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OpenAI: gpt-oss-20b vs Qwen: Qwen3.7 Flash

A side-by-side comparison of OpenAI: gpt-oss-20b ($0.11 / 1M tokens) and Qwen: Qwen3.7 Flash ($0.11 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	OpenAI: gpt-oss-20b	Qwen: Qwen3.7 Flash
Provider	OpenAI	Qwen
Input	$0.11 / 1M tokens	$0.11 / 1M tokens
Output	$0.45 / 1M tokens	$0.45 / 1M tokens
Cache read	$0.11 / 1M tokens	$0.02 / 1M tokens
Cache write	-	$0.13 / 1M tokens
Context window	131,072	1,000,000
Max output	117,964	65,536
Input	text	text, image, video
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Aug 5, 2025	Jul 27, 2026

Key differences

Both have about the same input price.
Qwen: Qwen3.7 Flash reads 7.6× more context (1,000,000 tokens).
Only OpenAI: gpt-oss-20b supports structured JSON output.
A request with 1,000 input and 500 output tokens costs $0.000333 with OpenAI: gpt-oss-20b and $0.000333 with Qwen: Qwen3.7 Flash.

In depth

OpenAI: gpt-oss-20b is a text model from OpenAI, released on 2025-08-05. Qwen: Qwen3.7 Flash is a text model from Qwen, released on 2026-07-27. Both are served through api14 under the same OpenAI-compatible surface, so the choice between them comes down to what your task actually needs rather than to any difference in how you connect.

The clearest split is context and input modalities. Qwen3.7 Flash accepts text, image and video input and carries a context window of 1,000,000 tokens, which is the larger of the two. gpt-oss-20b accepts text only and carries a context window of 131,072 tokens. On price the two are about the same for both input and output, so cost is not the deciding factor here. Where gpt-oss-20b stands apart is structured output: it is the one that supports structured outputs, and its parameter list is broader overall, including frequency_penalty, logit_bias, logprobs, min_p, reasoning_effort, repetition_penalty, stop, top_k and top_logprobs alongside the sampling and tool controls both models share. Qwen3.7 Flash supports a smaller set, covering include_reasoning, logprobs, max_tokens, presence_penalty, reasoning, response_format, seed, temperature, tool_choice, tools, top_logprobs and top_p.

For a developer picking between them, the practical rule follows from those facts. If your input is long, or if it includes images or video, Qwen3.7 Flash is the natural fit because it is the only one of the two that accepts those modalities and the only one with the million-token window. If your task is text in and text out and you depend on structured outputs, or on the finer sampling and penalty controls such as logit_bias, min_p, top_k or reasoning_effort, gpt-oss-20b is the better match. Both expose tool calling and reasoning controls, so agent style workloads and reasoning style workloads are not by themselves a reason to prefer one over the other.

Calling either model through api14 works the same way. You point your client at the api14 base URL, send a request in the OpenAI chat completions shape, and set the model field. To use the OpenAI model, set model to "openai/gpt-oss-20b". To use the Qwen model, set model to "qwen/qwen3.7-flash". Nothing else in the request has to change for the basic case: the same messages array, the same headers, the same response parsing. If you rely on parameters that only one side lists, keep that request on that side, since sending an unsupported parameter is the one place the two diverge in practice.

There are still cases where the other model wins. If you have already built around structured outputs and a wide set of sampling controls, switching to Qwen3.7 Flash would mean giving those up, so gpt-oss-20b remains the better pick even for short text tasks. Conversely, if your text prompt is very large, or your pipeline ingests screenshots or clips alongside text, gpt-oss-20b cannot take that input at all, and Qwen3.7 Flash is the only option of the two.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "openai/gpt-oss-20b" to "qwen/qwen3.7-flash" and prompts, streaming and tools keep working.

OpenAI: gpt-oss-20b details & playground →Qwen: Qwen3.7 Flash details & playground →

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/qwen3.7-flash",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

More comparisons

gpt-oss-20b vs Qwen3.7 Flash: API price, context & features · api14