AI Model2026-05-17

DeepSeek

Also known as: DeepSeek / DeepSeek V4 / DeepSeek R1

Open-weights LLMs from China's DeepSeek. DeepSeek V4 features a 1.6 T-parameter MoE with 1 M context and drew global attention for its ultra-low training cost.

Overview

DeepSeek V4 Preview is released as open weights with a 1 M context window. Its reported training cost — a fraction of GPT-4's — sparked global debate about AI development economics. See DeepSeek V4 release.

R1 reasoning model

DeepSeek R1 specialises in maths and coding via chain-of-thought reinforcement learning, with growing adoption as a cost-efficient local alternative to Claude.

Overview of DeepSeek V4 Preview, released on April 24, 2026: two open-weight Mixture-of-Experts variants (V4-Pro at 1.6T total / 49B active and V4-Flash at 284B / 13B), 1-million-token context, weights on Hugging Face, and rollout via API and chat — based on official information.

Local LLM Landscape April 2026 — Top 10 Open-Source Models Comprehensive Comparison [Ollama Guide]

Comprehensive comparison of the top 10 local LLMs as of April 2026. Covers SWE-bench scores, Japanese language performance, VRAM requirements, Ollama commands, and licensing for Gemma 4, Llama 4, Qwen 3.5, GLM-5.1, Kimi K2.5, MiniMax M2.5, and more.

Claude Alternative Local LLM Comparison 2026 — Qwen 3.5, Mistral Small 4, DeepSeek R1 & Gemma 4 Reviewed

Following Anthropic Claude restrictions, comprehensive comparison of local LLMs including Qwen 3.5-9B, Mistral Small 4, DeepSeek R1, Gemma 4, and Llama 4. Detailed analysis of Japanese performance, hardware requirements, and use-case recommendations.

DeepSeek V4 Pro 0813 Hits GA: Pricing, Benchmarks, Harness v0.1

DeepSeek V4 Pro hit GA (V4-Pro-0813) Aug 12, 2026 with big benchmark gains. API prices rise Aug 16, output ~2.3x. Covers pricing, self-hosting, Harness v0.1.

Reasonix: The DeepSeek-Native Terminal Coding Agent

Reasonix is a DeepSeek-native AI coding agent for the terminal: a single MIT-licensed Go binary engineered around prefix-cache stability. As of August 2026 it has 33,538 GitHub stars. Here's how to install it, how it's configured, and how it compares to Claude Code, Codex, Aider, and Cline.

DeepSeek V4 Requirements Reference — VRAM, RAM & GPU by Quantization, Plus API Pricing and the July 24 Legacy Retirement [Updated for the 0731 Build]

DeepSeek V4-Flash needs roughly 160GB at 4-bit and V4-Pro about 920GB. The July 31 V4-Flash-0731 build keeps the same footprint while beating V4-Pro on agent benchmarks. VRAM, RAM and GPU tables by quantization, API pricing, and the legacy model retirement. Updated August 2026.

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