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DeepSeek V4.1 Flash vs Qwen-Plus: API price, context & features · api14

DeepSeek: DeepSeek V4.1 Flash vs Qwen: Qwen-Plus

A side-by-side comparison of DeepSeek: DeepSeek V4.1 Flash ($0.18 / 1M tokens) and Qwen: Qwen-Plus ($0.91 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	DeepSeek: DeepSeek V4.1 Flash	Qwen: Qwen-Plus
Provider	DeepSeek	Qwen
Input	$0.18 / 1M tokens	$0.91 / 1M tokens
Output	$1.98 / 1M tokens	$2.73 / 1M tokens
Cache read	$0.06 / 1M tokens	$0.18 / 1M tokens
Cache write	-	$1.14 / 1M tokens
Context window	1,048,576	1,000,000
Max output	943,718	32,768
Input	text, image	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Sep 10, 2026	Feb 1, 2025

Key differences

DeepSeek: DeepSeek V4.1 Flash is 80% cheaper on input tokens.
DeepSeek: DeepSeek V4.1 Flash is 27% cheaper on output tokens.
Only DeepSeek: DeepSeek V4.1 Flash supports reasoning effort control.
A request with 1,000 input and 500 output tokens costs $0.00117 with DeepSeek: DeepSeek V4.1 Flash and $0.00228 with Qwen: Qwen-Plus.

In depth

DeepSeek: DeepSeek V4.1 Flash is a text model from DeepSeek, released on 2026-09-10. Qwen: Qwen-Plus is a text model from Qwen, released on 2025-02-01. Both are served through api14 as chat-style models with tool and structured output support, so the choice between them comes down to modality, context and reasoning rather than to a fundamental difference in what kind of API they expose.

The two models are close in context length, with DeepSeek V4.1 Flash at 1,048,576 tokens and Qwen-Plus at 1,000,000 tokens, a difference that is unlikely to decide anything on its own. The clearer split is in input modalities. DeepSeek V4.1 Flash accepts both text and image input, while Qwen-Plus accepts text only. DeepSeek V4.1 Flash also exposes reasoning controls (include_reasoning, reasoning, reasoning_effort) that Qwen-Plus does not list, and it carries a wider parameter surface overall, including frequency_penalty, logit_bias, min_p, parallel_tool_calls, repetition_penalty, top_a and seed alongside the usual sampling knobs. Qwen-Plus supports a smaller but still practical set: temperature, top_p, top_k, presence_penalty, frequency_penalty, logprobs, top_logprobs, stop, seed, response_format, structured_outputs, tools and tool_choice. On price, DeepSeek V4.1 Flash is the cheaper of the two for both input and output.

For most text-only work, either model will do the job, and the deciding factors are cost and control. If you are running high-volume classification, extraction, summarisation or chat where the input is plain text, DeepSeek V4.1 Flash is the cheaper option and gives you more sampling and reasoning parameters to tune. If your pipeline sends screenshots, scanned pages, diagrams or other images alongside text, DeepSeek V4.1 Flash is the one that can take them, since Qwen-Plus is text in and text out. If you want explicit reasoning effort settings, or you rely on parallel tool calls, logit_bias or min_p, those are on the DeepSeek side. Qwen-Plus remains a reasonable pick when you already have prompts and evaluation harnesses tuned to it, when you want a smaller parameter surface to reason about, or when you simply prefer to keep a Qwen model in the stack.

Calling either model through api14 works the same way, because the gateway is OpenAI-compatible. You point your existing OpenAI client at the api14 base URL, send your key, and set the model field. To use DeepSeek V4.1 Flash, set the model id to "deepseek/deepseek-v4.1-flash". To use Qwen-Plus, set it to "qwen/qwen-plus". Everything else in the request body (messages, temperature, max_tokens, tools, response_format and so on) keeps the same shape, so switching between the two is a one-line change in the model id. Parameters that only one side supports, such as reasoning_effort or parallel_tool_calls, should be dropped when you switch to Qwen-Plus, since it does not list them.

There is still a case for Qwen-Plus even though DeepSeek V4.1 Flash is cheaper and accepts images. If your workload is purely text and you have already validated behaviour, latency or output style against Qwen-Plus, there is no requirement to move, and the context windows are close enough that long-document tasks are not a reason to switch on their own. Treat the two as interchangeable at the call site and pick per task: DeepSeek V4.1 Flash when you need image input, reasoning controls or the lower price, Qwen-Plus when text-only output from a Qwen model is what you want.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "deepseek/deepseek-v4.1-flash" to "qwen/qwen-plus" and prompts, streaming and tools keep working.

DeepSeek: DeepSeek V4.1 Flash details & playground →Qwen: Qwen-Plus 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/qwen-plus",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

DeepSeek: DeepSeek V4.1 Flash vs Qwen: Qwen-Plus

Specifications

Key differences

In depth

Switch with one string

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