DeepSeek permanently reduced V4 Pro pricing by 75%, dropping input tokens to $0.003625 per million and output tokens to $0.87 per million. Previously promotional pricing is now permanent.
Major release with 1.6T total parameters, 1M token context window, and substantial efficiency improvements over V3.2. DeepSeek claims near-frontier performance at a fraction of the cost.
DeepSeek V4 introduces two model sizes with major architectural improvements: hybrid attention mechanisms reduce memory usage by 9.5x-13.7x while supporting 1M token contexts, and mixed FP4/FP8 precision further reduces memory footprint. Added Huawei Ascend NPU support.
DeepSeek has permanently reduced pricing for its V4 Pro model by 75%, bringing input token costs down to $0.003625 per million tokens from $0.0145. The move makes permanent a promotional discount that was set to expire May 31, 2026.
DeepSeek released V4 in two versions: a 284 billion parameter Flash model and a 1.6 trillion parameter Pro model with 49 billion active parameters. According to DeepSeek, the models use 9.5x-13.7x less memory than V3 through compressed attention mechanisms and FP4/FP8 mixed precision, while supporting a 1 million token context window.
Chinese AI lab DeepSeek has released preview versions of DeepSeek V4 Flash and V4 Pro, mixture-of-experts models with 1 million token context windows. The V4 Pro has 1.6 trillion total parameters (49 billion active), making it the largest open-weight model available, while both models significantly undercut frontier model pricing.
DeepSeek released two preview models: V4 Pro (1.6T total parameters, 49B active) and V4 Flash (284B total, 13B active), both with 1 million token context windows. V4 Pro is priced at $1.74/M input tokens and $3.48/M output—42% cheaper than Claude Sonnet 4.6—while V4 Flash at $0.14/$0.28 per million tokens undercuts all small frontier models.
DeepSeek has released V4 Pro, a Mixture-of-Experts model with 1.6 trillion total parameters and 49 billion activated parameters. The model supports a 1-million-token context window and costs $1.74 per million input tokens and $3.48 per million output tokens.
DeepSeek released two new Mixture-of-Experts models: DeepSeek-V4-Pro with 1.6 trillion parameters (49B activated) and DeepSeek-V4-Flash with 284B parameters (13B activated), both supporting one million token context length. The models achieve 27% of inference FLOPs and 10% of KV cache compared to DeepSeek-V3.2 at 1M context through a hybrid attention architecture combining Compressed Sparse Attention and Heavily Compressed Attention.