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GLM 5.2 vs Llama 4 Maverick

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 GLM 5.2 and Llama 4 Maverick.

Zhipu AI

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,...

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Meta

Llama 4 Maverick

Meta's next-generation open weights model. Delivers premium agentic capabilities, reasoning, and tool call compliance for local or self-hosted enterprise stacks.

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Technical Specifications

SpecificationGLM 5.2Llama 4 Maverick
ProviderZhipu AIMeta
Context Window1,048,576 tokens1,048,576 tokens
Agent SuitabilityN/A89/100
Time to First Token (TTFT)N/A300 ms
Deployment Modelmanaged apiself hostable
Production Stabilitybetastable
API AvailableYesYes
Released Date2026-06-162026-05-25

API Pricing Comparison

Input Price per Million Tokens

GLM 5.2

$0.93

Llama 4 Maverick

$0.15

Output Price per Million Tokens

GLM 5.2

$3.00

Llama 4 Maverick

$0.60

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.

MMLUGeneral knowledge & multi-task understanding
8950.0%vs9150.0%
GLM 5.2
Llama 4 Maverick
HumanEvalPython coding & logic synthesis
9120.0%vs9380.0%
GLM 5.2
Llama 4 Maverick
MATHComplex mathematical problem solving
8050.0%vs8920.0%
GLM 5.2
Llama 4 Maverick
GPQAGraduate-level expert reasoning
5350.0%vs7640.0%
GLM 5.2
Llama 4 Maverick
HellaSwagCommonsense reasoning and inference
8980.0%vs9720.0%
GLM 5.2
Llama 4 Maverick
MT-BenchMulti-turn conversation flow quality
930.0%vs940.0%
GLM 5.2
Llama 4 Maverick

GLM 5.2 Quirks & Gotchas

No developer gotchas reported.

Llama 4 Maverick Quirks & Gotchas

  • โ–ธSelf-hostable via Ollama/Docker โ€” ideal for on-premise deployments
  • โ–ธRequires specific system prompt for optimal function calling reliability