Verified 2026 API Rates • Prompt Caching & Batch ROI

DeepSeek: DeepSeek V4.1 Flash vs OpenAI: GPT-6.1 Terra

Compare real-world API costs for DeepSeek: DeepSeek V4.1 Flash ($0.022/$0.4) vs OpenAI: GPT-6.1 Terra ($1/$5). Calculate Prompt Caching ROI & Batch API savings.

DeepSeek: DeepSeek V4.1 Flash saves up to 98% on base input tokens
DeepSeek

DeepSeek: DeepSeek V4.1 Flash

deepseek-v4.1-flash
Base Input Rate
$0.02 / 1M
Output Rate
$0.40 / 1M
Prompt Cache Read
$0.004 / 1M (-81.82%)
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-6.1 Terra

gpt-6.1-terra
Base Input Rate
$1.00 / 1M
Output Rate
$5.00 / 1M
Prompt Cache Read
$0.050 / 1M (-95%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
1,050k tokens
Quality Index (MMLU)
87.8
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-6.1 Terra:

DeepSeek: DeepSeek V4.1 Flash Caching Profile-81.82% read discount

  • Cached Read Price: $0.004 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-6.1 Terra Caching Profile-95% read discount

  • Cached Read Price: $0.050 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$0.02 / $0.40Standard on-demand rateInstant real-timeBulk evaluation, dataset labeling, background summarization
OpenAI: GPT-6.1 Terra$1.00 / $5.00$0.50 / $2.50 (-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 943.718k tokens.✓ Flat-rate billing across all prompt sizes up to max context ceiling.

OpenAI: GPT-6.1 Terra Context Capacity

Provides a 1,050k token context window with a maximum output limit of 128k 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:$18.98/mo
OpenAI: GPT-6.1 Terra:$300.63/mo
Delta Savings:-$281.65 (94%)
Architecture Verdict:DeepSeek: DeepSeek V4.1 Flash delivers 94% lower monthly spend ($281.65/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:$13.34/mo
OpenAI: GPT-6.1 Terra:$174.36/mo
Delta Savings:-$161.02 (92%)
Architecture Verdict:DeepSeek: DeepSeek V4.1 Flash delivers 92% lower monthly spend ($161.02/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:$63.80/mo
OpenAI: GPT-6.1 Terra:$616.25/mo
Delta Savings:-$552.45 (90%)
Architecture Verdict:DeepSeek: DeepSeek V4.1 Flash delivers 90% lower monthly spend ($552.45/mo savings) for this workload profile.
毫秒级实时交互模拟引擎

DeepSeek: DeepSeek V4.1 Flash 对比 OpenAI: GPT-6.1 Terra

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 V4.1 Flash 更便宜

预计每月节省

DeepSeek: DeepSeek V4.1 Flash$43.76$0.438// 千次请求
对比
OpenAI: GPT-6.1 Terra$634.00$6.340// 千次请求
Developer FAQs

Frequently Asked Questions: DeepSeek: DeepSeek V4.1 Flash vs OpenAI: GPT-6.1 Terra

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-6.1 Terra?

At base pricing, DeepSeek: DeepSeek V4.1 Flash costs $0.022/1M input and $0.4/1M output, while OpenAI: GPT-6.1 Terra costs $1/1M input and $5/1M 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-6.1 Terra?

DeepSeek: DeepSeek V4.1 Flash offers a 81.82% read discount ($0.004/1M), whereas OpenAI: GPT-6.1 Terra provides a 95% read discount ($0.05/1M). 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-6.1 Terra to save 50%?

DeepSeek: DeepSeek V4.1 Flash does not have a native 50% batch endpoint. OpenAI: GPT-6.1 Terra supports 50% batch discounts.

4What are the context window limits and tiered pricing rules for DeepSeek: DeepSeek V4.1 Flash vs OpenAI: GPT-6.1 Terra?

DeepSeek: DeepSeek V4.1 Flash features a 1,048.576k context window with flat per-token pricing. In comparison, OpenAI: GPT-6.1 Terra supports 1,050k tokens with flat per-token pricing.