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Head-to-Head Model Comparison

Gemini 2.5 Flash vs GLM-4.5-Flash

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
Gemini 2.5 Flash vs GLM-4.5-Flash: Benchmarks, Pricing & Speed Comparison

Google 的 Gemini 2.5 Flash 与 Zhipu AI 的 GLM-4.5-Flash 是当前备受关注的两款主力 AI 模型。Gemini 2.5 Flash 提供 1.05M Token 上下文窗口，API 定价为每百万 Token 输入 $0.30 / 输出 $2.50；而 GLM-4.5-Flash 提供 131.1K Token 上下文窗口，定价为每百万 Token 输入 $0.01 / 输出 $0.02。以下为两者的基准测试、延迟与成本全面对比。

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Google

Gemini 2.5 Flash

超高速低延迟推理

Google 推出的 Gemini 2.5 Flash 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 1.0M 上下文窗口、160 Token/秒生成速度与 68/100 综合智能指数（每百万 Token $0.3 输入 / $2.5 输出）。

Intelligence Index68 / 100
Input Token:

$0.30 / 1M

Output Token:

$2.50 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

58.2%

Zhipu AI

GLM-4.5-Flash

超高速低延迟推理

Zhipu AI 推出的 GLM-4.5-Flash 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 131K 上下文窗口、170 Token/秒生成速度与 72/100 综合智能指数（每百万 Token $0.01 输入 / $0.02 输出）。

Intelligence Index72 / 100
Input Token:

$0.01 / 1M

Output Token:

$0.02 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

N/A

核心差异一览

  • GLM-4.5-Flash is 81.5x cheaper for API usage (input + output tokens combined).
  • Gemini 2.5 Flash has a larger context window (1M vs 131K tokens).
  • GLM-4.5-Flash is faster at 170 tok/s vs 160 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGemini 2.5 FlashGLM-4.5-Flash
Intelligence Index
Composite reasoning & knowledge score (0-100)
6872
Provider
GoogleZhipu AI
Input Price
Cost per million input tokens
$0.30 / 1M$0.01 / 1M
Output Price
Cost per million output tokens
$2.50 / 1M$0.02 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.36 / 1M$0.00 / 1M
Context Window
Maximum input + output tokens
1.05M tokens~1,573 A4 pages of text131.1K tokens~197 A4 pages of text
Max Output Tokens
Per single request
66K8K
Throughput Speed
Tokens generated per second
160 tok/s170 tok/s
SWE-bench Verified
Real-world software engineering
58.2%N/A
GPQA Diamond
Graduate-level reasoning
75.4%N/A
Cached Input Price
Prompt caching discount per 1M tokens
$0.07 / 1M$0.00 / 1M

各项指标谁更胜一筹？

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
GLM-4.5-Flash
81.5x cheaper monthly runtime
Speed
GLM-4.5-Flash
+6% faster generation
Context
Gemini 2.5 Flash
1.05M tokens window

权威基准测试得分对比

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

Gemini 2.5 FlashGLM-4.5-Flash
SWE-bench Verified (Autonomous Coding)

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

58.2%vsN/A
GPQA Diamond (Doctorate-Level Science & Math)

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

75.4%vsN/A
MMLU-Pro (Multi-task Language Understanding)

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

83.2%vs68%
LMSYS Chatbot Arena Elo

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

1385ptsvs1240pts
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

84.5%vsN/A
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

160 tok/s vs170 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
Gemini 2.5 Flash0.45s
GLM-4.5-Flash0.22s
Est. End-to-End Response (500 tokens)TTFT + generation time
Gemini 2.5 Flash3.58s
GLM-4.5-Flash3.16s

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)
Gemini 2.5 Flash Monthly API Bill
$2.81 / month
$0.3/1M in · $2.5/1M out
GLM-4.5-Flash Monthly API Bill
$0.03 / month
$0.01/1M in · $0.02/1M out
GLM-4.5-Flash saves approximately $2.78 / month (99%) under this workload.81.5x Savings

Gemini 2.5 Flash · Strengths & Key Advantages

  • 提供 1.0M 上下文窗口与最高 66K 输出容量，核心基准表现优异（SWE-bench Verified 58.2% · GPQA Diamond 75.4%）
  • 高达 160 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 450 毫秒
  • 极具竞争力的 API 定价（每百万 Token $0.3 输入 / $2.5 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

GLM-4.5-Flash · Strengths & Key Advantages

  • 提供 131K 上下文窗口与最高 8K 输出容量，核心基准表现优异（MMLU-Pro 68% · Arena Elo 1240）
  • 高达 170 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 220 毫秒
  • 极具竞争力的 API 定价（每百万 Token $0.01 输入 / $0.02 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.

MetricGemini 2.5 FlashGLM-4.5-Flash
Cost per Task
Estimated USD to finish one task
$0.85$0.01
Output Tokens / Task
Tokens generated per task
32K10K
Reasoning Tokens / Task
Thinking tokens burned per task
14K0K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGemini 2.5 FlashGLM-4.5-Flash
Official API Model ID (SDK)models/gemini-2-5-flashglm-4-5-flash
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKZhipu AI REST API (OpenAI-Compatible)
Release Date2025-062025-07
Knowledge CutoffMarch 2025May 2025
ArchitectureHigh-throughput sparse multimodal transformer with thinking modeUltra-High-Speed Distilled Transformer
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Standard rate up to 200K tokens; 2x input/output tier above 200K tokensFlat rate ($0.01/1M in) across full 131K window
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0.075/1M with configurable TTLCached input at $0.001/1M tokens
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)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 & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationAPI Prompt Engineering & RAG Distillation
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedZhipu AI 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 Modalitiestext, vision, audio, videotext
Output Modalitiestexttext

Gemini 2.5 Flash vs GLM-4.5-Flash: 常见问题解答 (FAQ)

Which is more intelligent, Gemini 2.5 Flash or GLM-4.5-Flash?

GLM-4.5-Flash is more intelligent. It scores 72 compared with 68 on the composite Intelligence Index.

Which model is faster?

GLM-4.5-Flash is faster, generating 170 tokens per second compared with 160 tokens per second.

Which model is cheaper to run?

GLM-4.5-Flash is cheaper at $0.00 per 1M tokens blended, compared with $0.36 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GLM-4.5-Flash has lower latency, with a time to first token of 0.22s compared with 0.45s.

Which model has a larger context window?

Gemini 2.5 Flash has a larger context window, supporting 1.05M tokens compared with 131.1K tokens.

综合结论

综合来看，Gemini 2.5 Flash（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 GLM-4.5-Flash（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-4.5-Flash 在综合智能与编程基准测试中表现更强，GLM-4.5-Flash 拥有更快的 Token 生成速度，而 GLM-4.5-Flash 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，Gemini 2.5 Flash 和 GLM-4.5-Flash 哪个更强？+

在综合智能指数与编程基准评测中，GLM-4.5-Flash 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。

Gemini 2.5 Flash 与 GLM-4.5-Flash 的 API 价格哪个更便宜？+

Gemini 2.5 Flash 的 API 价格为输入 $0.30 / 输出 $2.50（每百万 Token），GLM-4.5-Flash 为输入 $0.01 / 输出 $0.02。综合混合成本来看，GLM-4.5-Flash 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？+

Gemini 2.5 Flash 支持 1.05M Token 上下文窗口，而 GLM-4.5-Flash 支持 131.1K Token。在流式生成速度方面，GLM-4.5-Flash 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: Google 与 Zhipu AI 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。