§01·compatibility · /check
Qwen3 14B on RTX 4080 Super
Yes — Qwen3 14B runs on the RTX 4080 Super (16 GB). Fastest community-measured result: 3745 prefill tokens/s, with 16 GB peak VRAM.
✓ runsllmactive40 series16GB VRAM
§02·benchmarks
| Task | Quant | Speed | VRAM | Works | Confidence | Source | Verified |
|---|---|---|---|---|---|---|---|
| llm | Q4_K | 3745prefill tokens/s | 16GB | ✓ | hardware-corner.net· web | 2026-05-15 | |
| llm | Q4_K | 64.2tokens/s | 16GB | ✓ | hardware-corner.net· web | 2026-05-15 |
§03·common questions
Can you run Qwen3 14B on RTX 4080 Super?
Yes — Qwen3 14B runs on the RTX 4080 Super (16 GB). Fastest community-measured result: 3745 prefill tokens/s, with 16 GB peak VRAM.
How much VRAM does Qwen3 14B need on RTX 4080 Super?
Measured peak VRAM is 16 GB.
Which quantizations have been tested for Qwen3 14B on RTX 4080 Super?
Q4_K — measured in community benchmarks.
How fast is Qwen3 14B on RTX 4080 Super?
Up to 3745 prefill tokens/s (llm), the fastest community-measured result.
Are there step-by-step instructions for Qwen3 14B on RTX 4080 Super?
Yes — a step-by-step recipe documents Qwen3 14B on the RTX 4080 Super; see the recipes listed below.
§04·related recipes
- llmbeginner16GB+
Qwen3-14B on RTX 4080 SUPER: 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