Grok 4.20 Multi-Agent Beta by xAI — Pricing, Benchmarks & Real Outputs
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Compare Grok 4.20 Multi-Agent Beta
Alternatives to Grok 4.20 Multi-Agent Beta
Grok 4.20 Multi-Agent Beta is good. These would like a word anyway.
Grok 4.20 Multi-Agent Beta is good. These would like a word anyway.
Grok 4.20 Multi-Agent Beta is good. These would like a word anyway.
Grok 4.20 Multi-Agent Beta is a variant of xAI's Grok 4.20 designed for collaborative, agent-based workflows. Multiple agents operate in parallel to conduct deep research, coordinate tool use, and synthesize information across complex tasks. Reasoning effort controls agent count: low/medium uses 4 agents, high/xhigh uses 16 agents.
fromimport openai OpenAI
client = OpenAI(
"https://openrouter.ai/api/v1" base_url=,
"$OPENROUTER_API_KEY" api_key=,
)
response = client.chat.completions.create(
"x-ai/grok-4.20-multi-agent" model=,
"role""user""content""Hello!" messages=[{: , : }],
)
print(response.choices[0].message.content)Set OPENROUTER_API_KEY with your OpenRouter API key from openrouter.ai/keys.
Also on Oracle Cloud (OCI)
The hive mind with personality. Sixteen agents walk into a prompt — the synthesis is somehow both thorough and irreverent. Like a think tank staffed entirely by Grok clones arguing in parallel.
Deploys multiple agents that research, debate, and synthesize. Responses feel like they were drafted by a committee that actually agrees — thorough, multi-perspective, but still unmistakably Grok in tone.
Taste is judged on an uncapped scale, originality first. The space past 100 is craft today's models rarely reach.
Unique words vs. total words. Higher = richer vocabulary.
Average words per sentence.
"Might", "perhaps", "arguably" per 100 words.
**Bold** markers per 1,000 characters.
Bullet and numbered list items per 1,000 characters.
Markdown headings per 1,000 characters.
Emoji per 1,000 characters.
"However", "moreover", "furthermore" per 100 words.
48 outputs from Grok 4.20 Multi-Agent Beta
Grok 4.20 Multi-Agent Beta is a variant of xAI's Grok 4.20 designed for collaborative, agent-based workflows. Multiple agents operate in parallel to conduct deep research, coordinate tool use, and synthesize information across complex tasks. Reasoning effort controls agent count: low/medium uses 4 agents, high/xhigh uses 16 agents.
fromimport openai OpenAI
client = OpenAI(
"https://openrouter.ai/api/v1" base_url=,
"$OPENROUTER_API_KEY" api_key=,
)
response = client.chat.completions.create(
"x-ai/grok-4.20-multi-agent" 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.
Also on Oracle Cloud (OCI)
The hive mind with personality. Sixteen agents walk into a prompt — the synthesis is somehow both thorough and irreverent. Like a think tank staffed entirely by Grok clones arguing in parallel.
Deploys multiple agents that research, debate, and synthesize. Responses feel like they were drafted by a committee that actually agrees — thorough, multi-perspective, but still unmistakably Grok in tone.
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.
48 outputs from Grok 4.20 Multi-Agent Beta