Rent a GPU

Can the NVIDIA RTX 4090 run Qwen2.5 Coder 32B?

RTX 4090 × Qwen2.5 Coder 32B8K context
YesRuns fully on the GPU
Memory at Q4_K_M22.6 GB of 24 GB
Weights 19.9 GBKV cache 2.1 GBRuntime 0.6 GB
QuantQ4_K_MGood, most popular
Speed~30tokens per second
Max context12Ktokens that fit at Q4_K_M
  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 4090 can run Qwen2.5 Coder 32B fully in VRAM at Q4_K_M (good, most popular), using about 22.6 GB of the 24 GB available, at roughly 30 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts Qwen2.5 Coder 32B:

ollama run qwen2.5-coder:32b

Ollama's default download is Q4_K_M (about 22.6 GB here). That is also the best quant that fits.

New to this? Step-by-step setup for the RTX 4090

Run it in the cloud

No NVIDIA RTX 4090? Run Qwen2.5 Coder 32B 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 24 GB the NVIDIA RTX 4090 can use.

QuantQualityMemoryFits?Speed
FP16Full quality68.3 GBToo big—
Q8_0Near-lossless37.6 GBToo big—
Q6_KExcellent29.6 GBToo big—
Q5_K_MVery good26.1 GBToo big—
Q4_K_MGood, most popular22.6 GBFits~30 tok/s
Q3_K_MNoticeably degraded18.8 GBFits~38 tok/s
Q2_KHeavily degraded15 GBFits~49 tok/s

Measured speed from real RTX 4090 owners

Tokens per second that people measured on their own NVIDIA RTX 4090, next to our estimate.

No one has measured Qwen2.5 Coder 32B on the NVIDIA RTX 4090 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an RTX 4090? Add your real speed

One command times Qwen2.5 Coder 32B 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:32b

Windows (PowerShell)

$env:GPUFIT_MODEL="qwen2.5-coder:32b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run Qwen2.5 Coder 32B comfortably

Models that run well on the NVIDIA RTX 4090

Frequently asked questions

Can NVIDIA RTX 4090 run Qwen2.5 Coder 32B?

Yes. The NVIDIA RTX 4090 can run Qwen2.5 Coder 32B fully in VRAM at Q4_K_M (good, most popular), using about 22.6 GB of the 24 GB available, at roughly 30 tokens/second.

How much VRAM does Qwen2.5 Coder 32B need?

About 22.6 GB at Q4_K_M with 8,192 tokens of context, and about 68.3 GB at full FP16 precision.

How fast is Qwen2.5 Coder 32B on the NVIDIA RTX 4090?

Roughly 30 tokens per second at Q4_K_M, estimated from the NVIDIA RTX 4090's 1008 GB/s memory bandwidth.