DeepSeek · 32.5B parameters · 131.1K context · commercial OK
Local (your GPU) $0 · ~27 GB VRAM | Rent a GPU from $0.18/hr | Your API key $0.36/1M est. |
Best next step
Already have 27 GB of VRAM? Run Q4_K_M locally for $0 compute. Open the local setup guide →
No matching GPU? For the same representative session, the chosen rented GPU is about $0.41 at $0.18/hr. Open Vast.ai at its current rate →
Decision basis: 4,000 input + 2,000 output tokens, prices checked 2026-07-27. API estimates never beat a real price here; referral status never changes the winner.
Novita AI offers model APIs and GPU instances. We do not include its prices in Spanvero's ranking yet, so compare Novita's current price and fit yourself.
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Qwen2.5-32B distilled from DeepSeek-R1’s reasoning traces — a strong local reasoning model. (MIT distill over a Qwen2.5 base.)
At $0.36/1M tokens, the cheapest API for DeepSeek-R1-Distill-Qwen-32B stays cheaper than an RTX 5090 at any daily volume — electricity alone costs more per token than the API does.
Local is never $0 — every figure here includes electricity and hardware amortization. Speeds come from published 7-8B Q4 benchmarks (your model, quant, and context will differ); break-even volumes are rounded to 2 significant figures.
| Parameters | 32.5B |
|---|---|
| Context window | 131.1K tokens |
| Recommended quant | Q4_K_M |
| VRAM requirement | ~27 GB (at Q4_K_M, 16.4K context) |
| Download size | ~20 GB |
| License | Commercial use OK |
Open the free Spanvero advisor → for the live, interactive math for your exact workload and hardware.
Three ways: $0 on your own machine if you have about 27 GB of VRAM (at Q4_K_M); a rented GPU from $0.18/hr (3× NVIDIA RTX 3060 12GB at the direct Vast.ai price); or about $0.36 per 1M blended tokens via your own API key (a rough estimate for this size). Spanvero adds $0 markup on every path.
Yes — DeepSeek-R1-Distill-Qwen-32B runs locally for $0 in compute if your GPU or Apple Silicon Mac has about 27 GB of VRAM/unified memory (at Q4_K_M with 16.4K context). Point LM Studio, Ollama, or llama.cpp at it; after the download it runs offline and free.
Any GPU or Apple Silicon Mac with about 27 GB of VRAM/unified memory handles DeepSeek-R1-Distill-Qwen-32B at Q4_K_M. Of the consumer hardware Spanvero tracks, the smallest that fits is an RTX 5090.
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Spanvero · What's new · Prices as of 2026-07-27. We're an honest advisor — $0 markup, your own accounts, we never resell compute. © 2026 Cynosure LLC.
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