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Grok 4.20 Multi-Agent vs GLM 5.2

Detailed technical comparison between Grok 4.20 Multi-Agent (xAI) and GLM 5.2 (Zhipu AI). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

⚡ Executive Summary & Verdict

Comparison Snapshot

Grok 4.20 Multi-Agent: 0 WinsvsGLM 5.2: 6 Wins
Context Leader

Grok 4.20 Multi-Agent

2,000,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

GLM 5.2

$0.80 / MTok
xAIactive

Grok 4.20 Multi-Agent

Grok 4.20 Multi-Agent 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...

View Grok 4.20 Multi-Agent Full Specs →
Zhipu AIactive

GLM 5.2

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering,...

View GLM 5.2 Full Specs →

Technical Specifications

🏆 = Superior Spec
SpecificationGrok 4.20 Multi-AgentGLM 5.2
ProviderxAIZhipu AI
Context Window2,000,000 tokens🏆1,048,576 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitybetabeta
API AvailableYesYes
Released Date2026-03-312026-06-16

API Pricing Comparison

Input Price per Million Tokens

Grok 4.20 Multi-Agent

$1.25

GLM 5.2

$0.80

Output Price per Million Tokens

Grok 4.20 Multi-Agent

$2.50

GLM 5.2

$2.50

💡 Cost Ratio: GLM 5.2 is 1.6x cheaper per input token than Grok 4.20 Multi-Agent.

Want to test both models live?

Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.

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Benchmark Performance Metrics

Standardized Scores (0–100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
80.8%vs89.5%+8.7% GLM 5.2
Grok 4.20 Multi-Agent
GLM 5.2 🏆
HumanEvalPython coding & logic synthesis
79.0%vs91.2%+12.2% GLM 5.2
Grok 4.20 Multi-Agent
GLM 5.2 🏆
MATHComplex mathematical problem solving
56.2%vs80.5%+24.3% GLM 5.2
Grok 4.20 Multi-Agent
GLM 5.2 🏆
GPQAGraduate-level expert reasoning
41.6%vs53.5%+11.9% GLM 5.2
Grok 4.20 Multi-Agent
GLM 5.2 🏆
HellaSwagCommonsense reasoning and inference
80.4%vs89.8%+9.4% GLM 5.2
Grok 4.20 Multi-Agent
GLM 5.2 🏆
MT-BenchMulti-turn conversation flow quality
8.6%vs9.3%+0.7% GLM 5.2
Grok 4.20 Multi-Agent
GLM 5.2 🏆

Grok 4.20 Multi-Agent Quirks & Gotchas

No developer gotchas reported.

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

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