OpenAI: GPT-5.1-Codex-Mini vs Qwen: Qwen3.6 27B
A side-by-side comparison of OpenAI: GPT-5.1-Codex-Mini ($0.88 / 1M tokens) and Qwen: Qwen3.6 27B ($1.58 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| OpenAI: GPT-5.1-Codex-Mini | Qwen: Qwen3.6 27B | |
|---|---|---|
| Provider | OpenAI | Qwen |
| Input | $0.88 / 1M tokens | $1.58 / 1M tokens |
| Output | $7.00 / 1M tokens | $9.45 / 1M tokens |
| Cache read | $0.11 / 1M tokens | - |
| Web search | $35.00 / 1K searches | - |
| Context window | 400,000 | 262,144 |
| Max output | 128,000 | 65,536 |
| Input | image, text | text, image, video |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Nov 13, 2025 | Apr 27, 2026 |
Key differences
- OpenAI: GPT-5.1-Codex-Mini is 44% cheaper on input tokens.
- OpenAI: GPT-5.1-Codex-Mini is 26% cheaper on output tokens.
- OpenAI: GPT-5.1-Codex-Mini reads 1.5× more context (400,000 tokens).
- A request with 1,000 input and 500 output tokens costs $0.00438 with OpenAI: GPT-5.1-Codex-Mini and $0.00630 with Qwen: Qwen3.6 27B.
In depth
OpenAI: GPT-5.1-Codex-Mini is made by OpenAI and is a text output model aimed at code oriented work. Qwen: Qwen3.6 27B is made by Qwen and is also a text output model, with a smaller parameter footprint implied by its name. Both are served through api14 as OpenAI compatible chat models, so from a client integration standpoint they behave the same way. The main difference at a glance is that the OpenAI model was released on 2025-11-13, while the Qwen model has a provider release date of 2026-04-27.
The two models differ most in context length and input modalities. GPT-5.1-Codex-Mini accepts image and text input and has a context window of 400000 tokens, which is the larger of the two. Qwen3.6 27B accepts text, image and video input, so it is the only one of the pair that can take video directly, but its context window is 262144 tokens. Both output text only. On parameters, the Qwen model exposes a broader sampling surface, including temperature, top_p, top_k, min_p, frequency_penalty, presence_penalty, repetition_penalty, logit_bias, logprobs, top_logprobs and stop, while the OpenAI model exposes reasoning controls such as reasoning_effort and verbosity alongside max_completion_tokens. Both support tools, tool_choice, structured_outputs, response_format, seed and include_reasoning, so neither has an exclusive lock on tool calling or structured output.
For practical selection, reach for GPT-5.1-Codex-Mini when the job involves long inputs, large repositories, lengthy documents or multi file context that benefits from the bigger window, and when you want the reasoning effort and verbosity knobs to tune how much thinking the model does. It is also the cheaper of the two on both input and output, so it is the natural default for high volume or cost sensitive workloads. Reach for Qwen3.6 27B when your input includes video, or when you need fine grained sampling control such as temperature, top_p, top_k, min_p, penalties, logit_bias or logprobs for tasks like classification, extraction with constrained decoding, or experiments where you want to inspect token level probabilities. If your pipeline is text and image only and fits inside 262144 tokens, either model can do the job, and the deciding factors become price and the specific parameter set you depend on.
Calling either model through api14 is the same request shape, because the gateway is OpenAI compatible. You point your client at the api14 base URL, send a chat completions request with your messages, tools and other parameters, and change only the model id string. Use "openai/gpt-5.1-codex-mini" for the OpenAI model and "qwen/qwen3.6-27b" for the Qwen model. Everything else, including authentication, the request path and the response format, stays the same, so switching between them is a one line change and you can A/B them behind a config flag.
There are still cases where the Qwen model is the better pick even though the OpenAI model is cheaper and has the larger context. If your input contains video, Qwen3.6 27B is the only one of the two that accepts it. If you rely on sampling parameters that GPT-5.1-Codex-Mini does not list, such as temperature, top_p, top_k, min_p, repetition_penalty, logit_bias or logprobs, then Qwen3.6 27B is the model that exposes them. In those situations the modality or parameter requirement outweighs the price and context advantage, and the Qwen model is the correct call.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "openai/gpt-5.1-codex-mini" to "qwen/qwen3.6-27b" and prompts, streaming and tools keep working.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.chat.completions.create({
"model": "qwen/qwen3.6-27b",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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