§01·compatibility · /check
Qwen3 14B on RTX 5080
Yes — Qwen3 14B runs on the RTX 5080 (16 GB). Fastest community-measured result: 3820.5 prefill tokens/s, with 16 GB peak VRAM.
✓ runsllmactive50 series16GB VRAM
§02·benchmarks
| Task | Quant | Speed | VRAM | Works | Confidence | Source | Verified |
|---|---|---|---|---|---|---|---|
| llm | Q4_K | 3820.5prefill tokens/s | 16GB | ✓ | hardware-corner.net· web | 2026-05-15 | |
| llm | Q4_K | 80.6tokens/s | 16GB | ✓ | hardware-corner.net· web | 2026-05-15 |
§03·common questions
Can you run Qwen3 14B on RTX 5080?
Yes — Qwen3 14B runs on the RTX 5080 (16 GB). Fastest community-measured result: 3820.5 prefill tokens/s, with 16 GB peak VRAM.
How much VRAM does Qwen3 14B need on RTX 5080?
Measured peak VRAM is 16 GB.
Which quantizations have been tested for Qwen3 14B on RTX 5080?
Q4_K — measured in community benchmarks.
How fast is Qwen3 14B on RTX 5080?
Up to 3820.5 prefill tokens/s (llm), the fastest community-measured result.
Are there step-by-step instructions for Qwen3 14B on RTX 5080?
Yes — a step-by-step recipe documents Qwen3 14B on the RTX 5080; see the recipes listed below.
§04·related recipes
- llmbeginner16GB+
Qwen3-14B on RTX 5080: Q4_K_M GGUF via Ollama or llama.cpp
- llmbeginner12GB+
Qwen3-14B on RTX 4060 Ti 16GB: Q4_K_M GGUF via Ollama or llama.cpp
- llmintermediate9GB+
Qwen3-14B on Apple M2 Pro: the strongest LLM that fits a 16 GB unified-memory Mac, via MLX 4-bit
- llmbeginner9GB+
Qwen3-14B on RX 7800 XT: ROCm via Ollama or llama.cpp-HIP
- llmbeginner12GB+
Qwen3-14B on RTX 5060 Ti: Q4_K_M GGUF via Ollama or llama.cpp