB, DeepSeek R1 Distill Qwen 14B achieves approximately 19.2 tokens per second decode speed with a time-to-first-token of 10108ms using Q4_K_M quantization.
Can RX 6750 XT 12GB run DeepSeek R1 Distill Qwen 14B for coding?
For coding workloads, DeepSeek R1 Distill Qwen 14B on RX 6750 XT 12GB receives a C grade with 19.2 tok/s and 13K context.
What context window can DeepSeek R1 Distill Qwen 14B use on RX 6750 XT 12GB?
On RX 6750 XT 12GB, DeepSeek R1 Distill Qwen 14B can safely use up to 13K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.
What should I upgrade first if DeepSeek R1 Distill Qwen 14B feels slow on RX 6750 XT 12GB?
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
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<iframe src="https://willitrunai.com/embed/hf-unsloth--deepseek-r1-distill-qwen-14b-gguf-on-rx-6750-xt-12gb" 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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