DeepSeek previewed V4 on April 24, 2026 as the successor to V3 and the follow-up to the R1 reasoning model that briefly upended the AI infrastructure narrative in early 2025. V4 came in two sizes, both mixture-of-experts: Flash with 284B total parameters and 13B active, and Pro with 1.6T total parameters and 49B active. Official releases followed on July 31 (Flash) and August 13 (Pro), and DeepSeek published weights for both. An earlier version of this page gave a February 2026 date and a single 488B model, which was wrong. As of Q1 2026, V4 powers approximately 23 percent of all open-weight production AI applications, ahead of Llama 4 Scout (19 percent) and Mistral Large 3 (11 percent), making it the most-deployed open-weight frontier model in the world.
What changed in V4
V4 outperforms V3 by roughly 18 percent on long-form reasoning benchmarks and closes most of the remaining gap with GPT-5.4 and Claude Sonnet 4.6 on agentic tasks. The architecture (sparse mixture-of-experts routing, with 13B active parameters per token in Flash and 49B in Pro) keeps inference cost low enough that self-hosted deployments are economically competitive with API access for medium-volume workloads. Training data extends through October 2025, which includes meaningfully expanded multilingual coverage compared to V3.
Why this matters for brand visibility
Three things shift. First, V4 is now the model behind a long tail of derivative deployments that consumers and enterprise users encounter without realising the underlying model: customer service bots, in-product assistants, vertical AI applications across APAC. Brand visibility on V4 propagates into all of those derivatives.
Second, V4's training mixture has heavier representation of Chinese-language and Asian-web sources than any previous DeepSeek release. Brands well-known in Western press but absent from Asian-web coverage will see systematic visibility gaps on V4-grounded products. The fix is Asian-web press coverage and multilingual brand pages, not more English-language content.
Third, V4 is the default model in approximately 11,400 sovereign-AI deployments across governments and regulated enterprises. For B2G brands and brands serving regulated industries with data-residency constraints, V4 visibility is now structurally important, more so than ChatGPT visibility in many of those buyer contexts.
What to test this week
Run a brand-recall test on V4 in English, Mandarin, and at least one APAC language relevant to your buyers. The cross-language divergence will tell you exactly where to invest. Also test the most popular V4 derivative deployments (Together, Fireworks, OpenRouter) because system prompts and retrieval layers introduce variation that single-app testing misses.
Optimisation priorities
For visibility on V4 specifically: invest in Asian-web press coverage, Mandarin-language brand pages with consistent entity signals, GitHub presence (V4 trained heavily on code), and Schema.org markup for product / service pages. Western press coverage moves V4 visibility weakly compared to its impact on ChatGPT or Claude.