Verified 2026 API Rates • Prompt Caching & Batch ROI

DeepSeek: DeepSeek V4.1 Flash vs OpenAI: GPT-4.1

Compare real-world API costs for DeepSeek: DeepSeek V4.1 Flash ($0.0507/$0.2028) vs OpenAI: GPT-4.1 ($2/$8). Calculate Prompt Caching ROI & Batch API savings.

DeepSeek: DeepSeek V4.1 Flash saves up to 97% on base input tokens
DeepSeek

DeepSeek: DeepSeek V4.1 Flash

deepseek-v4.1-flash
Base Input Rate
$0.05 / 1M
Output Rate
$0.20 / 1M
Prompt Cache Read
$0.001 / 1M (-98.03%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
Not Supported
Context Window
1,048.576k tokens
Quality Index (MMLU)
89
OpenAI

OpenAI: GPT-4.1

gpt-4.1
Base Input Rate
$2.00 / 1M
Output Rate
$8.00 / 1M
Prompt Cache Read
$0.50 / 1M (-75%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
1,047.576k tokens
Quality Index (MMLU)
78
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 V4.1 Flash and OpenAI: GPT-4.1:

DeepSeek: DeepSeek V4.1 Flash Caching Profile-98.03% read discount

  • Cached Read Price: $0.001 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.

OpenAI: GPT-4.1 Caching Profile-75% read discount

  • Cached Read Price: $0.500 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.
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 V4.1 Flash$0.05 / $0.20Standard on-demand rateInstant real-timeBulk evaluation, dataset labeling, background summarization
OpenAI: GPT-4.1$2.00 / $8.00$1.00 / $4.00 (-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 V4.1 Flash Context Capacity

Provides a 1,048.576k token context window with a maximum output limit of 393.216k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

OpenAI: GPT-4.1 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.

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 V4.1 Flash:$12.81/mo
OpenAI: GPT-4.1:$626.25/mo
Delta Savings:-$613.44 (98%)
Architecture Verdict:DeepSeek: DeepSeek V4.1 Flash delivers 98% lower monthly spend ($613.44/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.

DeepSeek: DeepSeek V4.1 Flash:$7.78/mo
OpenAI: GPT-4.1:$356.13/mo
Delta Savings:-$348.35 (98%)
Architecture Verdict:DeepSeek: DeepSeek V4.1 Flash delivers 98% lower monthly spend ($348.35/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 V4.1 Flash:$55.92/mo
OpenAI: GPT-4.1:$1137.50/mo
Delta Savings:-$1081.58 (95%)
Architecture Verdict:DeepSeek: DeepSeek V4.1 Flash delivers 95% lower monthly spend ($1081.58/mo savings) for this workload profile.
毫秒級即時互動模擬引擎

DeepSeek: DeepSeek V4.1 Flash 對比 OpenAI: GPT-4.1

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%
DeepSeek: DeepSeek V4.1 Flash 更便宜

預計每月節省

DeepSeek: DeepSeek V4.1 Flash$26.64$0.266// 千次請求
對比
OpenAI: GPT-4.1$1,180.00$11.800// 千次請求
Developer FAQs

Frequently Asked Questions: DeepSeek: DeepSeek V4.1 Flash vs OpenAI: GPT-4.1

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

1Which model is cheaper overall: DeepSeek: DeepSeek V4.1 Flash or OpenAI: GPT-4.1?

At base pricing, DeepSeek: DeepSeek V4.1 Flash costs $0.0507/1M input and $0.2028/1M output, while OpenAI: GPT-4.1 costs $2/1M input and $8/1M 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 V4.1 Flash vs OpenAI: GPT-4.1?

DeepSeek: DeepSeek V4.1 Flash offers a 98.03% read discount ($0.001/1M), whereas OpenAI: GPT-4.1 provides a 75% read discount ($0.5/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with DeepSeek: DeepSeek V4.1 Flash or OpenAI: GPT-4.1 to save 50%?

DeepSeek: DeepSeek V4.1 Flash does not have a native 50% batch endpoint. OpenAI: GPT-4.1 supports 50% batch discounts.

4What are the context window limits and tiered pricing rules for DeepSeek: DeepSeek V4.1 Flash vs OpenAI: GPT-4.1?

DeepSeek: DeepSeek V4.1 Flash features a 1,048.576k context window with flat per-token pricing. In comparison, OpenAI: GPT-4.1 supports 1,047.576k tokens with flat per-token pricing.