DeepSeek Launches 1.7T-Parameter V4 Pro and Open-Source Harness, Hikes Prices 50-1,100%

DeepSeek officially launched DeepSeek-V4-Pro-0813, a 1.7-trillion-parameter mixture-of-experts model activating 49 billion parameters per token, with a 1-million-token context window and a score of 87.9 on Terminal Bench 2.1. Alongside the model it released DeepSeek Harness v0.1, an MIT-licensed agentic framework positioned as a rival to Anthropic's Claude Code, significantly enhancing autonomous coding and agent capabilities.

The headline, however, is pricing. DeepSeek is multiplying its API costs in a sharp strategy shift, moving to a peak/off-peak structure that raises prices anywhere from 50% to 1,100%, with peak-hour pricing reaching $3.96 per million output tokens — roughly a fourfold rise — effective August 16. Forbes noted V4 Pro is priced at 14 times DeepSeek's cheapest model, marking a clear departure from the aggressive low-cost, open-source disruptor image that made DeepSeek famous.

Competitively, the move fits the week's pricing-realignment theme: even the industry's price leader is walking away from race-to-the-bottom economics now that it holds meaningful market share. That reframes the open-weight cost race, where Alibaba's Qwen and Google's newly cheap Gemini 3.7 Flash ($0.75/$3.75) now look aggressive by comparison.

The community backlash was immediate and loud. On r/DeepSeek, a thread titled '1500% price hike at peak hours' drew 418 upvotes, with users saying a 2x increase would be reasonable but this is 'too much' and accusing DeepSeek of margin-grabbing; many said they were switching to Muse Spark, GPT Luna, or Gemini 3.7 ('IT ROCKS'). The open-source Harness and strong Terminal Bench score may retain power users, but the pricing gamble tests how much loyalty DeepSeek's benchmarks can buy.