Home / Models / DeepSeek R1 Distill Qwen 7B / NVIDIA RTX 5070 Ti 16 GB
Can DeepSeek R1 Distill Qwen 7B run on NVIDIA RTX 5070 Ti 16 GB?
Yes. Calculated memory fit: DeepSeek R1 Distill Qwen 7B can run entirely in this GPU’s usable VRAM at one or more supported quantizations.
Can it run?
- Can it run?
- Yes, full GPU fit (calculated estimate).
- Full GPU fit?
- Yes
- Model
- DeepSeek R1 Distill Qwen 7B · 7.6B
- GPU
- NVIDIA RTX 5070 Ti 16 GB · 16 GB advertised
What else can NVIDIA RTX 5070 Ti 16 GB run? · Find other GPUs for DeepSeek R1 Distill Qwen 7B
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 4.5 GB |
|---|---|
| KV cache | 0.4 GB |
| Runtime reserve | 0.7 GB |
| Safety margin | 0.4 GB |
| Required (estimated) | 6.0 GB |
| GPU usable VRAM | 14.4 GB |
Result: FITS IN VRAM
Quantization table
| Quantization | 2K | 4K | 8K | 16K | 32K | 64K | 128K |
|---|---|---|---|---|---|---|---|
| BF16 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
| FP16 | Offload | Offload | Offload | Offload | Offload | Offload | Offload |
| Q3 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
| Q4 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
| Q5 | Fits | Fits | Fits | Fits | Fits | Fits | Fits |
| Q6 | Fits | Fits | Fits | Fits | Fits | Fits | Limited context |
| Q8 | Fits | Fits | Fits | Fits | Fits | Fits | Limited context |
What fits entirely in VRAM?
- Q3 at 128K context
- Q3 at 16K context
- Q3 at 2K context
- Q3 at 32K context
- Q3 at 4K context
- Q3 at 64K context
- Q3 at 8K context
- Q4 at 128K context
- Q4 at 16K context
- Q4 at 2K context
- Q4 at 32K context
- Q4 at 4K context
What requires RAM offload?
Offload is shown only when the model does not fully fit in usable VRAM but stays within the modeled offload allowance.
Performance
Separate from memory fit. Runtime is llama.cpp · quantization bucket Q4 (GGUF Q4_0 maps to Q4). Workload is llama-bench pp512 / tg128 (short context, batch 1, full GPU offload). This is not a ranking and not a 8K–128K speed claim.
- Model
- DeepSeek R1 Distill Qwen 7B
- GPU
- NVIDIA RTX 5070 Ti 16 GB
- Runtime
- llama.cpp · CUDA · model 1.0.0
- Decode
- ~145 tok/s · Calibrated estimate · HIGH confidence (spread ~128 tok/s–~163 tok/s)
- Prefill
- ~7447 tok/s at a 512-token prompt · Calibrated estimate · MEDIUM confidence
- Time to first token
- ~69 ms for a 512-token prompt (512 / prefill tok/s). Not estimated at 8K–128K.
decode_tps = GPU_efficiency × memory_bandwidth / model_weight_bytes; efficiency from same-gpu Llama 2 7B Q4_0 efficiency
Available graphics cards
These SKUs use this GPU chip. Amazon CTAs appear only for EXACT/HIGH matches. Absence of a price does not change the compatibility result above.
ASUS Prime -RTX5070TI-O16G NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7
16 GB · Amazon EXACT
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ASUS TUF Gaming TUF-RTX5070TI-O16G-GAMING NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7
16 GB · Amazon EXACT
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MSI GeForce RTX 5070 Ti 16G VENTUS 3X OC NVIDIA 16 GB GDDR7
16 GB · Amazon EXACT
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GIGABYTE GeForce RTX 5070 Ti GAMING OC 16G Graphics Card
16 GB · Amazon EXACT
Check price on AmazonASUS Prime -RTX5070TI-16G NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7
16 GB · Amazon EXACT
Check price on Amazon
MSI GAMING GeForce RTX 5070 Ti 16G TRIO OC NVIDIA 16 GB GDDR7
16 GB · Amazon EXACT
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ASUS ROG -STRIX-RTX5070TI-O16G-GAMING NVIDIA GeForce RTX 5070 Ti 16 GB GDDR7
16 GB · Amazon EXACT
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Sources
Model: official config deepseek-ai/DeepSeek-R1-Distill-Qwen-7B (main). GPU/product specs: Icecat. Compatibility: RigForAI calculator v1.0.0 estimated VRAM · Q8 at 8K: FITS_IN_VRAM. Amazon: affiliate commerce match, not a spec source.