Comparison · OpenAI and Qwen
GPT-5.4 Mini vs Qwen3.8 27B
Listed API prices of GPT-5.4 Mini and Qwen3.8 27B turned into the cost of the same three standard tasks, with speed from our own test requests in the United States and what each provider’s API documentation says about features that break on a switch. Output quality and answer length are not compared.
Calculated impact cost per task and per month
For an L2 task (deep analysis over a 50,000-token document, 3 steps), GPT-5.4 Mini costs $0.133 and Qwen3.8 27B $0.139 at the prices listed in the United States on , so GPT-5.4 Mini is 4.6 % less than Qwen3.8 27B, counting visible output only, without cache discounts or hidden reasoning.
| Task | GPT-5.4 Mini, per task | Qwen3.8 27B, per task | GPT-5.4 Mini, per month | Qwen3.8 27B, per month | GPT-5.4 Mini vs Qwen3.8 27B, per task |
|---|---|---|---|---|---|
| L1Micro-task (classification or strict JSON extraction) | $0.0020per L1 task | $0.0020per L1 task | $29.57per month | $29.20per month | +1.3 % |
| L2Deep analysis over a 50,000-token document | $0.133per L2 task | $0.139per L2 task | $1,938.15per month | $2,032.32per month | −4.6 % |
| L3Agentic coding loop, 15 steps | $1.03per L3 task | $1.09per L3 task | $14,996.02per month | $15,890.64per month | −5.6 % |
Calculated Per month: 20 tasks an hour around the clock, 730 hours.
Prices USD per 1M tokens
| Price | GPT-5.4 Mini | Qwen3.8 27B |
|---|---|---|
| Input, per 1M tokens | $0.750 | $0.800 |
| Output, per 1M tokens | $4.50 | $4.00 |
| Price from | Provider's price list · source page Published | Provider's price list · source page Published |
| Read | · the United States | · the United States |
| Context window | 400,000 tokens | 1,024,000 tokens |
What can I use it for? six common tasks, our data checks
Quality on your task: not measured by Measured Lab yet.
| Task | GPT-5.4 Mini | Qwen3.8 27B |
|---|---|---|
| Answer customer messages | Fits on price and context | — |
| Pull data from invoices and documents with strict JSON and page images | Fits on price and context | — |
| Summarize documents and meetings | Fits on price and context | — |
| Translate content | Fits on price and context | — |
| Chat assistant on your website | Fits on price and context | — |
| Write and review code with tool calls | Fits on price and context | — |
| Tasks it fits | 6 of 6 | — |
Checks of our data for six common tasks: a published price, a context window and answer length for the task and, where the task needs them, strict JSON output, page images and tool calls; prices, cost a month and terms for each model on its model card. Qwen3.8 27B is not in the model picker. Compare models for your own task in the model picker.
Speed in the US Observed our test requests
In our test requests from the United States, the median time to the first answer token was 663 ms for GPT-5.4 Mini (Direct API · OpenAI) and 139 ms for Qwen3.8 27B (Hosted by Cerebras).
| Model and route | Time to first answer token, median | Output speed, median | Answers |
|---|---|---|---|
| GPT-5.4 MiniDirect API · OpenAI | 663 ms range 319 ms–30,568 ms | 156 tokens/s range 47.6 tokens/s–265 tokens/s | 120 answers on 23 dates |
| Qwen3.8 27BHosted by Cerebras | 139 ms range 98 ms–16,848 ms | 610 tokens/s range 199 tokens/s–627 tokens/s | 115 answers on 23 dates |
| Qwen3.8 27BHosted by Groq | 195 ms range 102 ms–1,095 ms | 494 tokens/s range 210 tokens/s–528 tokens/s | 115 answers on 23 dates |
The same short request to every model, sent from a measurement point in the United States; medians of successful answers on at least 2 different dates, latest on . How we measure
What breaks when you switch Published provider documentation
Moving from OpenAI to Qwen, 3 of the 5 features may not carry over, by each provider’s documentation:
- Strict JSON schemas — OpenAI: yes; Qwen: partly. Code that parses answers without checks starts failing where a provider promises only valid JSON, not your schema.
- Streamed tool arguments — OpenAI: yes; Qwen: not stated. An interface that shows arguments as they are written sees nothing until the whole call is ready.
- Cache covers tool definitions — OpenAI: yes; Qwen: not stated. Where the cache does not cover tool definitions, a long tool list is paid as fresh input on every request.
Moving from Qwen to OpenAI: every feature that Qwen’s documentation lists as supported is also listed as supported by OpenAI.
| Feature of the API | OpenAI | Qwen |
|---|---|---|
| Strict JSON schemas | Yes | Partly |
| Parallel tool calls | Yes | Yes |
| Streamed tool arguments | Yes | Not stated |
| Reasoning with tools | Yes | Yes |
| Cache covers tool definitions | Yes | Not stated |
What each provider’s own API documentation says, read ; “not stated” is not the same as “no”. Quotes and sources: what breaks when you switch AI APIs.
Price changes in the last 30 days
- The listed price of Qwen3.8 27B changed on on OpenRouter: input $0.24 → $0.04, output $2.20 → $1.35 per 1M tokens.
- The listed price of Qwen3.8 27B changed on on OpenRouter: input $0.04 → $0.20, output $1.35 → $2.50 per 1M tokens.
- The listed price of Qwen3.8 27B changed on on OpenRouter: input $0.20 → $0.04, output $2.50 → $1.25 per 1M tokens.
- The listed price of Qwen3.8 27B changed on on OpenRouter: input $0.04 → $0.15, output $1.25 → $1.88 per 1M tokens.