Verified 2026 API Rates • Prompt Caching & Batch ROI

OpenAI: GPT-4.1 Mini vs GPT-4o mini

Compare real-world API costs for OpenAI: GPT-4.1 Mini ($0.4/$1.6) vs GPT-4o mini ($0.15/$0.6). Calculate Prompt Caching ROI & Batch API savings.

GPT-4o mini saves up to 63% on base input tokens
OpenAI

OpenAI: GPT-4.1 Mini

gpt-4.1-mini
Base Input Rate
$0.40 / 1M
Output Rate
$1.60 / 1M
Prompt Cache Read
$0.10 / 1M (-75%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
1,047.576k tokens
Quality Index (MMLU)
78
OpenAI

GPT-4o mini

gpt-4o-mini
Base Input Rate
$0.15 / 1M
Output Rate
$0.60 / 1M
Prompt Cache Read
$0.075 / 1M (-50%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
128k tokens
Quality Index (MMLU)
82
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 OpenAI: GPT-4.1 Mini and GPT-4o mini:

OpenAI: GPT-4.1 Mini Caching Profile-75% 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.

GPT-4o mini Caching Profile-50% read discount

  • Cached Read Price: $0.075 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
OpenAI: GPT-4.1 Mini$0.40 / $1.60$0.20 / $0.80 (-50%)24 Hours max (typically 30m - 2h)Bulk evaluation, dataset labeling, background summarization
GPT-4o mini$0.15 / $0.60$0.07 / $0.30 (-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.

OpenAI: GPT-4.1 Mini Context Capacity

Provides a 1,047.576k token context window with a maximum output limit of 32.768k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

GPT-4o mini Context Capacity

Provides a 128k token context window with a maximum output limit of 16.384k 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.

OpenAI: GPT-4.1 Mini:$125.25/mo
GPT-4o mini:$56.81/mo
Delta Savings:-$68.44 (55%)
Architecture Verdict:GPT-4o mini delivers 55% lower monthly spend ($68.44/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.

OpenAI: GPT-4.1 Mini:$71.23/mo
GPT-4o mini:$32.61/mo
Delta Savings:-$38.62 (54%)
Architecture Verdict:GPT-4o mini delivers 54% lower monthly spend ($38.62/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).

OpenAI: GPT-4.1 Mini:$227.50/mo
GPT-4o mini:$88.12/mo
Delta Savings:-$139.38 (61%)
Architecture Verdict:GPT-4o mini delivers 61% lower monthly spend ($139.38/mo savings) for this workload profile.
毫秒级实时交互模拟引擎

OpenAI: GPT-4.1 Mini 对比 GPT-4o mini

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%
GPT-4o mini 更便宜

预计每月节省

OpenAI: GPT-4.1 Mini$236.00$2.360// 千次请求
对比
GPT-4o mini$99.00$0.990// 千次请求
Developer FAQs

Frequently Asked Questions: OpenAI: GPT-4.1 Mini vs GPT-4o mini

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

1Which model is cheaper overall: OpenAI: GPT-4.1 Mini or GPT-4o mini?

At base pricing, OpenAI: GPT-4.1 Mini costs $0.4/1M input and $1.6/1M output, while GPT-4o mini costs $0.15/1M input and $0.6/1M 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 OpenAI: GPT-4.1 Mini vs GPT-4o mini?

OpenAI: GPT-4.1 Mini offers a 75% read discount ($0.1/1M), whereas GPT-4o mini provides a 50% read discount ($0.075/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with OpenAI: GPT-4.1 Mini or GPT-4o mini to save 50%?

OpenAI: GPT-4.1 Mini supports 50% batch offload discounts for asynchronous 24-hour turnaround tasks. GPT-4o mini supports 50% batch discounts.

4What are the context window limits and tiered pricing rules for OpenAI: GPT-4.1 Mini vs GPT-4o mini?

OpenAI: GPT-4.1 Mini features a 1,047.576k context window with flat per-token pricing. In comparison, GPT-4o mini supports 128k tokens with flat per-token pricing.