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Grok 4.20 Multi-Agent vs Llama 3.3 70B Instruct

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Grok 4.20 Multi-Agent and Llama 3.3 70B Instruct.

xAI

Grok 4.20 Multi-Agent

Grok 4.20 Multi-Agent is a variant of xAIโ€™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...

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Meta

Llama 3.3 70B Instruct

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...

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Technical Specifications

SpecificationGrok 4.20 Multi-AgentLlama 3.3 70B Instruct
ProviderxAIMeta
Context Window2,000,000 tokens131,072 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitybetastable
API AvailableYesYes
Released Date2026-03-312024-12-06

API Pricing Comparison

Input Price per Million Tokens

Grok 4.20 Multi-Agent

$1.25

Llama 3.3 70B Instruct

$0.10

Output Price per Million Tokens

Grok 4.20 Multi-Agent

$2.50

Llama 3.3 70B Instruct

$0.32

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

Grok 4.20 Multi-Agent Quirks & Gotchas

No developer gotchas reported.

Llama 3.3 70B Instruct Quirks & Gotchas

No developer gotchas reported.