See key specs and per-benchmark scores for each model/mode. Scroll horizontally for all columns. 当前对比 2 个模型的评测数据与核心参数。
MiniMax-M2.7
GLM-5
Compare benchmark results across thinking modes and tool usage.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Best Overall
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Best Single
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Thinking Mode (Default)
MiniMax-M2.7 · 1 Modality support
Higher is usually better; “—” means no score.
Complete scores for each model/mode across selected benchmarks.
Feature compare
Licensing, MoE architecture, and multi-modality support.
| Features & specs | MI MiniMax-M2.7MiniMaxAI | GL GLM-5智谱AI |
|---|---|---|
Model snapshots | ||
Organization | MiniMaxAI | 智谱AI |
模型全名 | MiniMax-M2.7 | GLM-5 |
模型简介 | Not provided | Not provided |
模型类型 | 推理大模型 | 聊天大模型 |
模型代号 | minimax-m2-7 | glm-5 |
Release | 2026-03-18 | 2026-02-11 |
MoE | Yes | Yes |
规格与性能 | ||
Context length | 200K | 200K |
Parameters | 2290 | 7440 |
激活参数量 | 100 | 400 |
模型规模 | 100b | 100b |
模型大小 | 未知 | 1.51TB |
推理速度 | ||
推理等级 | ||
最大输出 | 204800 | 131072 |
Supported modes | No mode data | No mode data |
开源与许可 | ||
Code Open Source | Not provided | Not provided |
Weights Open Source | Not provided | Closed Source |
Commercial use | 不可以商用 | 免费商用授权 |
Modality support | ||
Text Input/Output | / | / |
Image Input/Output | Not provided | Not provided |
Audio Input/Output | Not provided | Not provided |
Video Input/Output | Not provided | Not provided |
Embedding Input/Output | Not provided | Not provided |
API 接口详情 | ||
Text 价格 | Input: $0.3 / 1M tokensOutput: $1.2 / 1M tokensCache: $0.375 / 1M tokens | Input: $1 / 1M tokensOutput: $3.2 / 1M tokensCache: $0.2 / 1M tokens |
Image API pricing | Not provided | Not provided |
Audio API pricing | Not provided | Not provided |
Video API pricing | Not provided | Not provided |
Embedding API pricing | Not provided | Not provided |
Resources | ||
GitHub | Repo | Repo |
Hugging Face | Model Page | Model Page |
Official Page | Not provided | Not provided |
Guides | Not provided | Not provided |
Papers | MiniMax M2.7: Early Echoes of Self-Evolution | GLM-5: From Vibe Coding to Agentic Engineering |
DataLearnerAI | MiniMax M2.7 发布：模型开始帮自己训练自己 | Not provided |
API pricing
Side-by-side input/output token pricing
