Verified 2026 API Rates • Prompt Caching & Batch ROI

DeepSeek: DeepSeek V3.2 vs Google: Gemini 4 Carbon

Compare real-world API costs for DeepSeek: DeepSeek V3.2 ($0.26/$0.38) vs Google: Gemini 4 Carbon ($2/$10). Calculate Prompt Caching ROI & Batch API savings.

DeepSeek: DeepSeek V3.2 saves up to 87% on base input tokens
DeepSeek

DeepSeek: DeepSeek V3.2

deepseek-v3.2
Base Input Rate
$0.26 / 1M
Output Rate
$0.38 / 1M
Prompt Cache Read
$0.13 / 1M (-50%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
Not Supported
Context Window
163.84k tokens
Quality Index (MMLU)
88
Google

Google: Gemini 4 Carbon

gemini-4-carbon
Base Input Rate
$2.00 / 1M
Output Rate
$10.00 / 1M
Prompt Cache Read
$0.10 / 1M (-95%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
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 DeepSeek: DeepSeek V3.2 and Google: Gemini 4 Carbon:

DeepSeek: DeepSeek V3.2 Caching Profile-50% read discount

  • Cached Read Price: $0.130 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.

Google: Gemini 4 Carbon Caching Profile-95% read discount

  • Cached Read Price: $0.100 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
DeepSeek: DeepSeek V3.2$0.26 / $0.38Standard on-demand rateInstant real-timeBulk evaluation, dataset labeling, background summarization
Google: Gemini 4 Carbon$2.00 / $10.00$1.00 / $5.00 (-50%)24 Hours max (typically 30m - 2h)Offline 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.

DeepSeek: DeepSeek V3.2 Context Capacity

Provides a 163.84k token context window with a maximum output limit of 147.456k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

Google: Gemini 4 Carbon Context Capacity

Provides a 1,048.576k token context window with a maximum output limit of 943.718k 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.

DeepSeek: DeepSeek V3.2:$72.08/mo
Google: Gemini 4 Carbon:$601.25/mo
Delta Savings:-$529.17 (88%)
Architecture Verdict:DeepSeek: DeepSeek V3.2 delivers 88% lower monthly spend ($529.17/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.

DeepSeek: DeepSeek V3.2:$41.30/mo
Google: Gemini 4 Carbon:$348.72/mo
Delta Savings:-$307.42 (88%)
Architecture Verdict:DeepSeek: DeepSeek V3.2 delivers 88% lower monthly spend ($307.42/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).

DeepSeek: DeepSeek V3.2:$223.00/mo
Google: Gemini 4 Carbon:$1232.50/mo
Delta Savings:-$1009.50 (82%)
Architecture Verdict:DeepSeek: DeepSeek V3.2 delivers 82% lower monthly spend ($1009.50/mo savings) for this workload profile.
毫秒级实时交互模拟引擎

DeepSeek: DeepSeek V3.2 对比 Google: Gemini 4 Carbon

针对企业典型三大工程落地形态(RAG 知识库、Coding Agent 多轮、离线批量清洗)进行精确成本演算:

Live 50ms Engine
月度请求量 (Requests)100,000
单次输入 Tokens (Input)4,000
单次输出 Tokens (Output)1,000
Prompt 缓存命中率 (Cache Hit)70%
Batch API 批处理分流比例0%
DeepSeek: DeepSeek V3.2 更便宜

预计每月节省

DeepSeek: DeepSeek V3.2$105.60$1.056// 千次请求
对比
Google: Gemini 4 Carbon$1,268.00$12.680// 千次请求
Developer FAQs

Frequently Asked Questions: DeepSeek: DeepSeek V3.2 vs Google: Gemini 4 Carbon

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

1Which model is cheaper overall: DeepSeek: DeepSeek V3.2 or Google: Gemini 4 Carbon?

At base pricing, DeepSeek: DeepSeek V3.2 costs $0.26/1M input and $0.38/1M output, while Google: Gemini 4 Carbon costs $2/1M input and $10/1M 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 DeepSeek: DeepSeek V3.2 vs Google: Gemini 4 Carbon?

DeepSeek: DeepSeek V3.2 offers a 50% read discount ($0.13/1M), whereas Google: Gemini 4 Carbon provides a 95% read discount ($0.1/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with DeepSeek: DeepSeek V3.2 or Google: Gemini 4 Carbon to save 50%?

DeepSeek: DeepSeek V3.2 does not have a native 50% batch endpoint. Google: Gemini 4 Carbon supports 50% batch discounts.

4What are the context window limits and tiered pricing rules for DeepSeek: DeepSeek V3.2 vs Google: Gemini 4 Carbon?

DeepSeek: DeepSeek V3.2 features a 163.84k context window with flat per-token pricing. In comparison, Google: Gemini 4 Carbon supports 1,048.576k tokens with flat per-token pricing.