Can the RTX A1000 run Qwen3.5 4B?
Yes. Qwen3.5 4B fits the RTX A1000's 8 GB at Q4_K_M (about 4.8 GB needed), running at an estimated 37 tok/s. There's room for up to Q8_0 if you want higher quality.
Every quantization
Qwen3.5 4B (4.7B) on 8 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 3 GB | 4.8 GB | Fits easily | ~37 tok/s |
| Q5_K_M | 3 GB | 4.8 GB | Fits easily | ~37 tok/s |
| Q8_0 | 5 GB | 6.8 GB | Fits | ~22 tok/s |
| FP16 | 9 GB | 10.8 GB | Too big | - |
Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX A1000's 192 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.
Run it
Copy, paste, go
llama-server -hf unsloth/Qwen3.5-4B-GGUF -ngl 99Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Qwen3.5 4B details →
Compare
Same model, other hardware - and other models on this card
Qwen3.5 4B on other hardware
- RTX 5090~343 tok/s
- RTX 5090 D~342 tok/s
- RTX 6000D~300 tok/s
- RTX 4090~209 tok/s
- RTX 3090~183 tok/s
- Radeon RX 7900 XTX~183 tok/s
- RTX 5080~183 tok/s
- RTX 3080 Ti~174 tok/s
Also runs on the RTX A1000
- Mistral-7B-Instruct-v0.2~28 tok/s
- Qwen3-4B-Instruct-2507~55 tok/s
- NVIDIA Nemotron 3 Nano 4B~55 tok/s
- Phi-4 Mini~44 tok/s
Frequently asked
Quick answers
Can the RTX A1000 run Qwen3.5 4B?
Yes. Qwen3.5 4B fits the RTX A1000's 8 GB at Q4_K_M (about 4.8 GB needed), running at an estimated 37 tok/s. There's room for up to Q8_0 if you want higher quality.
How much VRAM does Qwen3.5 4B need?
About 3 GB of weights at Q4_K_M, 5 GB at Q8_0 and 9 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is Qwen3.5 4B on the RTX A1000?
Roughly 37 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX A1000's 192 GB/s memory bandwidth.