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

GLM 4.6 vs MiniMax M2.7

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 4.6 and MiniMax M2.7.

Zhipu AI

GLM 4.6

Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...

View Full Specs
MiniMax

MiniMax M2.7

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...

View Full Specs

Technical Specifications

SpecificationGLM 4.6MiniMax M2.7
ProviderZhipu AIMiniMax
Context Window202,752 tokens204,800 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-09-302026-03-18

API Pricing Comparison

Input Price per Million Tokens

GLM 4.6

$0.43

MiniMax M2.7

$0.18

Output Price per Million Tokens

GLM 4.6

$1.74

MiniMax M2.7

$0.72

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/Avs8250.0%
GLM 4.6
MiniMax M2.7
HumanEvalPython coding & logic synthesis
N/Avs8000.0%
GLM 4.6
MiniMax M2.7
MATHComplex mathematical problem solving
N/Avs5400.0%
GLM 4.6
MiniMax M2.7
GPQAGraduate-level expert reasoning
N/Avs3900.0%
GLM 4.6
MiniMax M2.7
HellaSwagCommonsense reasoning and inference
N/Avs8400.0%
GLM 4.6
MiniMax M2.7
MT-BenchMulti-turn conversation flow quality
N/Avs870.0%
GLM 4.6
MiniMax M2.7

GLM 4.6 Quirks & Gotchas

No developer gotchas reported.

MiniMax M2.7 Quirks & Gotchas

No developer gotchas reported.