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GPT-6 Sol vs GLM 5.3 Prime: API price, context & features · api14

OpenAI: GPT-6 Sol vs Z.ai: GLM 5.3 Prime

A side-by-side comparison of OpenAI: GPT-6 Sol ($7.00 / 1M tokens) and Z.ai: GLM 5.3 Prime ($9.80 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	OpenAI: GPT-6 Sol	Z.ai: GLM 5.3 Prime
Provider	OpenAI	Z.ai
Input	$7.00 / 1M tokens	$9.80 / 1M tokens
Output	$35.00 / 1M tokens	$30.80 / 1M tokens
Cache read	$0.70 / 1M tokens	$1.96 / 1M tokens
Cache write	$8.75 / 1M tokens	-
Web search	$35.00 / 1K searches	-
Context window	1,050,000	1,000,000
Max output	128,000	131,072
Input	file, image, text	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Sep 22, 2026	Sep 23, 2026

Key differences

OpenAI: GPT-6 Sol is 29% cheaper on input tokens.
Z.ai: GLM 5.3 Prime is 12% cheaper on output tokens.
Only OpenAI: GPT-6 Sol supports structured JSON output.
A request with 1,000 input and 500 output tokens costs $0.02 with OpenAI: GPT-6 Sol and $0.03 with Z.ai: GLM 5.3 Prime.

In depth

OpenAI: GPT-6 Sol is a text model from OpenAI, released on 22 September 2026. Z.ai: GLM 5.3 Prime is a text model from Z.ai, released on 23 September 2026. Both are listed on api14 as text category models, and both accept a prompt and return text, so at the level of basic use they occupy the same slot in your stack. The differences show up in what you can send in, how you steer the output, and what the request costs.

The clearest split is in input modalities. GPT-6 Sol accepts files, images and text, so you can hand it a screenshot, a PDF or a document alongside your instructions. GLM 5.3 Prime accepts text only, which means anything visual or file based has to be converted to text before it reaches the model. On context, the two are close enough that the difference is not worth planning around: GPT-6 Sol lists 1,050,000 tokens and GLM 5.3 Prime lists 1,000,000. Structured outputs are listed for GPT-6 Sol but not for GLM 5.3 Prime, so if you need the model constrained to a schema, that is a point in OpenAI's favour. GLM 5.3 Prime carries a wider set of sampling controls, including temperature, top_p, top_k, frequency and presence penalties, stop sequences and logprobs with top logprobs. Both expose reasoning controls such as reasoning effort and include reasoning, and both support tools, so neither has an exclusive claim there.

For day to day work, pick based on what you are feeding in and what you need back. If your pipeline involves images, uploaded files or mixed media, GPT-6 Sol is the straightforward choice because the other model cannot take those inputs at all. If you need guaranteed schema shaped output, again GPT-6 Sol is the safer call. If your task is pure text and you want fine control over sampling, or you want logprobs for scoring and reranking, GLM 5.3 Prime gives you knobs that GPT-6 Sol does not list. On price, GPT-6 Sol is the cheaper option for input, while GLM 5.3 Prime is the cheaper option for output, so the better deal depends on your ratio of prompt tokens to completion tokens. Long prompts with short answers lean toward GPT-6 Sol, while short prompts with long generations lean toward GLM 5.3 Prime.

Calling either model through api14 works the same way, because the API is OpenAI compatible. You point your existing client at api14, send a chat completions request, and set the model field. To use OpenAI's model, set the model id to openai/gpt-6-sol. To use Z.ai's model, set it to z-ai/glm-5.3-prime. Everything else in the request body stays as it is, apart from parameters that a given model does not support, which you should drop or the request may be rejected. That means you can switch between the two by changing one string, and you can route different requests to different models inside the same application without rewriting your client code.

There are still cases where the text only model is the better pick. If your workload is entirely text, you gain nothing from the file and image support on GPT-6 Sol, and GLM 5.3 Prime's output pricing plus its sampling and logprob controls may suit you better, particularly for generation heavy jobs or for tasks where you want to inspect token level probabilities. Conversely, if you are working with documents or screenshots, or you need structured outputs, GPT-6 Sol remains the one to call.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "openai/gpt-6-sol" to "z-ai/glm-5.3-prime" and prompts, streaming and tools keep working.

OpenAI: GPT-6 Sol details & playground →Z.ai: GLM 5.3 Prime 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": "z-ai/glm-5.3-prime",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

OpenAI: GPT-6 Sol vs Z.ai: GLM 5.3 Prime

Specifications

Key differences

In depth

Switch with one string

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