Gemma 3n 2B is good. These would like a word anyway.
Google DeepMind's Gemma 3n at an effective 2B parameters inside a 6B architecture. The MatFormer design lets it nest submodels and recombine them through Mix-and-Match, which is how it runs on low-resource hardware. 32K context, multilingual.
No free endpoint for Gemma 3n 2B was found in Rival’s OpenRouter listings. Other providers or chat apps may have separate free offers.
Provider data: OpenRouter usage limits
fromimport openai OpenAI
client = OpenAI(
"https://openrouter.ai/api/v1" base_url=,
"$OPENROUTER_API_KEY" api_key=,
)
response = client.chat.completions.create(
"google/gemma-3n-e2b-it:free" model=,
"role""user""content""Hello!" messages=[{: , : }],
)
print(response.choices[0].message.content)Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.
Taste is judged on an uncapped scale, originality first. The space past 100 is craft today's models rarely reach.
Unique words vs. total words. Higher = richer vocabulary.
Average words per sentence.
"Might", "perhaps", "arguably" per 100 words.
**Bold** markers per 1,000 characters.
Bullet and numbered list items per 1,000 characters.
Markdown headings per 1,000 characters.
Emoji per 1,000 characters.
"However", "moreover", "furthermore" per 100 words.
25 outputs · generated before accounting joined the chat
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