โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

GLM 4.5 vs Qwen2.5 72B 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 GLM 4.5 and Qwen2.5 72B Instruct.

Zhipu AI

GLM 4.5

GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens. GLM-4.5 delivers significantly...

View Full Specs
Alibaba

Qwen2.5 72B Instruct

Qwen2.5 72B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and...

View Full Specs

Technical Specifications

SpecificationGLM 4.5Qwen2.5 72B Instruct
ProviderZhipu AIAlibaba
Context Window131,072 tokens131,072 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-07-252024-09-19

API Pricing Comparison

Input Price per Million Tokens

GLM 4.5

$0.60

Qwen2.5 72B Instruct

$0.36

Output Price per Million Tokens

GLM 4.5

$2.20

Qwen2.5 72B Instruct

$0.40

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
N/Avs8530.0%
GLM 4.5
Qwen2.5 72B Instruct
HumanEvalPython coding & logic synthesis
N/Avs8660.0%
GLM 4.5
Qwen2.5 72B Instruct
MATHComplex mathematical problem solving
N/Avs7460.0%
GLM 4.5
Qwen2.5 72B Instruct
GPQAGraduate-level expert reasoning
N/Avs4800.0%
GLM 4.5
Qwen2.5 72B Instruct
HellaSwagCommonsense reasoning and inference
N/Avs8820.0%
GLM 4.5
Qwen2.5 72B Instruct
MT-BenchMulti-turn conversation flow quality
N/Avs912.0%
GLM 4.5
Qwen2.5 72B Instruct

GLM 4.5 Quirks & Gotchas

No developer gotchas reported.

Qwen2.5 72B Instruct Quirks & Gotchas

No developer gotchas reported.