Moonshot AI · 1043B parameters · 131.1K context · commercial OK
Local (your GPU) $0 · ~703 GB VRAM | Rent a GPU from $20.64/hr | Your API key $8.44/1M est. |
Best next step
Already have 703 GB of VRAM? Run Q4_K_M locally for $0 compute. Check the exact hardware fit →
No matching GPU? For the same representative session, the chosen rented GPU is about $26.54 at $20.64/hr. Open DigitalOcean 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.
Check Novita AI — referral link. You use your own account and pay Novita's normal price; Novita may pay Spanvero a commission.
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Trillion-param (1.04T) MoE — 32B active, 384 experts, MLA attention; among the strongest open-weights agentic/coding models. At FP16 (~2 TB) it needs a multi-GPU cluster; ships native FP8 (~1 TB).
Kimi K2 Instruct needs more memory than any of our consumer hardware presets — running it locally means multi-GPU or workstation territory, so the API price is the honest baseline here.
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 | 1043B |
|---|---|
| Context window | 131.1K tokens |
| Recommended quant | Q4_K_M |
| VRAM requirement | ~703 GB (at Q4_K_M, 16.4K context) |
| Download size | ~1090 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 703 GB of VRAM (at Q4_K_M); a rented GPU from $20.64/hr (6× NVIDIA H200 141GB (HGX) at the direct DigitalOcean price); or about $8.44 per 1M blended tokens via your own API key (a rough estimate for this size). Spanvero adds $0 markup on every path.
Only with serious hardware: at Q4_K_M, Kimi K2 Instruct needs about 703 GB of VRAM/unified memory — more than any consumer GPU or Mac we track — so local means multi-GPU workstation territory. Most people use a rented GPU or their own API key instead.
No single consumer GPU we track holds Kimi K2 Instruct — it needs about 703 GB at Q4_K_M. That is multi-GPU, cluster, or API territory.
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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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