Verified 2026 API Rates • Prompt Caching & Batch ROI

OpenAI: GPT-6.1 Sol vs OpenAI o1

Compare real-world API costs for OpenAI: GPT-6.1 Sol ($2/$10) vs OpenAI o1 ($15/$60). Calculate Prompt Caching ROI & Batch API savings.

OpenAI: GPT-6.1 Sol saves up to 87% on base input tokens
OpenAI

OpenAI: GPT-6.1 Sol

gpt-6.1-sol
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
1,050k tokens
Quality Index (MMLU)
94.5
OpenAI

OpenAI o1

o1
Base Input Rate
$15.00 / 1M
Output Rate
$60.00 / 1M
Prompt Cache Read
$7.50 / 1M (-50%)
Cache Write Surcharge
$0.00 (Free write)
Batch API Discount
-50% Off
Context Window
200k tokens
Quality Index (MMLU)
91.8
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 OpenAI: GPT-6.1 Sol and OpenAI o1:

OpenAI: GPT-6.1 Sol 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.

OpenAI o1 Caching Profile-50% read discount

  • Cached Read Price: $7.500 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
OpenAI: GPT-6.1 Sol$2.00 / $10.00$1.00 / $5.00 (-50%)24 Hours max (typically 30m - 2h)Bulk evaluation, dataset labeling, background summarization
OpenAI o1$15.00 / $60.00$7.50 / $30.00 (-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.

OpenAI: GPT-6.1 Sol 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.

OpenAI o1 Context Capacity

Provides a 200k token context window with a maximum output limit of 100k 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-6.1 Sol:$601.25/mo
OpenAI o1:$5681.25/mo
Delta Savings:-$5080.00 (89%)
Architecture Verdict:OpenAI: GPT-6.1 Sol delivers 89% lower monthly spend ($5080.00/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-6.1 Sol:$348.72/mo
OpenAI o1:$3260.63/mo
Delta Savings:-$2911.90 (89%)
Architecture Verdict:OpenAI: GPT-6.1 Sol delivers 89% lower monthly spend ($2911.90/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-6.1 Sol:$1232.50/mo
OpenAI o1:$8812.50/mo
Delta Savings:-$7580.00 (86%)
Architecture Verdict:OpenAI: GPT-6.1 Sol delivers 86% lower monthly spend ($7580.00/mo savings) for this workload profile.
Motor Interactivo en Tiempo Real

OpenAI: GPT-6.1 Sol vs OpenAI o1

Cálculos de costos mensuales en 3 cargas de trabajo empresariales habituales (RAG, Agente de Código y Limpieza por Lotes):

Live 50ms Engine
Peticiones Mensuales100,000
Tokens de Entrada / Pet.4,000
Tokens de Salida1,000
Tasa de Acierto de Caché70%
Descarga a Batch API0%
OpenAI: GPT-6.1 Sol Más Económico

ahorra aproximadamente

OpenAI: GPT-6.1 Sol$1,268.00$12.680// 1k peticiones
vs
OpenAI o1$9,900.00$99.000// 1k peticiones
Developer FAQs

Frequently Asked Questions: OpenAI: GPT-6.1 Sol vs OpenAI o1

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

1Which model is cheaper overall: OpenAI: GPT-6.1 Sol or OpenAI o1?

At base pricing, OpenAI: GPT-6.1 Sol costs $2/1M input and $10/1M output, while OpenAI o1 costs $15/1M input and $60/1M 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-6.1 Sol vs OpenAI o1?

OpenAI: GPT-6.1 Sol offers a 95% read discount ($0.1/1M), whereas OpenAI o1 provides a 50% read discount ($7.5/1M). High cache hit ratios (>70%) significantly compress the cost delta in agentic and RAG architectures.

3Can I use Batch API with OpenAI: GPT-6.1 Sol or OpenAI o1 to save 50%?

OpenAI: GPT-6.1 Sol supports 50% batch offload discounts for asynchronous 24-hour turnaround tasks. OpenAI o1 supports 50% batch discounts.

4What are the context window limits and tiered pricing rules for OpenAI: GPT-6.1 Sol vs OpenAI o1?

OpenAI: GPT-6.1 Sol features a 1,050k context window with flat per-token pricing. In comparison, OpenAI o1 supports 200k tokens with flat per-token pricing.