The 12 best LLMs of 2026: Claude, ChatGPT, Gemini, DeepSeek and Grok compared

In 2026, the world of language models looks like a hypermarket with a huge dairy aisle: forty-seven kinds of yogurt, all of them alike, and you've already spent six minutes staring at the shelf. The difference is that the stakes aren't breakfast. They're code quality, analytics speed, and your team's working hours.

An author on Habr took 12 current models and compared them honestly, using benchmarks and real-world scenarios instead of marketing promises. The review covers three categories. The first is proprietary flagships: OpenAI's ChatGPT 5.

4 and ChatGPT 5.4 Pro, Anthropic's Claude Opus 4.7 and Claude Sonnet 4.

6, Google's Gemini 3.1 Pro, and xAI's Grok 4.20.

The second is specialized tools: the BotHub aggregator and Perplexity's search model, Sonar. The third is open or semi-open options: DeepSeek v3.2, Gemma 4 26B A4B, and GPT-OSS-120B.

As expected, ChatGPT 5.4 Pro and Claude Opus 4.7 came out strongest on deep analysis and complex code, but they win in different ways.

GPT-5.4 Pro leads in structured scenarios: function calling, agentic chains, and tool use. Claude Opus 4.

7 excels elsewhere. It produces more coherent narrative in long texts and handles 100k+ token contexts without quality degrading toward the end. Gemini 3.

1 Pro stands out for native multimodality: it processes documents, images, and code in a single window, with no extra API hops between services. In the mid-price tier, Claude Sonnet 4.6 remains the workhorse for most tasks.

It's faster and cheaper than the flagship, and its code quality is good enough for 80% of production scenarios. Grok 4.20 is interesting for the freshness of its data (xAI has minimal lag behind real time) and for having no restrictions where other models get nervous about content filters.

The real surprise among budget options was DeepSeek v3.2. At a price several times lower than the American flagships, it delivers results comparable to Sonnet 4.

6 on coding and analysis tasks, especially in the Chinese-language domain. Google's Gemma 4 26B A4B suits local deployment: its mixture-of-experts architecture lets it fit on reasonable hardware without cloud costs. GPT-OSS-120B, the largest open model in the review, is for now most interesting as a reference point for teams building vertical products who want to know exactly where the open-source ceiling is.

Perplexity Sonar occupies its own niche. It isn't a pure chatbot but a search model with live internet access built in. Where the others answer from their training weights, Sonar actually searches and cites sources.

BotHub, by contrast, acts as an aggregator: a single interface for accessing a dozen models with Russian payment options, which under current conditions is a key feature in its own right. The article's main takeaway isn't which model is best, because the right answer always depends on the task. For everyday coding, Sonnet 4.

6 or Gemini 3 Flash offer the best balance of speed and cost. For deep research and agentic systems, pick Opus 4.7 or ChatGPT 5.

4 Pro. To save budget without a catastrophic drop in quality, go with DeepSeek v3.2.

In 2026, the LLM market has finally matured to the point where choosing a model isn't a lottery but an engineering decision with clear trade-offs.