Head-to-Head Model Comparison

GLM-5V-Turbo vs Hunyuan Large V2

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GLM-5V-Turbo vs Hunyuan Large V2: Benchmarks, Pricing & Speed Comparison

GLM-5V-Turbo by Zhipu AI and Hunyuan Large V2 by Tencent 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, Hunyuan Large V2 holds a notable pricing advantage for token ingestion. On output generation, GLM-5V-Turbo is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Hunyuan Large V2 provides an expanded memory horizon with 512K tokens. In latency-sensitive production environments, GLM-5V-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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Zhipu AI

GLM-5V-Turbo

Derin Akıl Yürütme Modeli

Zhipu AI tarafından geliştirilen GLM-5V-Turbo, 200K token bağlam penceresi ve 1M girdi başına $0.9, 1M çıktı başına $2.7 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.

Intelligence Index85 / 100
Input Token:

$0.90 / 1M

Output Token:

$2.70 / 1M

Context Window:

200K tokens

SWE-bench Verified:

N/A

Tencent

Hunyuan Large V2

Derin Akıl Yürütme Modeli

Tencent tarafından geliştirilen Hunyuan Large V2, 512K token bağlam penceresi ve 1M girdi başına $0.7, 1M çıktı başına $2.8 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.

Intelligence Index85 / 100
Input Token:

$0.70 / 1M

Output Token:

$2.80 / 1M

Context Window:

512K tokens

SWE-bench Verified:

N/A

Bir Bakışta Temel Farklar

  • Hunyuan Large V2 is 1.1x cheaper for API usage (input + output tokens combined).
  • Hunyuan Large V2 has a larger context window (512K vs 200K tokens).
  • GLM-5V-Turbo is faster at 85 tok/s vs 80 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGLM-5V-TurboHunyuan Large V2
Intelligence Index
Composite reasoning & knowledge score (0-100)
8585
Provider
Zhipu AITencent
Input Price
Cost per million input tokens
$0.90 / 1M$0.70 / 1M
Output Price
Cost per million output tokens
$2.70 / 1M$2.80 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.51 / 1M$0.47 / 1M
Context Window
Maximum input + output tokens
200K tokens~300 A4 pages of text512K tokens~768 A4 pages of text
Max Output Tokens
Per single request
16K16K
Throughput Speed
Tokens generated per second
85 tok/s80 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A
GPQA Diamond
Graduate-level reasoning
64%66%
Cached Input Price
Prompt caching discount per 1M tokens
$0.09 / 1M$0.07 / 1M

Hangi Alanda Kim Kazanıyor?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Hunyuan Large V2
1.1x cheaper monthly runtime
Speed
GLM-5V-Turbo
+6% faster generation
Context
Hunyuan Large V2
512K tokens window

Doğrulanmış Benchmark Puanları

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

GLM-5V-TurboHunyuan Large V2
GPQA Diamond (Doctorate-Level Science & Math)

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

64%vs66%
MMLU-Pro (Multi-task Language Understanding)

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

81%vs82.5%
LMSYS Chatbot Arena Elo

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

1355ptsvs1365pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

85 tok/s vs80 tok/s

Gecikme Süresi ve Yanıt Hızı

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-5V-Turbo0.49s
Hunyuan Large V20.48s
Est. End-to-End Response (500 tokens)TTFT + generation time
GLM-5V-Turbo6.37s
Hunyuan Large V26.73s

Gerçek Zamanlı Token Maliyet Simülatörü

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-5V-Turbo Monthly API Bill
$3.92 / month
$0.9/1M in · $2.7/1M out
Hunyuan Large V2 Monthly API Bill
$3.67 / month
$0.7/1M in · $2.8/1M out
Hunyuan Large V2 saves approximately $0.24 / month (6%) under this workload.1.1x Savings

