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Can the NVIDIA RTX 4080 run Qwen2.5 Coder 14B?

RTX 4080 × Qwen2.5 Coder 14B8K context
YesRuns fully on the GPU
Memory at Q6_K14.3 GB of 16 GB
Weights 12.1 GBKV cache 1.6 GBRuntime 0.6 GB
QuantQ6_KExcellent
Speed~35tokens per second
Max context15Ktokens that fit at Q6_K
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Yes. The NVIDIA RTX 4080 can run Qwen2.5 Coder 14B fully in VRAM at Q6_K (excellent), using about 14.3 GB of the 16 GB available, at roughly 35 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Qwen2.5 Coder 14B:

ollama run qwen2.5-coder:14b

Ollama's default download is Q4_K_M (about 11.2 GB here). You have room for Q6_K, which is excellent: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the RTX 4080

Run it in the cloud

No NVIDIA RTX 4080? Run Qwen2.5 Coder 14B in the cloud.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

Rent a GPU on RunPodRent a GPU on Vast.ai

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 16 GB the NVIDIA RTX 4080 can use.

QuantQualityMemoryFits?Speed
FP16Full quality31.8 GBToo big—
Q8_0Near-lossless17.9 GBToo big—
Q6_KExcellent14.3 GBFits~35 tok/s
Q5_K_MVery good12.7 GBFits~41 tok/s
Q4_K_MGood, most popular11.2 GBFits~48 tok/s
Q3_K_MNoticeably degraded9.4 GBFits~59 tok/s
Q2_KHeavily degraded7.8 GBFits~78 tok/s

Measured speed from real RTX 4080 owners

Tokens per second that people measured on their own NVIDIA RTX 4080, next to our estimate.

No one has measured Qwen2.5 Coder 14B on the NVIDIA RTX 4080 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 4080? Add your real speed

One command times Qwen2.5 Coder 14B in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh -s -- qwen2.5-coder:14b

Windows (PowerShell)

$env:GPUFIT_MODEL="qwen2.5-coder:14b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Qwen2.5 Coder 14B comfortably

Models that run well on the NVIDIA RTX 4080

Frequently asked questions

Can NVIDIA RTX 4080 run Qwen2.5 Coder 14B?

Yes. The NVIDIA RTX 4080 can run Qwen2.5 Coder 14B fully in VRAM at Q6_K (excellent), using about 14.3 GB of the 16 GB available, at roughly 35 tokens/second.

How much VRAM does Qwen2.5 Coder 14B need?

About 11.2 GB at Q4_K_M with 8,192 tokens of context, and about 31.8 GB at full FP16 precision.

How fast is Qwen2.5 Coder 14B on the NVIDIA RTX 4080?

Roughly 35 tokens per second at Q6_K, estimated from the NVIDIA RTX 4080's 717 GB/s memory bandwidth.