Home / Models / Qwen3 8B / NVIDIA RTX 4080 16 GB
Can Qwen3 8B run on NVIDIA RTX 4080 16 GB?
Yes. Calculated memory fit: Qwen3 8B 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
- Qwen3 8B · 8.2B
- GPU
- NVIDIA RTX 4080 16 GB · 16 GB advertised
What else can NVIDIA RTX 4080 16 GB run? · Find other GPUs for Qwen3 8B
Memory calculation
Breakdown for Q4 at 8K context, batch size 1. Calculator v1.0.0.
| Model weights | 4.8 GB |
|---|---|
| KV cache | 1.1 GB |
| Runtime reserve | 0.7 GB |
| Safety margin | 0.4 GB |
| Required (estimated) | 7.1 GB |
| GPU usable VRAM | 14.4 GB |
Result: FITS IN VRAM
Quantization table
| Quantization | 2K | 4K | 8K | 16K | 32K | 40K |
|---|---|---|---|---|---|---|
| BF16 | Offload | Offload | Offload | Offload | Offload | Offload |
| FP16 | Offload | Offload | Offload | Offload | Offload | Offload |
| Q3 | Fits | Fits | Fits | Fits | Fits | Fits |
| Q4 | Fits | Fits | Fits | Fits | Fits | Fits |
| Q5 | Fits | Fits | Fits | Fits | Fits | Fits |
| Q6 | Fits | Fits | Fits | Fits | Fits | Fits |
| Q8 | Fits | Fits | Fits | Fits | Limited context | Limited context |
What fits entirely in VRAM?
- Q3 at 16K context
- Q3 at 2K context
- Q3 at 32K context
- Q3 at 4K context
- Q3 at 40K context
- Q3 at 8K context
- Q4 at 16K context
- Q4 at 2K context
- Q4 at 32K context
- Q4 at 4K context
- Q4 at 40K context
- Q4 at 8K 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
- Qwen3 8B
- GPU
- NVIDIA RTX 4080 16 GB
- Runtime
- llama.cpp · CUDA · model 1.0.0
- Decode
- ~106 tok/s · Calibrated estimate · HIGH confidence (spread ~94 tok/s–~119 tok/s)
- Prefill
- ~7576 tok/s at a 512-token prompt · Calibrated estimate · MEDIUM confidence
- Time to first token
- ~68 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.
MSI VENTUS RTX 4080 16GB 3X OC NVIDIA GeForce RTX 4080 GDDR6X
16 GB · Amazon EXACT
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GIGABYTE GAMING GeForce RTX 4080 16GB OC NVIDIA GDDR6X
16 GB · Amazon EXACT
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ASUS ROG -STRIX-RTX4080-O16G-GAMING NVIDIA GeForce RTX 4080 16 GB GDDR6X
16 GB · Amazon EXACT
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GIGABYTE EAGLE GeForce RTX 4080 16GB OC NVIDIA GDDR6X
16 GB · Amazon EXACT
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GIGABYTE AERO GeForce RTX 4080 16GB OC NVIDIA GDDR6X
16 GB · Amazon EXACT
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ASUS ROG -STRIX-RTX4080-O16G-WHITE NVIDIA GeForce RTX 4080 16 GB GDDR6X
16 GB · Amazon EXACT
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GIGABYTE EAGLE GV-N4080EAGLE-16GD graphics card NVIDIA GeForce RTX 4080 16 GB GDDR6X
16 GB · Amazon EXACT
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GIGABYTE AORUS GeForce RTX 4080 MASTER NVIDIA 16 GB GDDR6X
16 GB · Amazon EXACT
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GIGABYTE AORUS XTREME AORUS GeForce RTX 4080 16GB XTREME WATERFORCE NVIDIA GDDR6X
16 GB · Amazon EXACT
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ASUS TUF Gaming TUF-RTX4080-O16G-GAMING NVIDIA GeForce RTX 4080 16 GB GDDR6X
16 GB · Amazon unmatched
ASUS TUF Gaming TUF-RTX4080-16G-GAMING NVIDIA GeForce RTX 4080 16 GB GDDR6X
16 GB · Amazon unmatched
Sources
Model: official config Qwen/Qwen3-8B (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.