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xAI · Balanced

Grok 4.20 Multi-Agent

Added Mar 31, 2026

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Use in the app

Grok 4.20 Multi-Agent is tuned for collaborative agentic workflows while keeping the same 2M-token context window and multimodal support. Content policy rejections can still be charged: SpaceXAI may pass through a $0.05 moderation-failure fee, or a $0.055 usage-guidelines violation fee, depending on which rejection upstream returns.

  • Reasoning
  • Tools
  • Vision
  • Structured output
Input
Text, Images
Output
Text
Reasoning effort
low · medium · high · xhigh
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$1.25
Output
$2.50
Cache read
$0.20

Reference prices as published by the model provider. API example

Specifications

Context window
2M
Max output
131.1K
Average output (7 days)
3.3K tokens
Longer than 97% of 465 models

Side by side

Grok 4.20 Multi-Agent compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Grok 4.20 Multi-AgentxAIThis modelGrok 4.7xAIRemove
ProviderxAIxAI
Discovery tierBalancedFrontier
AddedMar 31, 2026Sep 21, 2026
Limits
Context window2MBest500K
Max output131.07K—
Average output3.3K tokens1.3K tokens
Pricing, USD per 1M tokens
Input$1.25Best$2.00
Output$2.50Best$6.00
Cache read$0.20Best$0.50
Performance
Throughput—153.3 tok/s
Time to first token—13.6 s
Request success (24h)—99.9%
Benchmark indexes
Intelligence Index—46.3
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesYes
Reasoning effortlow, medium, high, xhighlow, medium, high, xhigh

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Grok 4.20 Multi-Agent
  • Grok 4.7

Intelligence Index

  • Grok 4.20 Multi-Agent—
  • Grok 4.746.3
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 63.5%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 37.7%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 1,630 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 1,707 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 23.2%

  • AA-LCRv1.1

    Reasoning across long documents

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 77.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 18.9%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 42.3%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 24.7%

  • SciCode

    Scientific computing in Python

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 57.8%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Grok 4.20 Multi-Agent: —
    • Grok 4.7: 77.0%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "x-ai/grok-4.20-multi-agent",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="x-ai/grok-4.20-multi-agent",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

xAI

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