Chinese AI lab DeepSeek released V3.2 in 2025, and the model scored 96.0% on AIME 2025 while charging $0.028 per million input tokens—roughly one-tenth the cost of GPT-5. The company open-sourced the entire 671-billion-parameter model under an MIT license, making frontier-class AI performance available to anyone with sufficient compute resources. OpenAI, Google, and Anthropic now face direct competition from a model that matches their flagship products in mathematical reasoning and coding while undercutting their pricing by an order of magnitude.
DeepSeek achieved these economics through architectural innovations that reduce computational overhead without sacrificing quality. The lab introduced DeepSeek Sparse Attention (DSA), a fine-grained indexing system that identifies significant portions of long contexts and skips unnecessary computation. DeepSeek also refined its Mixture-of-Experts architecture to use 256 specialized expert networks per layer, activating only 8 per token, and eliminated auxiliary losses through a novel bias-term routing approach. These technical choices enabled DeepSeek to train V3 for $5.5 million—less than one-tenth what competitors reportedly spend—, and V3.2 builds directly on that efficient foundation.
The release raises fundamental questions about the competitive moat around closed frontier models and whether premium pricing can survive when open alternatives deliver comparable performance at dramatically lower cost.
The DeepSeek-V3.2 Breakthrough
DeepSeek-V3.2 has 671 billion parameters in total, but the Mixture-of-Experts architecture activates only 37 billion per token. The company released two variants in 2025: V3.2 for mainstream deployment and V3.2-Special for high-compute reasoning tasks. V3.2-Speciale remained available temporarily until December 15, 2025, while V3.2 serves as the primary production model.
The model earned gold medal-level performance across multiple international competitions in 2025, including the International Mathematical Olympiad (IMO), Chinese Mathematical Olympiad (CMO), International Collegiate Programming Contest (ICPC), and International Olympiad in Informatics (IOI). DeepSeek-V3.2 scored 96.0% on the 2025 American Invitational Mathematics Examination (AIME), surpassing GPT-5 High’s 94.6% and matching Gemini 3 Pro’s 95.0%. The model also achieved 99.2% on the Harvard-MIT Mathematics Tournament (HMMT) 2025, compared to Gemini 3 Pro’s 97.5%.
Pricing Comparison
ModelCached InputStandard InputOutput
DeepSeek V3.2 $0.028/M tokens $0.28/M tokens $0.42/M tokens
GPT-5 — $1.25/M tokens $10/M tokens
A typical workload processing 100,000 input tokens and generating 100,000 output tokens costs roughly $0.07 with DeepSeek compared to $1.13 with GPT-5.