19 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.
The August 2026 frontier landscape: neck-and-neck on SWE-bench Verified, separation on SWE-bench Pro. Which model for which job, benchmark literacy, and the Turkish-performance criterion.
In July 2026 three major providers released new frontier models. An enterprise-use comparison, multi-model strategy, and a right-choice guide.
There's no single best model. A field guide to the August 2026 landscape, the benchmark trap, and a framework for choosing the right model for your work.
July 2026 packed five major models into two weeks. Model selection by use case, a comparison table, and an enterprise framework centered on KVKK and the EU AI Act.
There is no single best model in 2026: how to match GPT-5.6, Claude Opus 4.8, Fable 5, Gemini 3.1 and open models to the job, plus routing and KVKK guidance.
The July 2026 LLM API price table, a TCO framework, and cost-cutting levers. Why cheapest isn't always right, plus the KVKK/data-residency dimension.
GPT-5.6 vs Claude Opus 4.8 vs Gemini 3.1 Pro: code, agentic tasks, price, context, and Turkish performance. A guide to choosing the model that fits your job, not the smartest one.
In July 2026 three frontier labs shipped models at once. I compare GPT-5.6, Claude Fable 5, Gemini Deep Think and Grok 4.5 from the field.
Claude Opus 4.8, GPT-5, Gemini 3, Grok 4... In July 2026 there is no 'best model,' only the right one. An enterprise selection framework by task, budget, and KVKK.
Frontier models as of July 2026: benchmarks, price/performance and an enterprise selection guide. Which model for which job? Practical field notes.
Claude Sonnet 5, Gemini 3.5 Flash, GPT-5.6 and open-weight models. A use-case model-selection framework with a cost/latency table.
What is Gemini? Gemini is Google's family of multimodal AI models that can process text, images, audio, and code in a single model. This guide: a clear definition, how Gemini works, model variants, Gemini features, Workspace integration, comparison with ChatGPT, data privacy, 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.
ChatGPT Search now serves 800M weekly users, and roughly 18% of all searches happen inside LLM interfaces. Generative Engine Optimization (GEO) is the discipline of becoming a cited source across ChatGPT, Perplexity, Gemini, and Google AI Overviews. This playbook covers: GEO vs SEO vs AEO, the 7 technical foundations (Schema, E-E-A-T, first 200 words, comparison tables, citation frequency, entity consistency, multi-format), a 50+ item audit checklist, measurement tools (LLMrefs, Profound, Otterly), and a Turkish B2B SaaS case study.
We benchmarked GPT-5.5, Claude Opus 4.7 and Gemini 3.1 Pro on Turkish workloads end to end: TR-MMLU and TUMLU benchmark numbers, a 50-prompt real-world test across legal, finance, code, creative writing and Q&A, an A/B in a Turkish enterprise, TL-based cost analysis and a decision matrix for picking the right model for each Turkish task. 35+ references.
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.
An end-to-end comparison of the 2026 versions of OpenAI ChatGPT, Anthropic Claude, and Google Gemini. Twelve comparison tables across model families, pricing, Turkish fluency, code generation, long context, multimodal capabilities, voice, video, computer use, custom assistants, agent/MCP support, data privacy, and KVKK compliance. Use-case-based decision matrix for Turkish individual users and enterprise buyers.
A comprehensive Turkish guide that takes prompt engineering from zero to advanced. Covers the 6 components of a prompt, 14 core techniques (zero-shot, few-shot, CoT, ToT, ReAct, self-consistency, meta-prompting), Turkish-specific notes, 20+ ready templates, model-specific differences (GPT-5, Claude Opus 4.7, Gemini 3), prompt injection defenses, DSPy-based automatic optimization, and A/B testing.