Head-to-Head Model Comparison

Gemini 2.5 Flash vs GLM-4.5-Flash

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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Related topics (12)
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

Gemini 2.5 Flash da Google e GLM-4.5-Flash da Zhipu AI são dois modelos de IA de destaque. O Gemini 2.5 Flash oferece uma janela de contexto de 1.05M tokens a $0.30/$2.50 por milhão de tokens, enquanto o GLM-4.5-Flash oferece 131.1K tokens de contexto a $0.01/$0.02 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.

Comparação Direta (VS)

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Google

Gemini 2.5 Flash

Inferência Ultrarrápida

O Gemini 2.5 Flash da Google é um modelo de IA projetado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, oferecendo janela de contexto de 1.0M, velocidade de 160 tokens/s, índice de inteligência de 68/100 e

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

Inferência Ultrarrápida

O GLM-4.5-Flash da Zhipu AI é um modelo de IA projetado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, oferecendo janela de contexto de 131K, velocidade de 170 tokens/s, índice de inteligência de 72/100 e

Intelligence Index72 / 100
Input Token:

$0.01 / 1M

Output Token:

$0.02 / 1M

Context Window:

131.1K tokens

SWE-bench Verified:

N/A

Principais Diferenças em Resumo

  • 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

Quem vence em cada categoria?

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

Pontuações de Benchmarks Verificadas

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

Latência e Tempo de Resposta

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

Simulador Interativo de Custo de Tokens

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

  • Janela de contexto de 1.0M com limite máximo de saída de 66K tokens (SWE-bench Verified 58.2% · GPQA Diamond 75.4%)
  • Taxa de transferência rápida de 160 tokens/segundo com latência inicial (TTFT) de 450 ms
  • Economia de API competitiva ($0.3/$2.5 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
  • Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
  • Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

GLM-4.5-Flash · Strengths & Key Advantages

  • Janela de contexto de 131K com limite máximo de saída de 8K tokens (MMLU-Pro 68% · Arena Elo 1240)
  • Taxa de transferência rápida de 170 tokens/segundo com latência inicial (TTFT) de 220 ms
  • Economia de API competitiva ($0.01/$0.02 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
  • Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
  • Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

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

Especificações Técnicas

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: Respostas Rápidas (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.

Veredito

Tanto Gemini 2.5 Flash (Indicado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, arquiteturas RAG corporativas e integração escalável via API.) quanto GLM-4.5-Flash (Indicado para respostas em tempo real com latência ultrabaixa e roteamento de alto volume, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: GLM-4.5-Flash lidera em inteligência geral e programação, GLM-4.5-Flash oferece geração mais rápida e GLM-4.5-Flash apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Gemini 2.5 Flash ou GLM-4.5-Flash?+

Nas avaliações de inteligência e código, GLM-4.5-Flash leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Gemini 2.5 Flash ou GLM-4.5-Flash?+

O Gemini 2.5 Flash custa $0.30 / $2.50 por 1M de tokens (entrada/saída) e o GLM-4.5-Flash custa $0.01 / $0.02. No custo combinado, GLM-4.5-Flash é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Gemini 2.5 Flash suporta 1.05M tokens de contexto contra 131.1K tokens do GLM-4.5-Flash, enquanto GLM-4.5-Flash entrega maior velocidade de geração.

AI Terminology & Guide
Explore Glossary →

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

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.

Fontes oficiais: Documentação oficial de API da Google e Zhipu AI e benchmarks independentes (2026).