DeepSeek

OpenRouter has introduced DeepSeek: DeepSeek Pro Latest, a routing alias that automatically points to whichever DeepSeek Pro model is newest. The endpoint offers a 1,049K token context window at $0.58 per 1M input tokens and $1.74 per 1M output tokens.

OpenRouter has launched deepseek-flash-latest, a persistent endpoint that always points to the current DeepSeek Flash model. It offers a 1,049K token context window, text-and-image input, and pricing of $0.15 per 1M input tokens and $0.60 per 1M output tokens.

DeepSeek has released V4.1-Flash, a 552B-parameter multimodal Mixture-of-Experts model supporting 1M-token context and activating only 8B parameters during prefill. The model uses a new Causal Encoder-Decoder architecture and Compressed Sparse Attention 2 to cut global KV cache to 890 bytes per token, roughly a quarter of its predecessor.

DeepSeek has released DeepSeek-V4-Flash-Vision-Exp, its first experimental multimodal model in the V4 family, adding visual understanding to the V4-Flash architecture. The 305B-parameter model shows substantial gains on multimodal agent benchmarks while holding steady on text-only tasks.

DeepSeek has released V4 Flash Vision Exp, an experimental vision-enabled variant of DeepSeek V4 Flash 0731 that adds image understanding while matching the base model's text performance. The sparse mixture-of-experts model uses 13B active parameters out of 284B total and supports a 1M token context window.

DeepSeek will raise API output token pricing roughly fourfold starting August 16, introducing peak and off-peak rates for its V4 Pro and V4 Flash models. Despite the increase, DeepSeek remains cheaper than competitors like OpenAI's GPT-5.6 Sol and Moonshot's Kimi K3.

DeepSeek has shipped the general availability release of DeepSeek V4 Pro, codenamed 0813, featuring a 1,049,000-token context window. The mixture-of-experts model is priced at $0.43 per million input tokens and $0.87 per million output tokens, and is live now on OpenRouter.

DeepSeek has published a new routing endpoint, deepseek-v4-flash-latest, that always points to the newest model in its V4 Flash family. The endpoint offers a 1,049K token context window and pricing of $0.09/M input and $0.18/M output tokens via OpenRouter.

DeepSeek has updated its budget model V4 Flash to version '0731,' pushing its Artificial Analysis Intelligence Index score to 50 — just one point behind OpenAI's GPT-5.6 Luna — while costing an estimated 60 percent less per task. The MIT-licensed model keeps its 284B-parameter architecture but shows major gains in agentic benchmarks and token efficiency.

DeepSeek has released V4 Flash 0731, a sparse mixture-of-experts model with 13B active parameters out of 284B total and a 1049K token context window. The model targets coding, reasoning, and agent workflows, priced at $0.14 per million input tokens and $0.28 per million output tokens via OpenRouter.

Unsloth has released optimized GGUF quantizations of DeepSeek-V4-Flash, a 284B parameter Mixture-of-Experts model that activates 13B parameters and supports 1 million token context windows. The Q8 quantization (UD-Q8_K_XL) runs at 162GB with claimed lossless precision, only 7GB larger than the Q4 variant.

Cline, the autonomous AI coding assistant, released v4.0.2 with support for reasoning effort controls on DeepSeek thinking models, including the new 'xhigh' setting. The update also improves the ClinePass provider experience with clearer reasoning controls and model selection.

DeepSeek has released two new MoE models: DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSeek-V4-Flash with 284B parameters (13B activated). Both models support a one million token context window and use a hybrid attention architecture that requires only 27% of single-token inference FLOPs and 10% of KV cache compared to DeepSeek-V3.2.

DeepSeek has released two Mixture-of-Experts models: V4-Pro with 1.6 trillion parameters (49B activated) and V4-Flash with 284B parameters (13B activated), both supporting 1 million token context windows. V4-Pro requires only 27% of inference FLOPs and 10% of KV cache compared to V3.2 at 1M token context, trained on over 32 trillion tokens.

Chunjiang Intelligence has released DeepSeek-V4-Fable, an autonomous agent model designed for offensive security research and CTF challenges. The model, distilled from Claude-5-Fable and built on DeepSeek-V4-Flash, was trained on 80,000 verified CTF trajectories and achieves a 58.7% solve rate across held-out security challenges.

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 a preview of its V4 model on April 24, 2026, claiming the open-source system matches leading closed-source models from Anthropic, Google, and OpenAI. The company emphasized improved coding capabilities and compatibility with domestic Huawei chips, but did not disclose training costs or hardware specifications.

DeepSeek has released V4-Flash-Base, a 292 billion parameter base model now available on Hugging Face. The model uses BF16, I64, F32, and F8_E4M3 tensor types and is distributed in Safetensors format.