DeepSeek-V3.2 vs DeepSeek-V3.2-AWQ

Specs, VRAM requirements and download trends — updated 14 August 2026.

deepseek-ai · A · Open weights
Params
685.4 B
Context
163,840
30d
7.6 M
mit · commercial OK
QuantTrio · B · Open weights
Params
685.4 B
Context
163,840
30d
168 K
mit · commercial OK

Specification comparison

Differences are highlighted; identical values are muted.

Specification DeepSeek-V3.2 DeepSeek-V3.2-AWQ
Deployment Open weights · also via API Open weights
Parameters 685.4 B 685.4 B
Architecture DeepseekV32ForCausalLM DeepseekV32ForCausalLM
Context length 163,840 163,840
Licence mit mit
Commercial use Allowed Allowed
Languages — —
Downloads 30d 7,616,440 167,983
Downloads all time 35.7 M 1.5 M
Quantizations on the Hub SAFETENSORS SAFETENSORS
Gated No No
First seen on the Hub 2025-12-01 2025-12-03
API input price / 1M tokens $0.26 not on OpenRouter
API output price / 1M tokens $0.38 not on OpenRouter
Est. cost per 1M input + 1M output tokens $0.64 not on OpenRouter
Cached input / 1M tokens $0.13 not on OpenRouter
AA Intelligence Index — not on OpenRouter
AA Coding Index 44.2 not on OpenRouter
AA Agentic Index — not on OpenRouter
Max output tokens 147,456 not on OpenRouter
API providers 7 not on OpenRouter
Tool calling Yes not on OpenRouter
Reasoning mode Yes not on OpenRouter

API cost

Estimated cost of 1M input + 1M output tokens via OpenRouter

DeepSeek-V3.2 $0.64

Download trend

Daily snapshots, last 90 days (13 Aug – 10 Nov)

7.6 M168 K
DeepSeek-V3.2 DeepSeek-V3.2-AWQ

VRAM side by side

On RTX 4090 · 24 GB · 8K context unless noted

DeepSeek-V3.2-AWQ · fp16 @ 160K ctx 2,454.7 GB / 24 GB
❌ Won’t fit
DeepSeek-V3.2 · fp16 @ 160K ctx 2,815.1 GB / 24 GB
❌ Won’t fit

Adjacent comparisons