GLM-5V-Turbo · Strengths & Key Advantages

  • Zhipu AI imzalı gelişmiş Frontier Commercial Vision-Language Transformer mimarisi ve 200K token bağlam kapasitesi
  • Dengeli API maliyeti ($0.9/1M girdi, $2.7/1M çıktı) ve yüksek yanıt hızı
  • Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
  • Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
  • Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir

Hunyuan Large V2 · Strengths & Key Advantages

  • Tencent imzalı gelişmiş High-Scale Sparse Mixture-of-Experts Transformer mimarisi ve 512K token bağlam kapasitesi
  • Dengeli API maliyeti ($0.7/1M girdi, $2.8/1M çıktı) ve yüksek yanıt hızı
  • Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
  • Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
  • Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir

Token Use & Task Economics

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

MetricGLM-5V-TurboHunyuan Large V2
Cost per Task
Estimated USD to finish one task
$0.22$0.22
Output Tokens / Task
Tokens generated per task
20K22K
Reasoning Tokens / Task
Thinking tokens burned per task
6K7K

Teknik Özellikler

Architecture, release timeline, capabilities, and modalities.

FeatureGLM-5V-TurboHunyuan Large V2
Official API Model ID (SDK)glm-5v-turbohunyuan-large-v2
API ProtocolZhipu AI REST API (OpenAI-Compatible)Tencent REST API (OpenAI-Compatible)
Release Date2026-042026-05
Knowledge CutoffFebruary 2026February 2026
ArchitectureFrontier Commercial Vision-Language TransformerHigh-Scale Sparse Mixture-of-Experts Transformer
ParametersConfidential500B total (30B active MoE)
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 ($0.9/1M in) across full 200K windowFlat rate ($0.7/1M in) across full 512K window
Prompt Cache Policy & TTLCached input at $0.09/1M tokensCached input at $0.07/1M 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 & 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) · Vision (~258–765 tokens per image tile)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 VerifiedTencent 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, visiontext
Output Modalitiestexttext

GLM-5V-Turbo vs Hunyuan Large V2: Hızlı Yanıtlar (SSS)

Which model is faster?

GLM-5V-Turbo is faster, generating 85 tokens per second compared with 80 tokens per second.

Which model is cheaper to run?

Hunyuan Large V2 is cheaper at $0.47 per 1M tokens blended, compared with $0.51 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Hunyuan Large V2 has lower latency, with a time to first token of 0.48s compared with 0.49s.

Which model has a larger context window?

Hunyuan Large V2 has a larger context window, supporting 512K tokens compared with 200K tokens.

Sonuç

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 Hunyuan Large V2 if your workflow prioritizes Social chatbots, creative writing, game NPC dialogue, and extensive document summarization. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Sıkça Sorulan Sorular (SSS)

How does GLM-5V-Turbo compare to Hunyuan Large V2 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 Hunyuan Large V2 costs $0.70 input and $2.80 output. Overall, Hunyuan Large V2 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 Hunyuan Large V2?+

GLM-5V-Turbo supports a context window of 200K tokens (~150k words), while Hunyuan Large V2 supports 512K tokens (~384k words). Therefore, Hunyuan Large V2 can process more textual data and document context in a single prompt.

Which AI model is better for software engineering and coding: GLM-5V-Turbo or Hunyuan Large V2?+

GLM-5V-Turbo scores at the frontier of coding benchmarks, while Hunyuan Large V2 scores competitively for software generation. For complex autonomous debugging and agentic engineering, GLM-5V-Turbo provides robust code generation and tool calling.

What is the difference in reasoning capability and extended thinking between GLM-5V-Turbo and Hunyuan Large V2?+

GLM-5V-Turbo features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Hunyuan Large V2 provides chain-of-thought reasoning depth for complex math and science.

How does inference speed (tokens per second) compare between GLM-5V-Turbo and Hunyuan Large V2?+

GLM-5V-Turbo generates approximately 85 tokens per second, while Hunyuan Large V2 delivers 80 tokens per second. In latency-sensitive production environments, GLM-5V-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 Hunyuan Large V2 to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Hunyuan Large V2 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%.

AI Terminology & Guide
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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.

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