Verified 2026 API Rates • Prompt Caching & Batch ROI

Cohere: Command A vs Tencent: Hy4

Compare real-world API costs for Cohere: Command A ($2.5/$10) vs Tencent: Hy4 ($0.417/$1.2505). Calculate Prompt Caching ROI & Batch API savings.

Tencent: Hy4 saves up to 83% on base input tokens
Cohere

Cohere: Command A

command-a
Base Input Rate
$2.50 / 1M
Output Rate
$10.00 / 1M
Prompt Cache Read
$2.50 / 1M (-0%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
Not Supported
Context Window
256k tokens
Quality Index (MMLU)
78
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 Cohere: Command A and Tencent: Hy4:

Cohere: Command A Caching Profile-0% read discount

  • Cached Read Price: $2.500 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
Cohere: Command A$2.50 / $10.00Standard on-demand rateInstant real-timeBulk 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.

Cohere: Command A Context Capacity

Provides a 256k token context window with a maximum output limit of 8.192k 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.

Cohere: Command A:$1275.00/mo
Tencent: Hy4:$92.02/mo
Delta Savings:-$1182.98 (93%)
Architecture Verdict:Tencent: Hy4 delivers 93% lower monthly spend ($1182.98/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.

Cohere: Command A:$800.00/mo
Tencent: Hy4:$53.59/mo
Delta Savings:-$746.40 (93%)
Architecture Verdict:Tencent: Hy4 delivers 93% lower monthly spend ($746.40/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).

Cohere: Command A:$3125.00/mo
Tencent: Hy4:$409.66/mo
Delta Savings:-$2715.34 (87%)
Architecture Verdict:Tencent: Hy4 delivers 87% lower monthly spend ($2715.34/mo savings) for this workload profile.
毫秒級即時互動模擬引擎

Cohere: Command A 對比 Tencent: Hy4

針對企業典型三大工程落地形態(RAG 知識庫、Coding Agent 多輪、離線批次清洗)進行精確成本演算:

Live 50ms Engine
月度請求量 (Requests)100,000
單次輸入代幣 (Input Tokens)4,000
單次輸出代幣 (Output Tokens)1,000
Prompt 快取命中率 (Cache Hit)70%
Batch API 批次分流比例0%
Tencent: Hy4 更便宜

預計每月節省

Cohere: Command A$2,000.00$20.000// 千次請求
對比
Tencent: Hy4$180.97$1.810// 千次請求
Developer FAQs

Frequently Asked Questions: Cohere: Command A vs Tencent: Hy4

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

1Which model is cheaper overall: Cohere: Command A or Tencent: Hy4?

At base pricing, Cohere: Command A costs $2.5/1M input and $10/1M 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 Cohere: Command A vs Tencent: Hy4?

Cohere: Command A offers a 0% read discount ($2.5/1M), 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 Cohere: Command A or Tencent: Hy4 to save 50%?

Cohere: Command A does not have a native 50% batch endpoint. Tencent: Hy4 uses low base on-demand pricing.

4What are the context window limits and tiered pricing rules for Cohere: Command A vs Tencent: Hy4?

Cohere: Command A features a 256k context window with flat per-token pricing. In comparison, Tencent: Hy4 supports 1,048.576k tokens with flat per-token pricing.