OpenAI: GPT-5 Nano (batch) vs Qwen: Qwen3.5-9B (batch)
Neither wins outright: OpenAI: GPT-5 Nano (batch) is the pick when cost matters at scale, Qwen: Qwen3.5-9B (batch) when you generate long outputs in one go.
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 Nano (batch)
Qwen: Qwen3.5-9B (batch)
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$5.88
$17.75
OpenAI: GPT-5 Nano (batch) saves $11.88
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$5.00
$22.90
OpenAI: GPT-5 Nano (batch) saves $17.90
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)
$5.40
$23.40
OpenAI: GPT-5 Nano (batch) saves $18.00
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$3.20
$15.10
OpenAI: GPT-5 Nano (batch) saves $11.90
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$1.45
$8.75
OpenAI: GPT-5 Nano (batch) saves $7.30
Capabilities side by side
Capability
OpenAI: GPT-5 Nano (batch)
Qwen: Qwen3.5-9B (batch)
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
✓ 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
✓ Yes
—
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 Nano (batch): price unchanged since we started tracking it on 2026-08-07.
Qwen: Qwen3.5-9B (batch): price unchanged since we started tracking it on 2026-08-29.
Which should you choose?
Choose OpenAI: GPT-5 Nano (batch) if…
cost matters at scale — it is 64% cheaper on a typical 3:1 input/output mix ($5.88 vs $17.75 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 file / PDF input — to accept documents without your own parsing step; Qwen: Qwen3.5-9B (batch) does not advertise it
you need built-in web search — to answer from live web results; Qwen: Qwen3.5-9B (batch) does not advertise it
you need seed (reproducible sampling) — to repeat a generation for tests and evals; Qwen: Qwen3.5-9B (batch) does not advertise it
Choose Qwen: Qwen3.5-9B (batch) if…
you generate long outputs in one go — up to 236K tokens (about 176,900 words) per response
you want the newer model — released 2026-03-10, 7 months after the other
Frequently asked questions
Is OpenAI: GPT-5 Nano (batch) better than Qwen: Qwen3.5-9B (batch)?
Neither wins outright: OpenAI: GPT-5 Nano (batch) is the pick when cost matters at scale, Qwen: Qwen3.5-9B (batch) when you generate long outputs in one go. In short: OpenAI: GPT-5 Nano (batch) when cost matters at scale, you need to fit long inputs in one request, you need file / PDF input, you need built-in web search, you need seed (reproducible sampling); Qwen: Qwen3.5-9B (batch) when you generate long outputs in one go, you want the newer model.
Which is cheaper, OpenAI: GPT-5 Nano (batch) or Qwen: Qwen3.5-9B (batch)?
OpenAI: GPT-5 Nano (batch) is cheaper: $0.07 vs $0.19 per 1M tokens at a typical 3:1 input/output mix, 64% less. For 50,000 support conversations a month that is $5.88 against $17.75.
How much do OpenAI: GPT-5 Nano (batch) and Qwen: Qwen3.5-9B (batch) cost per million tokens?
OpenAI: GPT-5 Nano (batch) costs $0.03 per 1M input tokens and $0.20 per 1M output tokens; Qwen: Qwen3.5-9B (batch) costs $0.17 input and $0.25 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, OpenAI: GPT-5 Nano (batch) or Qwen: Qwen3.5-9B (batch)?
OpenAI: GPT-5 Nano (batch): 400K tokens, about 600 pages, against 262K (about 393 pages) for Qwen: Qwen3.5-9B (batch).
Do OpenAI: GPT-5 Nano (batch) and Qwen: Qwen3.5-9B (batch) support function calling and JSON output?
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
Qwen3.5-9B is a multimodal foundation model from the Qwen3.5 family, designed to deliver strong reasoning, coding, and visual understanding in an efficient 9B-parameter architecture. It uses a unified vision-language design...