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GLM-5-Turbo vs MiniMax-M2.7-highspeed

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GLM-5-Turbo vs MiniMax-M2.7-highspeed: Benchmarks, Pricing & Speed Comparison

Zhipu AI 的 GLM-5-Turbo 与 MiniMax 的 MiniMax-M2.7-highspeed 是当前备受关注的两款主力 AI 模型。GLM-5-Turbo 提供 200K Token 上下文窗口，API 定价为每百万 Token 输入 $0.60 / 输出 $1.80；而 MiniMax-M2.7-highspeed 提供 204K Token 上下文窗口，定价为每百万 Token 输入 $0.25 / 输出 $1.00。以下为两者的基准测试、延迟与成本全面对比。

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Zhipu AI

GLM-5-Turbo

超高速低延迟推理

Zhipu AI 推出的 GLM-5-Turbo 是一款面向实时交互对话、高并发路由与极低延迟生产环境的超高速大模型，具备 200K 上下文窗口、95 Token/秒生成速度与 86/100 综合智能指数（每百万 Token $0.6 输入 / $1.8 输出）。

Intelligence Index86 / 100
Input Token:

$0.60 / 1M

Output Token:

$1.80 / 1M

Context Window:

200K tokens

SWE-bench Verified:

55%

MiniMax

MiniMax-M2.7-highspeed

超高速低延迟推理

MiniMax 推出的 MiniMax-M2.7-highspeed 是一款面向实时交互对话、高并发路由与极低延迟生产环境的超高速大模型，具备 204K 上下文窗口、140 Token/秒生成速度与 82/100 综合智能指数（每百万 Token $0.25 输入 / $1 输出）。

Intelligence Index82 / 100
Input Token:

$0.25 / 1M

Output Token:

$1.00 / 1M

Context Window:

204K tokens

SWE-bench Verified:

N/A

核心差异一览

  • MiniMax-M2.7-highspeed is 2.0x cheaper for API usage (input + output tokens combined).
  • MiniMax-M2.7-highspeed has a larger context window (204K vs 200K tokens).
  • MiniMax-M2.7-highspeed is faster at 140 tok/s vs 95 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGLM-5-TurboMiniMax-M2.7-highspeed
Intelligence Index
Composite reasoning & knowledge score (0-100)
8682
Provider
Zhipu AIMiniMax
Input Price
Cost per million input tokens
$0.60 / 1M$0.25 / 1M
Output Price
Cost per million output tokens
$1.80 / 1M$1.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.34 / 1M$0.17 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text204K tokens~306 A4 pages of text
Max Output Tokens
Per single request
16K8K
Throughput Speed
Tokens generated per second
95 tok/s140 tok/s
SWE-bench Verified
Real-world software engineering
55%N/A
GPQA Diamond
Graduate-level reasoning
65%63%
Cached Input Price
Prompt caching discount per 1M tokens
$0.06 / 1M$0.03 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
MiniMax-M2.7-highspeed
2.0x cheaper monthly runtime
Speed
MiniMax-M2.7-highspeed
+47% faster generation
Context
MiniMax-M2.7-highspeed
204K tokens window

权威基准测试得分对比

Official evaluation metrics verified by independent third-party research labs.

GLM-5-TurboMiniMax-M2.7-highspeed
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

55%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

65%vs63%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

82.5%vs78%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1365ptsvs1335pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs140 tok/s

延迟与响应速度

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
GLM-5-Turbo0.42s
MiniMax-M2.7-highspeed0.29s
Est. End-to-End Response (500 tokens)TTFT + generation time
GLM-5-Turbo5.68s
MiniMax-M2.7-highspeed3.86s

实时 Token 成本模拟器

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
GLM-5-Turbo Monthly API Bill
$2.61 / month
$0.6/1M in · $1.8/1M out
MiniMax-M2.7-highspeed Monthly API Bill
$1.31 / month
$0.25/1M in · $1/1M out
MiniMax-M2.7-highspeed saves approximately $1.30 / month (50%) under this workload.2.0x Savings

