Cheapest way to run Qwen2.5-Coder 32B
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Qwen2.5-Coder 32B needs 22.0 GB at 4-bit — cheapest rental $0.33/hr.
Quick answer
At 4-bit with an 8K-token conversation, Qwen2.5-Coder 32B needs about 22.0 GB. It fits a RTX 5090 (32 GB), so if you already own one it costs nothing per token; the cheapest rental big enough is RTX A6000 on Runpod at $0.33 an hour.
| Option | What you need | Cost | Notes |
|---|---|---|---|
| Your own GPU | RTX 5090 (32 GB) at 4-bit (Q4_K_M), needs 22.0 GB | No GPU purchase prices in our data. Check price on Amazon Amazon affiliate link | $0 per token or hour once you own the card (power not counted) |
| Mac (unified memory) | Mac, 32 GB at 4-bit (Q4_K_M), needs 22.0 GB | No Mac prices in our data | $0 per token once you own it |
| Rent a GPU | RTX A6000 (48 GB total) on Runpod Referral link, Community Cloud | $0.33 per hour | Pay only while it runs. Price checked 2026-11-09 |
Fit rule: the Q4_K_M file (or the highest precision that fits) plus an 8K-token FP16 KV cache under 90% of memory, same as the calculator. Sizes and sources: Qwen2.5-Coder 32B VRAM page. Rental prices: GPU prices (checked 2026-11-09). Hourly and per-token prices measure different things, so which is cheaper depends on how much you use it.
Links marked Referral link, Affiliate partner or Amazon affiliate link may earn us credit or a commission at no cost to you. Disclosure.
Precision ladder: what each quant costs
| Precision | Needs at 8K | Smallest consumer GPU | Smallest Mac | Cheapest single-GPU rental | Cheapest rental overall (any GPU count) |
|---|---|---|---|---|---|
| 16-bit (FP16/BF16) | 67.7 GB | none (max 32 GB) | Mac, 96 GB at 16-bit (FP16/BF16) | A100 PCIe (80 GB) on Vast.ai, $0.40/hr | A100 PCIe (80 GB) on Vast.ai, $0.40/hr |
| 8-bit (Q8_0) | 37.0 GB | none (max 32 GB) | Mac, 48 GB at 8-bit (Q8_0) | RTX A6000 (48 GB) on Runpod, $0.33/hr | RTX A6000 (48 GB) on Runpod, $0.33/hr |
| 4-bit (Q4_K_M) | 22.0 GB | RTX 5090 (32 GB) | Mac, 32 GB at 4-bit (Q4_K_M) | RTX A6000 (48 GB) on Runpod, $0.33/hr | RTX A6000 (48 GB) on Runpod, $0.33/hr |
Every row names its precision, Mac rows included (Macs share unified memory with the system, so the same 90% rule applies). Single-GPU and multi-GPU rentals are listed separately: a multi-GPU rental needs software that splits the model across cards (llama.cpp, vLLM tensor parallel). Prices checked 2026-11-09.
How context length changes the bill (4-bit)
| Context | Needs | Cheapest rental overall |
|---|---|---|
| 8K tokens | 22.0 GB | RTX A6000 (48 GB) on Runpod, $0.33/hr |
| 32K tokens | 28.4 GB | RTX A6000 (48 GB) on Runpod, $0.33/hr |
| 128K tokens | 54.2 GB | A100 PCIe (80 GB) on Vast.ai, $0.40/hr |
What $100 of rental buys you
We list no GPU purchase prices (they change daily and we cannot check them), so this page does not compare renting with buying. At the cheapest rental that fits (RTX A6000 (48 GB) on Runpod, $0.33/hr), $100 of rental buys about 303 hours of running Qwen2.5-Coder 32B at 4-bit with 8K context. Electricity, storage and setup time are not counted.
Fit quirks for this model
- From config.json (64 layers, 8 KV heads, head size 5,120 / 40 = 128), an FP16 cache takes 2 × 64 × 8 × 128 × 2 bytes = 262,144 bytes per token.
- Maximum context is 131,072 tokens; longer settings are capped.
Model data checked 2026-11-03; rental prices checked 2026-11-09. For file sizes, sources and the full fit table see the Qwen2.5-Coder 32B VRAM requirements page; this page is only about cost.
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