9 posts
I compare the leading LLMs as of August 2026 through an enterprise buyer's eyes: capability, cost, latency and KVKK data residency, with practical picks.
Open source LLM comparison: the strengths, licenses, sizes, Turkish performance of Llama, Qwen, Mistral and DeepSeek, plus an enterprise model selection framework.
What is DeepSeek? DeepSeek is a family of open-source LLMs and reasoning models developed by a Chinese research company, notable for its low-cost training and MoE architecture. This guide: a clear definition, how DeepSeek works, MoE architecture, reasoning-model logic, what being an open-source LLM means, enterprise use, GDPR, comparison with other models, and FAQs.
What is an LLM? How do Large Language Models (LLMs) work, what does Transformer architecture solve, what are tokens, embeddings, and context windows, and how do GPT-5, Claude Opus 4.7, Gemini 3, and Llama 4 compare? A comprehensive 2026 reference covering Turkish LLM performance, training stages, hallucination control, and cost modeling.
The GPT-5.6, Claude Sonnet 5, Gemini 3.2 and Qwen/DeepSeek wave. 'Best model' is the wrong question; which model for which job is the right one. A decision framework with Turkish, cost and KVKK reality.
Detailed review of 8+ Chinese LLMs including Moonshot Kimi K2 (1T MoE), Zhipu GLM-4.5, 01.AI Yi-Large/Yi-Lightning, MiniMax abab, and Baichuan: architectures, benchmarks, pricing, open-weight vs API, Turkish fluency, KVKK + data residency legal-risk map, censorship behavior, and a 6-scenario usage guide.
Detailed comparison of 15 real ChatGPT rivals: Claude, Gemini, Perplexity, Copilot, Mistral Le Chat, DeepSeek, Qwen, Pi, Grok, You.com, Poe, HuggingChat, Meta AI, Character.AI, Jasper. Model, price, strengths, weaknesses, KVKK status, Turkish fluency, and an 8-scenario selection guide.
Detailed comparison of the three most powerful 2026 open-weight LLM families — DeepSeek (V3 + R1), Qwen (2.5 + 3), and Meta Llama (4). Architecture (MoE vs dense), benchmarks (MMLU, HumanEval, GSM8K), Turkish performance, license (MIT vs Apache vs Llama Community), cost (self-hosted vs API), hardware (VRAM, GPU), fine-tune friendliness, ecosystem (Hugging Face, vLLM, Ollama), KVKK / data sovereignty advantages. Use cases for Turkish enterprises.
The most comprehensive 2026 Turkish LLM benchmark: MMLU-TR, Belebele-TR, TruthfulQA-TR, Turkish HumanEval, MGSM-TR, and hallucination tests. Score tables for GPT-5, Claude Opus 4.7, Gemini 3, Mistral Large 3, Llama 4, DeepSeek V3, Qwen 2.5, and local Turkish models (Cezeri, BERTurk, Trendyol-LLM), with use-case mapping and transparent methodology.