Models / DeepSeek V3.2 Exp / Calculator

DeepSeek V3.2 Exp cost & VRAM calculator

What does DeepSeek V3.2 Exp cost to run for your workload, and can you run it on your own hardware? Set your workload below - we compute per-provider API cost live and tell you honestly whether local hardware can run it.

LOCAL ISN'T PRACTICAL

This is where owning stops making sense

DeepSeek V3.2 Exp is a 685-billion-parameter model. No rig an individual can buy runs it - so unlike a workstation GPU model, there's no break-even to compute. The honest answer for nearly everyone is the per-provider API cost below.

685B total, ~37B active per token (MoE, 256 routed experts) - shares the V3 backbone. Adds DeepSeek Sparse Attention (DSA): a lightning indexer (FP8, Hadamard dot-product) selects top-2048 tokens per query, then MLA runs only over those. The first fine-grained sparse attention from DeepSeek and the precursor to V4’s CSA. Built on V3.1-Terminus. Experimental; superseded by V4 within ~7 months. Open weights under MIT.

Your workload

Casual Power user Team of 5 Codebase task

DeepSeek V3.2 Exp runs an always-on thinking mode. Reasoning (thinking) tokens are billed at the output rate ($15.00/M), so count them here to see the thinking portion of your bill.

API cost for your workload

Provider Rate ($/1M) Monthly cost
SiliconFlow $0.27 in · $0.41 out $0.01 cheapest

Monthly cost is an estimate from list prices and your workload - verify against the provider before committing. Cached fraction applies the cache rate to that share of input.

Can you run it locally?

NO - NO INDIVIDUAL RIG RUNS IT

DeepSeek V3.2 Exp has no published quantization that fits a rig one person can buy, so there's no local-hardware recommendation and no break-even to compute. The honest answer is the per-provider API cost above.

685B total, ~37B active per token (MoE, 256 routed experts) - shares the V3 backbone. Adds DeepSeek Sparse Attention (DSA): a lightning indexer (FP8, Hadamard dot-product) selects top-2048 tokens per query, then MLA runs only over those. The first fine-grained sparse attention from DeepSeek and the precursor to V4’s CSA. Built on V3.1-Terminus. Experimental; superseded by V4 within ~7 months. Open weights under MIT.

See the model card for the full architecture notes and any cloud subscription plans.

Full model card API pricing table Generic token calculator