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Moondream 3.1 vs Nemotron 3.5 Super VL: API price, context & features · api14

Moondream: Moondream 3.1 vs NVIDIA: Nemotron 3.5 Super VL

A side-by-side comparison of Moondream: Moondream 3.1 ($1.05 / 1M tokens) and NVIDIA: Nemotron 3.5 Super VL ($0.52 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Moondream: Moondream 3.1	NVIDIA: Nemotron 3.5 Super VL
Provider	Moondream	NVIDIA
Input	$1.05 / 1M tokens	$0.52 / 1M tokens
Output	$8.75 / 1M tokens	$1.75 / 1M tokens
Cache read	-	$0.07 / 1M tokens
Context window	32,000	1,048,576
Max output	4,096	943,718
Input	text, image	text, image, video
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Oct 15, 2026	Oct 15, 2026

Key differences

NVIDIA: Nemotron 3.5 Super VL is 50% cheaper on input tokens.
NVIDIA: Nemotron 3.5 Super VL is 80% cheaper on output tokens.
NVIDIA: Nemotron 3.5 Super VL reads 32.8× more context (1,048,576 tokens).
Only NVIDIA: Nemotron 3.5 Super VL supports tool calling.
Only NVIDIA: Nemotron 3.5 Super VL supports structured JSON output.
A request with 1,000 input and 500 output tokens costs $0.00542 with Moondream: Moondream 3.1 and $0.00140 with NVIDIA: Nemotron 3.5 Super VL.

In depth

Moondream: Moondream 3.1 is a model from Moondream, listed on api14 under the model id moondream/moondream3.1-9b-a2b. NVIDIA: Nemotron 3.5 Super VL comes from NVIDIA and is listed as nvidia/nemotron-3.5-super-vl. Both are text output models in the text category, and both carry a provider release date of 2026-10-15. The practical difference starts with who is behind them and what each was built to handle, since one is a compact vision language model and the other is a much larger multimodal system from NVIDIA.

The capability gap is wide. Moondream 3.1 accepts text and image input and produces text, with a context window of 32,000 tokens. Nemotron 3.5 Super VL accepts text, image and video input, also producing text, and its context window is 1,048,576 tokens, far larger than Moondream's. Nemotron is also the only one of the two that supports tools and structured outputs, and it exposes a much longer parameter list, including frequency_penalty, logit_bias, logprobs, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, tool_choice, tools, top_k and top_logprobs. Moondream's supported parameters are narrower: include_reasoning, max_completion_tokens, max_tokens, reasoning, temperature and top_p. Reasoning support is not a meaningful differentiator between them here. On price, Nemotron is the cheaper option for both input and output.

For a developer choosing between them, the decision usually comes down to scope and cost. If your task is straightforward image plus text work, such as captioning, visual question answering or short document reading, Moondream 3.1 fits comfortably inside its 32,000 token window and keeps the request surface simple. If you need to process video, handle very long documents or long conversation histories, call tools, or force structured output, Nemotron 3.5 Super VL is the one that supports those things, and its million token context means you rarely have to chunk input. Because Nemotron is also cheaper on both input and output, it is the default pick when its extra features are useful, and Moondream is mainly attractive when you want a smaller, simpler model for bounded image tasks.

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 request to the chat completions endpoint with your api14 key, and set the model field to the id you want. Switching between the two is a one line change: use moondream/moondream3.1-9b-a2b for Moondream 3.1, or nvidia/nemotron-3.5-super-vl for Nemotron 3.5 Super VL. Messages, images and other request fields keep the same shape, so you can move an existing integration from one model to the other by editing only that string.

There are still cases where Moondream is the better pick. If your workload is purely image and text, stays within a modest context, and does not need tools or structured outputs, Moondream 3.1 covers it without pulling in capabilities you will not use. It is the leaner choice for simple, well bounded vision tasks, while Nemotron 3.5 Super VL is the better fit whenever video, very long context, tool calling or structured output matters.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "moondream/moondream3.1-9b-a2b" to "nvidia/nemotron-3.5-super-vl" and prompts, streaming and tools keep working.

Moondream: Moondream 3.1 details & playground →NVIDIA: Nemotron 3.5 Super VL 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": "nvidia/nemotron-3.5-super-vl",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

Moondream: Moondream 3.1 vs NVIDIA: Nemotron 3.5 Super VL

Specifications

Key differences

In depth

Switch with one string

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