Models

GLM 5.2 vs MiniMax M2.7

Compare GLM 5.2 from Z.AI and MiniMax M2.7 from Minimax on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

Z.AIGLM 5.2MinimaxMiniMax M2.7
36% off
Z.AI logo
GLM 5.2
Z.AI · text → text

GLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow engineering standards more consistently, and complete the full development workflow from requirements to multi-platform deployment in a single task.

Input$1.1268$0.7212 /M
Output$3.9438$2.524 /M
Cache read$0.2817$0.1803 /M
Minimax logo
MiniMax M2.7
Minimax · text → text

MiniMax M2.7 can autonomously build complex Agent Harnesses and, leveraging capabilities such as Agent Teams, complex Skills, and the Tool Search tool, complete highly complex productivity tasks.

Input$0.2958 /M
Output$1.1832 /M
Cache read$0.0592 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

GLM 5.2
MiniMax M2.7
Input /M
$1.1268$0.721236%
$0.2958
Output /M
$3.9438$2.52436%
$1.1832
Cache read /M
$0.2817$0.180336%
$0.0592
Context length
1,000,000
200,000
Max output
128,000
128,000
Time to First Token
0.6 s
2.5 s
Throughput
35.9 tok/s
28.0 tok/s
Modalities
text
text
Supported Parameters
thinkingtoolsfunction callingstructured outputs
thinkingtoolsfunction callingstructured outputs
API Formats
chat_completions · claude_api
Released
June 16, 2026
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Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

glm-5.2minimax-m2.7

Tokens / day

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Requests / day

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Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

glm-5.2minimax-m2.7

Throughput (tok/s)

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TTFT (s)

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Uptime (%)

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LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
glm-5.2minimax-m2.7
1340140014601520
Overall
14151472
Coding
14801509
Math
14221476
Hard prompts
14401492
Instruction following
14071465
Multi-turn
14261469
Creative writing
13621451
Longer query
14321482
Chinese
14421517
English
14351480
WebDev Arena
glm-5.2minimax-m2.7
1360144015201600
Overall
13981587
React
13881599
HTML
14041539
Gaming
13841625
Simulations
13851612
Data analytics
14031543

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

MiniMax M2.7
$35.50 /mo
GLM 5.2
$127$81.13 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: GLM 5.2, MiniMax M2.7?

MiniMax M2.7: $1.1832/M output tokens; GLM 5.2: $2.524/M. Use the cost calculator above to estimate your own workload.

How do their coding arena scores compare?

GLM 5.2: 1509; MiniMax M2.7: 1480 (LMArena coding leaderboard).

Which responds faster?

GLM 5.2: 0.6s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

GLM 5.2 accepts 1,000,000 and MiniMax M2.7 accepts 200,000 input tokens. Maximum output per request is 128,000 tokens on GLM 5.2 and 128,000 tokens on MiniMax M2.7.

Which one generates tokens faster?

GLM 5.2 at 35.9 tok/s and MiniMax M2.7 at 28.0 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

GLM 5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs; MiniMax M2.7 accepts text input and supports thinking, tool calling, function calling and structured outputs.

Can I call GLM 5.2 and MiniMax M2.7 with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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