xAI Grok 4.6: what it can do and what replaces it in Yenisei

Grok 4.6 is the xAI flagship. It is a reasoning model: before answering, it works through the task step by step, and on hard tasks this shows. Add image understanding, tool calling and a large context window of up to 500K tokens.

This model is not in the Yenisei catalog: we work with open-weight models and our own Yenisei lineup. Below is what Grok can do and what to take instead for the same tasks.

What Grok 4.6 can do

• Reasoning. Math, logic, parsing multi-step conditions: where a regular model skips steps, a reasoning model makes fewer mistakes.
• Vision. It understands images: diagrams, charts, interface screenshots.
• Tools. It calls functions confidently and works as the basis of an agent.
• Long context. 500K tokens is enough for most document tasks.

What replaces it in Yenisei

• Kimi K2.6 (kimi-k2.6): reasoning, image input and tool calling in one model. The closest to Grok in its set of capabilities.
• DeepSeek V4 Pro (deepseek-pro): the senior DeepSeek, with reasoning and tools and a context of up to a million tokens. For when you do not need images but do need logic and long context.
• GLM 5.3 (glm-5.3): the Z.AI flagship with reasoning and a very long window; good at analytics and agent scenarios.
• Yenisei Max (yenisei-max): our senior model with reasoning, image and video input, and a million tokens of context.

How to call

curl https://api.yenisei.ru/v1/chat/completions \
  -H "Authorization: Bearer $YENISEI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k2.6",
    "messages": [
      {"role": "user", "content": "A basket holds 3 red and 5 blue balls. We draw two without replacement. What is the probability that both are blue? Show your work."}
    ]
  }'

Where reasoning is needed and where it is not

A reasoning model is justified where logic itself matters: analytics with conclusions, debugging non-trivial errors, planning an agent's actions, untangling contradictory requirements.

On a high-volume cheap stream, such as labeling and short answers, it is excessive: you pay for thinking where none is required. Take a lightweight model for that: Mistral Nemo (mistral-nemo), GPT-OSS 20B (gpt-oss-20b) or Yenisei 100 (yenisei-100).

Prices for all models are on the plans and pricing page, billed in rubles, 1 credit = 1 ₽.