A fast multimodal model: where GPT-4o was the best fit and what to use instead

For a long time, OpenAI's GPT-4o was the go-to model for fast, inexpensive tasks with text and images. Since then the GPT-5 flagships and the reasoning branch have appeared, but a model like this still has its niche: there it wins on speed and price.

GPT-4o is not in the Yenisei catalog. This niche is covered by open models: Qwen3.8 Flash (qwen-flash), Gemma 4 26B (gemma-4-26b), Mistral Small 3.2 (mistral-small-3.2), and from our own lineup, Yenisei 100 (yenisei-100).

What you need from such a model

• Text and images in one request: a photo of a document, an interface screenshot, a diagram.
• Speed: low latency matters for interactive scenarios.
• Reasonable context: not a million, but enough headroom for everyday tasks.

Where a fast model for text and images is the best fit

Image analysis in a stream

If you need to recognize the contents of hundreds of screenshots or receipt photos, a heavy reasoning model is overkill. A fast model that understands images will extract what is visible, with no delay and cheaply.

curl https://api.yenisei.ru/v1/chat/completions \
  -H "Authorization: Bearer $YENISEI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen-flash",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "What error is shown on this screenshot? Keep it short."},
        {"type": "image_url", "image_url": {"url": "https://example.com/screen.png"}}
      ]
    }]
  }'

Interactive assistants

When a person is sitting there waiting for an answer, the latency of reasoning models is irritating. A fast model answers without a pause, and on everyday questions its quality is just as good.

Moderate budget

If the task doesn't require a flagship's depth, you simply save money.

Where a fast model falls short

• Complex multi-step reasoning: this calls for a reasoning model, such as Kimi K2.6 (kimi-k2.6), which also understands images.
• Huge documents: use a model with a window of about a million tokens, such as Kimi K3 (kimi-k3) or Yenisei Max (yenisei-max).
• Delicate agent chains: larger models hold the tool protocol more reliably.

How to think about the choice

"Fast, with images, inexpensive": as long as the task fits those words, there is no reason to drag in a flagship. As soon as it becomes "this needs more thought," switch to a larger model. Payment is in rubles, 1 credit = 1 ₽.