Home / Companies / Deepinfra / Blog / Post Details
Content Deep Dive

DeepSeek V3.2 API Benchmarks: Latency, Throughput & Cost

Blog post from Deepinfra

Post Details
Company
Date Published
Author
Deep
Word Count
2,011
Company Posts That Month
34
Language
English
Hacker News Points
-
Post removed?
No
Summary

DeepSeek V3.2 is an advanced large language model featuring a 685B parameter Mixture of Experts architecture, designed to combine fast conversational capabilities with deep reasoning skills. Notable for its technical advancements, the model utilizes DeepSeek Sparse Attention for efficient long-context processing, a scalable reinforcement learning framework that rivals GPT-5, and an innovative task synthesis pipeline that integrates reasoning into tool-use scenarios. The model has demonstrated exceptional performance in international competitions such as the International Mathematical Olympiad and is available through various inference providers. Benchmarking results highlight DeepInfra as the recommended provider due to its competitive pricing, low latency, and comprehensive API features, while Google Vertex is noted for its speed and low latency, albeit at a higher cost. Other providers such as Novita and SiliconFlow offer budget-friendly options, though they come with certain limitations in API features or latency.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Real-time 3 8,074 1,860 309 -46%
LLM 2 7,732 1,424 279 -3%
AI Agents 1 7,105 1,572 286 -11%
Multi-agent systems 1 617 238 84 -23%
RAG 1 1,342 304 105 -38%
Reinforcement learning 1 117 55 30 -36%
Vector Search 1 2,305 541 182 -32%
Use This Data

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.