GLM-5-Turbo · Strengths & Key Advantages

  • 提供 200K 上下文窗口与最高 16K 输出容量，核心基准表现优异（SWE-bench Verified 55% · GPQA Diamond 65%）
  • 高达 95 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 420 毫秒
  • 极具竞争力的 API 定价（每百万 Token $0.6 输入 / $1.8 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
  • 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

MiniMax-M2.7-highspeed · Strengths & Key Advantages

  • 提供 204K 上下文窗口与最高 8K 输出容量，核心基准表现优异（GPQA Diamond 63% · MMLU-Pro 78%）
  • 高达 140 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 290 毫秒
  • 极具竞争力的 API 定价（每百万 Token $0.25 输入 / $1 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
  • 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
  • 在超长链路的前沿科研推导任务上，深度略逊于顶配重型旗舰推理模型

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGLM-5-TurboMiniMax-M2.7-highspeed
Cost per Task
Estimated USD to finish one task
$0.16$0.06
Output Tokens / Task
Tokens generated per task
22K15K
Reasoning Tokens / Task
Thinking tokens burned per task
7K2K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGLM-5-TurboMiniMax-M2.7-highspeed
Official API Model ID (SDK)glm-5-turbominimax-m2-7-highspeed
API ProtocolZhipu AI REST API (OpenAI-Compatible)MiniMax REST API (OpenAI-Compatible)
Release Date2026-032026-03
Knowledge CutoffJanuary 2026January 2026
ArchitectureHosted Accelerated Frontier TransformerHigh-Throughput Hosted Cloud Accelerator
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.6/1M in) across full 200K windowFlat rate ($0.25/1M in) across full 204K window
Prompt Cache Policy & TTLCached input at $0.06/1M tokensCached input at $0.025/1M tokens
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMCloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier ClassificationZhipu AI Production Safety & Alignment VerifiedMiniMax Production Safety & Alignment Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestexttext
Output Modalitiestexttext

GLM-5-Turbo vs MiniMax-M2.7-highspeed: 常见问题解答 (FAQ)

Which is more intelligent, GLM-5-Turbo or MiniMax-M2.7-highspeed?

GLM-5-Turbo is more intelligent. It scores 86 compared with 82 on the composite Intelligence Index.

Which model is faster?

MiniMax-M2.7-highspeed is faster, generating 140 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

MiniMax-M2.7-highspeed is cheaper at $0.17 per 1M tokens blended, compared with $0.34 (7:2:1 cache:input:output ratio).

Which model has lower latency?

MiniMax-M2.7-highspeed has lower latency, with a time to first token of 0.29s compared with 0.42s.

Which model has a larger context window?

MiniMax-M2.7-highspeed has a larger context window, supporting 204K tokens compared with 200K tokens.

综合结论

综合来看，GLM-5-Turbo（适合：面向实时交互对话、高并发路由与极低延迟生产环境的超高速任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）与 MiniMax-M2.7-highspeed（适合：面向实时交互对话、高并发路由与极低延迟生产环境的超高速任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）各具优势：GLM-5-Turbo 在综合智能与编程基准测试中表现更强，MiniMax-M2.7-highspeed 拥有更快的 Token 生成速度，而 MiniMax-M2.7-highspeed 则在规模化 API 部署中具备更高的成本效益。

常见问题 (FAQ)

在编程和深度推理方面，GLM-5-Turbo 和 MiniMax-M2.7-highspeed 哪个更强？+

在综合智能指数与编程基准评测中，GLM-5-Turbo 表现占优。建议结合上方的 SWE-bench Verified 与 GPQA Diamond 跑分根据具体场景选择。

GLM-5-Turbo 与 MiniMax-M2.7-highspeed 的 API 价格哪个更便宜？+

GLM-5-Turbo 的 API 价格为输入 $0.60 / 输出 $1.80（每百万 Token），MiniMax-M2.7-highspeed 为输入 $0.25 / 输出 $1.00。综合混合成本来看，MiniMax-M2.7-highspeed 更具性价比。

哪款模型拥有更大的上下文窗口和更快的响应速度？+

GLM-5-Turbo 支持 200K Token 上下文窗口，而 MiniMax-M2.7-highspeed 支持 204K Token。在流式生成速度方面，MiniMax-M2.7-highspeed 的吞吐表现更快。

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

数据来源: Zhipu AI 与 MiniMax 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。