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DeepSeek V4.1 Flash vs Mercury 2: API price, context & features · api14

DeepSeek: DeepSeek V4.1 Flash vs Inception: Mercury 2

A side-by-side comparison of DeepSeek: DeepSeek V4.1 Flash ($0.18 / 1M tokens) and Inception: Mercury 2 ($0.88 / 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	Inception: Mercury 2
Provider	DeepSeek	Inception
Input	$0.18 / 1M tokens	$0.88 / 1M tokens
Output	$1.98 / 1M tokens	$2.63 / 1M tokens
Cache read	$0.06 / 1M tokens	$0.09 / 1M tokens
Context window	1,048,576	128,000
Max output	943,718	50,000
Input	text, image	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Sep 10, 2026	Mar 4, 2026

Key differences

DeepSeek: DeepSeek V4.1 Flash is 80% cheaper on input tokens.
DeepSeek: DeepSeek V4.1 Flash is 24% cheaper on output tokens.
DeepSeek: DeepSeek V4.1 Flash reads 8.2× more context (1,048,576 tokens).
A request with 1,000 input and 500 output tokens costs $0.00117 with DeepSeek: DeepSeek V4.1 Flash and $0.00219 with Inception: Mercury 2.

In depth

DeepSeek: DeepSeek V4.1 Flash is a text model from DeepSeek, released on 10 September 2026. Inception: Mercury 2 is a text model from Inception, released on 4 March 2026. Both are served through api14 as text category models, so neither is a specialist in audio or video generation. The main difference at first glance is age and scope: Mercury 2 has been available longer, while DeepSeek V4.1 Flash is the newer arrival with a much wider set of tunable parameters.

The two differ most in context window and input handling. DeepSeek V4.1 Flash accepts text and image input and produces text output, with a context length of 1,048,576 tokens. Mercury 2 accepts text only and produces text output, with a context length of 128,000 tokens. So DeepSeek V4.1 Flash has the larger context by a wide margin and is the only one of the two that can look at images. DeepSeek V4.1 Flash also exposes a longer parameter list, including frequency and presence penalties, logit bias, logprobs and top logprobs, min_p, top_a, top_k, seed, repetition penalty and parallel tool calls. Mercury 2 supports a smaller set: include_reasoning, max_tokens, reasoning, reasoning_effort, response_format, stop, structured_outputs, temperature, tool_choice and tools. Both support tools and structured outputs, and both expose reasoning controls, so those are not points of separation. The practical split is breadth versus simplicity.

For choosing between them, start with the size of the input. If you are sending long documents, large codebases, lengthy transcripts or multi file context, DeepSeek V4.1 Flash is the natural pick because its context window is far larger. If your task involves screenshots, scanned pages or diagrams alongside text, DeepSeek V4.1 Flash is the only option here that takes image input. If you need fine control over sampling, such as seeds for reproducibility, logprobs for confidence checks or penalties to steer repetition, DeepSeek V4.1 Flash gives you those knobs. Mercury 2 is the leaner choice when your prompts are short to moderate, text only, and you mainly want temperature, reasoning effort, tools and structured outputs. It covers the common production patterns without the extra parameters to reason about. On price, DeepSeek V4.1 Flash is the cheaper of the two on both input and output, so cost sensitive, high volume text work also leans toward it.

Calling either model through api14 works the same way because the API is OpenAI compatible. You point your client at the api14 base URL, send your key, and use the chat completions style request you already use. The only thing that changes between the two is the model id string: use "deepseek/deepseek-v4.1-flash" for DeepSeek V4.1 Flash and "inception/mercury-2" for Mercury 2. Your message array, tool definitions and response format settings carry over unchanged. If you switch from Mercury 2 to DeepSeek V4.1 Flash, you can keep the same request shape and simply add the parameters you want from the larger set. Going the other way, drop any parameters Mercury 2 does not list, such as logprobs or seed, and remove image content from your messages.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "deepseek/deepseek-v4.1-flash" to "inception/mercury-2" and prompts, streaming and tools keep working.

DeepSeek: DeepSeek V4.1 Flash details & playground →Inception: Mercury 2 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": "inception/mercury-2",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

DeepSeek: DeepSeek V4.1 Flash vs Inception: Mercury 2

Specifications

Key differences

In depth

Switch with one string

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