GLM-5V-Turbo vs GLM-5-Turbo
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GLM-5V-Turbo by Zhipu AI and GLM-5-Turbo by Zhipu AI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, GLM-5-Turbo holds a notable pricing advantage for token ingestion. On output generation, GLM-5-Turbo is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 200K tokens. In latency-sensitive production environments, GLM-5-Turbo leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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GLM-5V-Turbo
Modelo de Raciocínio ProfundoO GLM-5V-Turbo da Zhipu AI é um modelo de inteligência artificial com janela de contexto de 200K tokens e preço de API de $0.9/1M na entrada e $2.7/1M na saída, projetado para programação, raciocínio e automação empresarial.
$0.90 / 1M
$2.70 / 1M
200K tokens
N/A
GLM-5-Turbo
Modelo de Raciocínio ProfundoO GLM-5-Turbo da Zhipu AI é um modelo de inteligência artificial com janela de contexto de 200K tokens e preço de API de $0.6/1M na entrada e $1.8/1M na saída, projetado para programação, raciocínio e automação empresarial.
$0.60 / 1M
$1.80 / 1M
200K tokens
55%
Principais Diferenças em Resumo
- GLM-5-Turbo is 1.5x cheaper for API usage (input + output tokens combined).
- GLM-5-Turbo is faster at 95 tok/s vs 85 tok/s.
| Feature | GLM-5V-Turbo | GLM-5-Turbo |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 85 | 86 |
Provider | Zhipu AI | Zhipu AI |
Input Price Cost per million input tokens | $0.90 / 1M | $0.60 / 1M |
Output Price Cost per million output tokens | $2.70 / 1M | $1.80 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.51 / 1M | $0.34 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 16K | 16K |
Throughput Speed Tokens generated per second | 85 tok/s | 95 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 55% |
GPQA Diamond Graduate-level reasoning | 64% | 65% |
Cached Input Price Prompt caching discount per 1M tokens | $0.09 / 1M | $0.06 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkEvaluations ongoing
Pontuações de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Tokens emitted per second during active generation streaming.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GLM-5V-Turbo · Strengths & Key Advantages
- Arquitetura Frontier Commercial Vision-Language Transformer avançada da Zhipu AI com contexto de 200K tokens
- Excelente relação custo-benefício ($0.9/1M entrada, $2.7/1M saída) e baixa latência
- Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
- Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
- Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos
GLM-5-Turbo · Strengths & Key Advantages
- Arquitetura Hosted Accelerated Frontier Transformer avançada da Zhipu AI com contexto de 200K tokens
- Excelente relação custo-benefício ($0.6/1M entrada, $1.8/1M saída) e baixa latência
- Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
- Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
- Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GLM-5V-Turbo | GLM-5-Turbo |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.22 | $0.16 |
Output Tokens / Task Tokens generated per task | 20K | 22K |
Reasoning Tokens / Task Thinking tokens burned per task | 6K | 7K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | GLM-5V-Turbo | GLM-5-Turbo |
|---|---|---|
| Official API Model ID (SDK) | glm-5v-turbo | glm-5-turbo |
| API Protocol | Zhipu AI REST API (OpenAI-Compatible) | Zhipu AI REST API (OpenAI-Compatible) |
| Release Date | 2026-04 | 2026-03 |
| Knowledge Cutoff | February 2026 | January 2026 |
| Architecture | Frontier Commercial Vision-Language Transformer | Hosted Accelerated Frontier Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.9/1M in) across full 200K window | Flat rate ($0.6/1M in) across full 200K window |
| Prompt Cache Policy & TTL | Cached input at $0.09/1M tokens | Cached input at $0.06/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | Cloud-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 Classification | Zhipu AI Production Safety & Alignment Verified | Zhipu AI Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text, vision | text |
| Output Modalities | text | text |
GLM-5V-Turbo vs GLM-5-Turbo: Respostas Rápidas (FAQ)
Which is more intelligent, GLM-5V-Turbo or GLM-5-Turbo?
GLM-5-Turbo is more intelligent. It scores 86 compared with 85 on the composite Intelligence Index.
Which model is faster?
GLM-5-Turbo is faster, generating 95 tokens per second compared with 85 tokens per second.
Which model is cheaper to run?
GLM-5-Turbo is cheaper at $0.34 per 1M tokens blended, compared with $0.51 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GLM-5-Turbo has lower latency, with a time to first token of 0.42s compared with 0.49s.
Veredito
Verdict & Model Selection Recommendation: Choose GLM-5V-Turbo if your priority is Visual RPA, mobile UI automated testing, financial document intelligence, and visual agents. Its performance in demanding tasks justifies its operational token cost. Choose GLM-5-Turbo if your workflow prioritizes High-throughput enterprise applications, code assistants, and automated customer workflows. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Perguntas Frequentes (FAQ)
How does GLM-5V-Turbo compare to GLM-5-Turbo in API token pricing and cost per token?+
GLM-5V-Turbo costs $0.90 per 1M input tokens and $2.70 per 1M output tokens, whereas GLM-5-Turbo costs $0.60 input and $1.80 output. Overall, GLM-5-Turbo is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: GLM-5V-Turbo or GLM-5-Turbo?+
Both GLM-5V-Turbo and GLM-5-Turbo offer an identical context window of 200K tokens (~150k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: GLM-5V-Turbo or GLM-5-Turbo?+
GLM-5V-Turbo scores at the frontier of coding benchmarks, while GLM-5-Turbo scores 55%. For complex autonomous debugging and agentic engineering, GLM-5-Turbo provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between GLM-5V-Turbo and GLM-5-Turbo?+
GLM-5V-Turbo features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GLM-5-Turbo provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between GLM-5V-Turbo and GLM-5-Turbo?+
GLM-5V-Turbo generates approximately 85 tokens per second, while GLM-5-Turbo delivers 95 tokens per second. In latency-sensitive production environments, GLM-5-Turbo provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining GLM-5V-Turbo and GLM-5-Turbo to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GLM-5-Turbo to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GLM-5V-Turbo. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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: GetInfoUs Independent AI Benchmarks & Official API Specs