deepseek-v3.2 API — compare providers

The same model (deepseek-v3.2) is served by 13 providers; GMICloud is the cheapest at $0.518/1M blended — the priciest (SambaNova) costs 1348% more. On quality, deepseek-v3.2 scores 1425 on the LMArena (Chatbot Arena) — so the cheapest endpoint is also the best value per dollar here.

LicenseMITopen weights · permissive · terms
Knowledge cutoffMarch 2026source · ranked
Quality (Elo)1425LMArena (Chatbot Arena) · source
Intelligence25.1Artificial Analysis Intelligence Index · source · ranked

Quality and intelligence scores are attached to the model itself — identical whichever provider serves it. Verified 2026-09-04.

RankProviderInput /1MOutput /1MBlended /1MValue (Elo/$)
1GMICloud$0.2088$0.3096$0.518 ← cheapest2,749 ← best value
2DeepInfra$0.26$0.38$0.642,227
3AtlasCloud$0.26$0.38$0.642,227
4Novita AI$0.269$0.4$0.6692,130
5SiliconFlow$0.259$0.42$0.6792,099
6Baidu$0.28$0.42$0.72,036
7Venice$0.33$0.48$0.811,759
8DigitalOcean$0.25$0.8$1.051,357
9Alibaba$0.3705$1.1115$1.482962
10Friendli$0.5$1.5$2712
11Phala$1$1$2712
12Google$0.56$1.68$2.24636
13SambaNova$3$4.5$7.5190

Value = model Elo ÷ blended price per 1M tokens. Since the model's quality is identical across providers, the cheapest endpoint is also the best value per dollar.

Prices are per 1M tokens (USD). "Blended" = input + output, for coarse ranking. Same underlying model, 13 serving providers, 1348% spread top to bottom. Context window: 163,840 tokens (147,456 max output) — see how it ranks in biggest context windows. See how this compares across the catalogue in same model, different price, or find the best quality per dollar in the value ranking.

Cost per 1,000 requests by workload

What each provider actually bills for a representative job, not just the sticker price.

ProviderChatbot
1000 in / 500 out
RAG / long context
8000 in / 500 out
Batch summarize
4000 in / 1000 out
GMICloud$0.36$1.83$1.14
DeepInfra$0.45$2.27$1.42
AtlasCloud$0.45$2.27$1.42
Novita AI$0.47$2.35$1.48
SiliconFlow$0.47$2.28$1.46
Baidu$0.49$2.45$1.54
Venice$0.57$2.88$1.80
DigitalOcean$0.65$2.40$1.80
Alibaba$0.93$3.52$2.59
Friendli$1.25$4.75$3.50
Phala$1.50$8.50$5.00
Google$1.40$5.32$3.92
SambaNova$5.25$26.25$16.50

Estimate your own workload

Input tokens/request:   Output tokens/request:   Requests:

ProviderEstimated cost (USD)

Self-host / quantized builds

Open weights under MIT — you can run deepseek-v3.2 on your own hardware instead of paying per token. Quantized builds lower the memory footprint; whether it fits your GPU or Mac depends on the model's size. Formats: GGUF for llama.cpp / Ollama / LM Studio, AWQ and GPTQ for GPU serving, MLX for Apple silicon.

Links search the live model hubs (Hugging Face, Ollama) so they track new builds as they appear — we don't host weights. Which formats exist depends on what the model owner and community have published.