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

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

In depth

OpenAI: GPT-6 Sol Pro is a text model from OpenAI, released on 2026-09-22. Z.ai: GLM 5.3 Prime is a text model from Z.ai, released on 2026-09-23. Both are listed on api14 under the text category, and both accept text input and return text output, so at the level of basic shape they are the same kind of product: a hosted model you send a prompt to and get generated text back. The differences show up in what each one accepts alongside that text and in the parameters each one exposes.

The clearest split is in input modalities. GPT-6 Sol Pro accepts files and images in addition to text, while GLM 5.3 Prime accepts text only. If your pipeline needs to hand a model a screenshot, a scanned page, a chart, or a document file, only one of these two can take it. Context length is close enough that it should not drive the decision: GPT-6 Sol Pro lists 1,050,000 tokens and GLM 5.3 Prime lists 1,000,000, which is about the same working room for long documents and long conversations. On parameters, GPT-6 Sol Pro is the only one of the two with structured outputs, and it also exposes max_completion_tokens and verbosity. GLM 5.3 Prime leans the other way, with sampling and inspection controls that GPT-6 Sol Pro does not list: temperature, top_p, top_k, frequency_penalty, presence_penalty, stop, logprobs and top_logprobs. Both support tools, tool choice, reasoning, reasoning effort, response format, seed and include_reasoning, so neither has an exclusive claim on tool calling or reasoning.

For picking between them, start from the input. If the task involves images or files, GPT-6 Sol Pro is the one to call, and there is no workaround on the other side. If you need the response to conform to a schema, GPT-6 Sol Pro is again the natural choice because structured outputs are listed for it and not for GLM 5.3 Prime. If you are tuning generation behavior, GLM 5.3 Prime gives you the knobs: temperature, top_p, top_k, penalties, stop sequences, and log probabilities for inspecting token-level confidence. That makes it the better fit for classification-style calls where you want to read logprobs, for sampling experiments, and for workloads where you want to shape output style directly rather than through a schema. On price, GPT-6 Sol Pro is the cheaper side for input and GLM 5.3 Prime is the cheaper side for output, so the cheaper option depends on your input-to-output ratio; check the live price table on this page for the actual numbers.

Calling either model through api14 works the same way, because the API is OpenAI-compatible. You point your existing OpenAI client at the api14 base URL, send your key, and set the model field to the id you want: "openai/gpt-6-sol-pro" or "z-ai/glm-5.3-prime". Everything else in the request body keeps the shape you already use. Switching between the two is a one-line change to that model id, so you can route a single workload to both and compare results without rewriting your integration. Keep in mind that parameters are not interchangeable across the two: sending temperature or top_p to GPT-6 Sol Pro, or structured outputs to GLM 5.3 Prime, is not supported by the listed parameter sets, so gate those fields on which model id you are calling.

Switch with one string

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

OpenAI: GPT-6 Sol Pro 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);

More comparisons

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