Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
Workload (per month)
OpenAI: GPT-5 Codex (batch)
Pareto 26.9
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$147
$338
OpenAI: GPT-5 Codex (batch) saves $191
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$125
$375
OpenAI: GPT-5 Codex (batch) saves $250
Coding / tool-using agent
2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens)
$135
$390
OpenAI: GPT-5 Codex (batch) saves $255
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$80.00
$245
OpenAI: GPT-5 Codex (batch) saves $165
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$36.25
$133
OpenAI: GPT-5 Codex (batch) saves $96.25
Capabilities side by side
Capability
OpenAI: GPT-5 Codex (batch)
Pareto 26.9
What it lets you do
Tool / function calling
✓ Yes
✓ Yes
call your APIs and run agent loops
Structured output (JSON schema)
✓ Yes
✓ Yes
return JSON that validates against your schema
Reasoning / thinking mode
✓ Yes
—
spend extra tokens thinking before answering hard problems
Image input
✓ Yes
✓ Yes
read screenshots, charts and scanned pages
Audio input
—
—
take speech or audio directly
File / PDF input
—
—
accept documents without your own parsing step
Image output
—
—
generate images, not just text
Built-in web search
✓ Yes
—
answer from live web results
Seed (reproducible sampling)
✓ Yes
—
repeat a generation for tests and evals
Log-probabilities
—
—
read token confidence for classification and scoring
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
OpenAI: GPT-5 Codex (batch): price unchanged since we started tracking it on 2026-08-07.
Pareto 26.9: price unchanged since we started tracking it on 2026-10-14.
Which should you choose?
Choose OpenAI: GPT-5 Codex (batch) if…
cost matters at scale — it is 54% cheaper on a typical 3:1 input/output mix ($147 vs $338 a month for 50,000 support chats)
you need to fit long inputs in one request — 400K tokens is roughly 600 pages, against 393
you need reasoning / thinking mode — to spend extra tokens thinking before answering hard problems; Pareto 26.9 does not advertise it
you need built-in web search — to answer from live web results; Pareto 26.9 does not advertise it
you need seed (reproducible sampling) — to repeat a generation for tests and evals; Pareto 26.9 does not advertise it
Choose Pareto 26.9 if…
you want the newer model — released 2026-10-13, 13 months after the other
Frequently asked questions
Is OpenAI: GPT-5 Codex (batch) better than Pareto 26.9?
Neither wins outright: OpenAI: GPT-5 Codex (batch) is the pick when cost matters at scale, Pareto 26.9 when you want the newer model. In short: OpenAI: GPT-5 Codex (batch) when cost matters at scale, you need to fit long inputs in one request, you need reasoning / thinking mode, you need built-in web search, you need seed (reproducible sampling); Pareto 26.9 when you want the newer model.
Which is cheaper, OpenAI: GPT-5 Codex (batch) or Pareto 26.9?
OpenAI: GPT-5 Codex (batch) is cheaper: $1.72 vs $3.75 per 1M tokens at a typical 3:1 input/output mix, 54% less. For 50,000 support conversations a month that is $147 against $338.
How much do OpenAI: GPT-5 Codex (batch) and Pareto 26.9 cost per million tokens?
OpenAI: GPT-5 Codex (batch) costs $0.63 per 1M input tokens and $5.00 per 1M output tokens; Pareto 26.9 costs $2.50 input and $7.50 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, OpenAI: GPT-5 Codex (batch) or Pareto 26.9?
OpenAI: GPT-5 Codex (batch): 400K tokens, about 600 pages, against 262K (about 393 pages) for Pareto 26.9.
Do OpenAI: GPT-5 Codex (batch) and Pareto 26.9 support function calling and JSON output?
GPT-5-Codex is a specialized version of GPT-5 optimized for software engineering and coding workflows. It is designed for both interactive development sessions and long, independent execution of complex engineering tasks....
Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.