Neither wins outright: OpenAI: GPT-5.4 Nano is the pick when you need to fit long inputs in one request, Qwen: Qwen3.5-9B (batch) when cost matters at scale.
| Spec | OpenAI: GPT-5.4 Nano | Qwen: Qwen3.5-9B (batch) |
|---|---|---|
| Provider | OpenAI | Qwen |
| Input price (per 1M tokens) | $0.20 | $0.17 |
| Output price (per 1M tokens) | $1.25 | $0.25 |
| Blended price (3:1 input/output) | $0.46 | $0.19 |
| Cheaper than … of all models we track | 54% | 70% |
| Context window | 400K tokens (~600 pages) | 262K tokens (~393 pages) |
| Larger context than … of all models | 63% | 48% |
| Max output per response | 128K tokens (~96,000 words) | 236K tokens (~176,900 words) |
| Input types | file, image, text | text, image, video |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2026-03-17 | 2026-03-10 |
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-5.4 Nano | Qwen: Qwen3.5-9B (batch) | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $40.00 | $17.75 | Qwen: Qwen3.5-9B (batch) saves $22.25 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $36.50 | $22.90 | Qwen: Qwen3.5-9B (batch) saves $13.60 |
| 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) | $39.00 | $23.40 | Qwen: Qwen3.5-9B (batch) saves $15.60 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $23.50 | $15.10 | Qwen: Qwen3.5-9B (batch) saves $8.40 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $11.25 | $8.75 | Qwen: Qwen3.5-9B (batch) saves $2.50 |
| Capability | OpenAI: GPT-5.4 Nano | 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.
Neither wins outright: OpenAI: GPT-5.4 Nano is the pick when you need to fit long inputs in one request, Qwen: Qwen3.5-9B (batch) when cost matters at scale. In short: OpenAI: GPT-5.4 Nano when 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 cost matters at scale, you generate long outputs in one go.
Qwen: Qwen3.5-9B (batch) is cheaper: $0.19 vs $0.46 per 1M tokens at a typical 3:1 input/output mix, 59% less. For 50,000 support conversations a month that is $17.75 against $40.00.
OpenAI: GPT-5.4 Nano costs $0.20 per 1M input tokens and $1.25 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.
OpenAI: GPT-5.4 Nano: 400K tokens, about 600 pages, against 262K (about 393 pages) for Qwen: Qwen3.5-9B (batch).
Tool calling — OpenAI: GPT-5.4 Nano: yes, Qwen: Qwen3.5-9B (batch): yes. JSON-schema structured output — OpenAI: GPT-5.4 Nano: yes, Qwen: Qwen3.5-9B (batch): yes.
Yes, both accept image input.
No free variant is listed for either; both are pay-per-token.
OpenAI: GPT-5.4 Nano can write up to 128K tokens (about 96,000 words) per response; Qwen: Qwen3.5-9B (batch) up to 236K (about 176,900 words).
OpenAI: GPT-5.4 Nano was listed on 2026-03-17; Qwen: Qwen3.5-9B (batch) on 2026-03-10.
GPT-5.4 nano is the most lightweight and cost-efficient variant of the GPT-5.4 family, optimized for speed-critical and high-volume tasks. It supports text and image inputs and is designed for low-latency...
Full OpenAI: GPT-5.4 Nano specs →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...
Full Qwen: Qwen3.5-9B (batch) specs →