Llama 3.3 70B: what made the proven open model good and what to move to

Llama 3.3 70B remained one of the most popular open models for a long time: a sizable share of ready-made prompts and integrations were written on it. It is no longer in the Yenisei catalog. Below is what it was valued for and what to take instead.

What Llama 3.3 70B was valued for

• Predictability. The model has been studied inside and out: its behavior, its weak spots, how to write prompts for it, all documented by the community.
• Ecosystem. Thousands of ready-made prompts, templates and integrations were written specifically for it.
• Balance of price and quality. 70B is large enough for complex text tasks and cheap enough for volume.

What to move to

• Llama 4 Maverick (llama-4-maverick) is the direct heir in the Meta lineup: the same ecosystem, plus image input and a context of about a million tokens.
• Llama 4 Scout (llama-4-scout) is lighter and cheaper, with a window over a million tokens, and it also understands images.
• GPT-OSS 120B (gpt-oss-120b) is OpenAI's open model, if you also need reasoning.

from openai import OpenAI
client = OpenAI(base_url="https://api.yenisei.ru/v1", api_key="YENISEI_KEY")
resp = client.chat.completions.create(
    model="llama-4-maverick",
    messages=[{"role": "user", "content": "Summarize these paragraphs in three bullet points."}],
    temperature=0.2,
)
print(resp.choices[0].message.content)

How to migrate without surprises

• Run your prompts. Take 30 to 50 typical requests and compare the answers of the old and the new model. Prompts tuned for 3.3 usually work on Llama 4 too, but the answer formatting may differ.
• Fix the temperature. For reproducibility keep temperature low; it makes comparison easier.
• Check answer length. Newer models sometimes write in more detail; if that matters, limit the length in the instruction.

Russian without illusions

The Meta lineup is middling in Russian. On simple tasks it is tolerable, but if the product is Russian-language and the text goes out to users, it is more honest to take a model with strong Russian, for example DeepSeek V4 Pro (deepseek-pro) or Qwen3.8 27B (qwen3.8-27b). Leave Llama for English and technical tasks, where it is in its element.