Verified 2026 API Rates • Prompt Caching & Batch ROI

Z.ai: GLM 5.1 vs Tencent: Hy4

Compare real-world API costs for Z.ai: GLM 5.1 ($1.4/$4.4) vs Tencent: Hy4 ($0.417/$1.2505). Calculate Prompt Caching ROI & Batch API savings.

Tencent: Hy4 saves up to 70% on base input tokens
Zhipu AI

Z.ai: GLM 5.1

glm-5.1
Base Input Rate
$1.40 / 1M
Output Rate
$4.40 / 1M
Prompt Cache Read
$0.26 / 1M (-81.43%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
204.8k tokens
Quality Index (MMLU)
88
Tencent

Tencent: Hy4

hy4
Base Input Rate
$0.42 / 1M
Output Rate
$1.25 / 1M
Prompt Cache Read
$0.021 / 1M (-94.96%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
Not Supported
Context Window
1,048.576k tokens
Quality Index (MMLU)
88
Differential Module 1

Prompt Caching ROI & Write Surcharge Break-Even Analysis

Prompt caching drastically reduces input token costs for static prefixes like system prompts, tool schemas, and document chunks. Compare caching mechanisms between Z.ai: GLM 5.1 and Tencent: Hy4:

Z.ai: GLM 5.1 Caching Profile-81.43% read discount

  • Cached Read Price: $0.260 per 1M tokens.
  • Write Surcharge: $0.00 (automatic caching with zero write penalty).
  • Minimum Cache Prefix: 1,024 tokens.
  • Amortization Rule: Immediate net savings from first cached read call.

Tencent: Hy4 Caching Profile-94.96% read discount

  • Cached Read Price: $0.021 per 1M tokens.
  • Write Surcharge: $0.00 (automatic caching with zero write penalty).
  • Minimum Cache Prefix: 1,024 tokens.
  • Amortization Rule: Immediate net savings from first cached read call.
Differential Module 2

Batch API 50% Discount Offload vs Real-Time SLA

Asynchronous Batch APIs cut total token expenditures in half (50% off input and output) in exchange for non-realtime execution (up to 24-hour turnaround SLA).

Model / ArchitectureStandard Input / OutputBatch 50% Off Input / OutputTurnaround SLAOptimal Use Cases
Z.ai: GLM 5.1$1.40 / $4.40$0.70 / $2.20 (-50%)24 Hours max (typically 30m - 2h)Bulk evaluation, dataset labeling, background summarization
Tencent: Hy4$0.42 / $1.25Standard on-demand rateInstant real-timeOffline document translation, embedding backfills, test suites
Differential Module 3

Context Window Escalation & Tiered Pricing Architecture

Massive context windows allow ingesting entire repositories or books, but pricing models differ drastically between flat-rate vendors and tiered step-up pricing.

Z.ai: GLM 5.1 Context Capacity

Provides a 204.8k token context window with a maximum output limit of 131.072k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

Tencent: Hy4 Context Capacity

Provides a 1,048.576k token context window with a maximum output limit of 65.536k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

Quill Strategic Content

Real-World Production Scenarios: Monthly Spend Projections

Pre-computed monthly engineering bill projections across 3 representative enterprise application workloads:

Scenario 1

RAG Knowledge Base & Enterprise Search

100,000 queries/month, 3,500 input tokens (system + 5 retrieved chunks), 400 output tokens, 75% prompt cache hit rate.

Z.ai: GLM 5.1:$366.75/mo
Tencent: Hy4:$92.02/mo
Delta Savings:-$274.73 (75%)
Architecture Verdict:Tencent: Hy4 delivers 75% lower monthly spend ($274.73/mo savings) for this workload profile.
Scenario 2

Multi-Turn Coding Agent & ReAct Loops

25,000 tasks/month, 8,000 input tokens (accumulating conversation context & tool schemas), 1,200 output tokens, 85% cache hit rate.

Z.ai: GLM 5.1:$201.83/mo
Tencent: Hy4:$53.59/mo
Delta Savings:-$148.24 (73%)
Architecture Verdict:Tencent: Hy4 delivers 73% lower monthly spend ($148.24/mo savings) for this workload profile.
Scenario 3

High-Throughput Offline Data Extraction

500,000 records/month, 1,500 input tokens, 250 output tokens, 100% batch offload (24-hour turnaround SLA).

Z.ai: GLM 5.1:$714.50/mo
Tencent: Hy4:$409.66/mo
Delta Savings:-$304.84 (43%)
Architecture Verdict:Tencent: Hy4 delivers 43% lower monthly spend ($304.84/mo savings) for this workload profile.
Motor Interactivo en Tiempo Real

Z.ai: GLM 5.1 vs Tencent: Hy4

Cálculos de costos mensuales en 3 cargas de trabajo empresariales habituales (RAG, Agente de Código y Limpieza por Lotes):

Live 50ms Engine
Peticiones Mensuales100,000
Tokens de Entrada / Pet.4,000
Tokens de Salida1,000
Tasa de Acierto de Caché70%
Descarga a Batch API0%
Tencent: Hy4 Más Económico

ahorra aproximadamente

Z.ai: GLM 5.1$680.80$6.808// 1k peticiones
vs
Tencent: Hy4$180.97$1.810// 1k peticiones
Developer FAQs

Frequently Asked Questions: Z.ai: GLM 5.1 vs Tencent: Hy4

Authoritative answers on API rate limits, pricing math, break-even thresholds, and architectural migration.

1Which model is cheaper overall: Z.ai: GLM 5.1 or Tencent: Hy4?

At base pricing, Z.ai: GLM 5.1 costs $1.4/1M input and $4.4/1M output, while Tencent: Hy4 costs $0.417/1M input and $1.2505/1M output. The cheaper option depends on your input-to-output token ratio and whether prompt caching or batch discounts are utilized.

2How does Prompt Caching impact the cost of Z.ai: GLM 5.1 vs Tencent: Hy4?

Z.ai: GLM 5.1 offers a 81.43% read discount ($0.26/1M), whereas Tencent: Hy4 provides a 94.96% read discount ($0.021/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with Z.ai: GLM 5.1 or Tencent: Hy4 to save 50%?

Z.ai: GLM 5.1 supports 50% batch offload discounts for asynchronous 24-hour turnaround tasks. Tencent: Hy4 uses low base on-demand pricing.

4What are the context window limits and tiered pricing rules for Z.ai: GLM 5.1 vs Tencent: Hy4?

Z.ai: GLM 5.1 features a 204.8k context window with flat per-token pricing. In comparison, Tencent: Hy4 supports 1,048.576k tokens with flat per-token pricing.