#deepseek-v4

DeepSeek abandons its no-outside-capital stance in a ~$7.4B maiden round led by Tencent and CATL, valuing it near $59B and reshaping open-weight economics.

H1 2026 open-weight retrospective — DeepSeek V4, Qwen 3, Llama 4 release cadence, benchmark gains vs frontier, adoption patterns, and four trend lines.

Migrate DeepSeek V3.2 to V4 across open-weight stacks — three reasoning modes, tokenizer change, HCA/CSA attention deltas, KV-cache reduction.

DeepSeek-V4 ships April 24, 2026 as open-weight MoE: Pro (1.6T/49B active) and Flash (284B/13B), 1M context, 27% FLOPs and 10% KV cache vs V3.2.

MoE choices powering 2026 frontier models compared — total vs active params, routing strategies, sparsity ratios, and the downstream cost implications.

Updated NIAH-2 results across 1M-context models — single-needle, multi-needle, and reasoning-over-context. Where models silently fail above 200K tokens.

We measured low/medium/high reasoning effort across 5 frontier models on math, code, and analysis. Quality lift, latency tax, and cost-per-correct-answer data.

Preview of Q2 2026 AI model releases. DeepSeek V4 at ~1T parameters, GPT-5.5 Spud with pretraining done, and Grok 5 expected by mid-2026. Timeline and specs.

DeepSeek V4 launches with approximately 1 trillion parameters, 1M context window, and Huawei Ascend optimization. China's frontier multimodal model analysis.

DeepSeek V4 brings 1 trillion parameters, 1M token context, and Engram O(1) memory. Architecture details, leaked benchmarks, and what it means for developers.