DeepSeek announced a permanent 75% discount for V4 Pro, reducing cache‑hit token costs to $0.003625 per million, prompting developers to share lower bills, swap Claude Code back‑ends via a single environment variable, and spark industry debate over pricing, privacy, and AI stack design.
claude-trace intercepts Claude Code’s Anthropic API calls, logs them to .jsonl, and generates a self‑contained HTML report that displays system prompts, tool definitions, tool outputs, and full request/response details, with options to include all requests or index the logs for searchable summaries.
This guide walks you through a five‑minute setup that lets you run the DeepSeek‑V4 model inside the Claude desktop client without creating a Claude account or paying for a Pro/Max subscription, while taking advantage of 5 million free tokens and low‑cost pricing.
This article explains the mechanics of prompt‑caching for large language models, breaks down static versus dynamic context, details KV‑cache operation and its pricing, and shows how Claude Code’s 30‑minute programming session reached a 92% cache hit rate that reduced inference costs by 81%, concluding with three production‑grade design rules.
This guide shows how to replace Anthropic's API by running a local Qwen 3.5 model with llama.cpp, configuring Claude Code via ANTHROPIC_BASE_URL, and includes hardware checks, build steps, model download, server launch, speed‑fix tips, and usage instructions for secure, cost‑free development.
The vLLM 0.17.0 release brings FlashAttention 4 integration, a mature Model Runner V2, complete Qwen 3.5 series support, a one‑click performance‑mode flag, Anthropic API compatibility, advanced weight‑offloading, broader hardware support beyond NVIDIA, ASR model integration, and detailed upgrade and installation guidance.
This article explores LM Studio’s evolution into a complete local AI development platform, detailing version 0.4’s architectural overhaul, headless daemon, parallel request handling, stateful REST API, UI refresh, and a suite of hidden developer features such as OpenAI‑compatible, Anthropic‑compatible APIs, CLI tools, native SDKs, and the LM Link remote‑model solution.
GLM‑4.7‑Flash, a 30B‑parameter MoE LLM released as fully open‑source and free, delivers 30B‑class performance across six benchmarks, runs locally with a single Ollama command, and offers a faster cloud‑hosted version with modest token‑based pricing, though hardware costs still apply.
Ollama v0.14.0 now supports the Anthropic API, letting you run Claude Code locally with open‑source models like Qwen or Llama without an API key, network, or cost, and the article provides a step‑by‑step setup, SDK examples, and an objective assessment of the approach.
