DeepSeek V3.2 API pricing

10 providers serve DeepSeek V3.2. DeepSeek V3.2 is an open-weight model (MIT) with 685B total parameters, 37B active per token (mixture-of-experts), up to 164K context. Prices below are per 1M tokens, cheapest input first (self-hosting math further down).

Refreshed 2026-08-28 · list prices from provider APIs

Input floor $0.260/1M at DeepInfra Output floor $0.380/1M at DeepInfra Find your workload winner →

Provider	Input $/1M	Output $/1M	Cache read $/1M	Context
DeepInfra	$0.260	$0.380output floor	$0.130	164K	Use
Novita AI	$0.269	$0.400	$0.135	164K	Use
DeepSeek	$0.280	$0.400	-	164K	Use
GMI Cloud	$0.280	$0.400	-	164K	Use
OpenRouter	$0.280	$0.400	-	164K	Use
Fireworks AI	$0.560	$1.68	-	164K	Use
Google Vertex AI	$0.560	$1.68	-	164K	Use
Azure AI Foundry	$0.580	$1.68	-	164K	Use
AWS Bedrock	$0.620	$1.85	-	164K	Use
SambaNova	$3.00	$4.50	-	33K	Use

The cheapest way to run DeepSeek V3.2

On an illustrative 70M-input / 30M-output monthly workload, today's lowest listed cost is roughly $29.60/month, at DeepInfra. Input-heavy, output-heavy and cache-heavy workloads can produce different winners. Use the live mix calculator below rather than combining floors from two different providers. On output-token cost alone, the API floor remains below our self-hosting estimate of ~$1.27/1M. Details below. Run your own numbers in the breakeven calculator, or read the breakeven math.

Your actual monthly cost

Uses today's list prices

Workload preset Input tokens / month (millions) Output tokens / month (millions) Input served from cache %

Cache read uses the listed cache rate where available; otherwise it falls back to normal input price. Batch, write-cache, volume and negotiated discounts are excluded.

Or run it yourself: DeepSeek V3.2 self-hosting economics

DeepSeek V3.2 is open-weight (MIT), so the API price above competes with the GPU-hour market. 685B total parameters (MoE, ~37B active per token) needs roughly 942 GB VRAM at FP8 or 471 GB at INT4, KV-cache headroom included.

No single GPU fits DeepSeek V3.2 at FP8 (942 GB needed), so it needs a multi-GPU node. Cheapest tracked option: 5× MI300X (192 GB each) at roughly $2.50/hr total (RunPod). Rent 5× MI300X at RunPod → INT4 quantization drops the requirement to 471 GB. Tune it in the calculator.

Breakeven estimate: a well-batched vLLM deployment on 5× MI300X ($2.50/hr) at ~1094 aggregate tok/s and 50% utilization works out to roughly $1.27 per 1M output tokens, versus $0.380 via the cheapest output-token API (DeepInfra). The API is cheaper unless your utilization or throughput beats these assumptions. Planning estimate: throughput varies with hardware, quantization, batch size and context. Tune it in the calculator.

Related models

Model	Cheapest in $/1M	Cheapest out $/1M	Providers
DeepSeek R1	$0.200	$0.400	17
DeepSeek V3	$0.200	$0.200	16
DeepSeek V4 Flash	$0.050	$0.100	13
DeepSeek-V3.1	$0.250	$0.950	10
DeepSeek V4 Pro	$0.435	$0.870	10
DeepSeek R1 Distill Llama 70B	$0.200	$0.375	10

FAQ

What is the cheapest API for DeepSeek V3.2?

As of 2026-08-28, the lowest input price for DeepSeek V3.2 is DeepInfra at $0.260 per 1M input tokens. The lowest output price is DeepInfra at $0.380 per 1M output tokens. The cheapest provider for a real workload depends on its input/output mix. The next-lowest input price is Novita AI at $0.269, a 3% difference.

How much VRAM do you need to self-host DeepSeek V3.2?

DeepSeek V3.2 has 685B parameters, so plan for roughly 942 GB of VRAM at FP8 or 471 GB at INT4/AWQ, KV-cache headroom included. That exceeds a single GPU. A typical node is 5× MI300X.

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