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Z.ai: GLM 4.5V vs Z.ai: GLM 4.7

A side-by-side comparison of Z.ai: GLM 4.5V ($2.10 / 1M tokens) and Z.ai: GLM 4.7 ($2.10 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Z.ai: GLM 4.5V	Z.ai: GLM 4.7
Provider	Z.ai	Z.ai
Input	$2.10 / 1M tokens	$2.10 / 1M tokens
Output	$6.30 / 1M tokens	$7.70 / 1M tokens
Cache read	$0.39 / 1M tokens	$0.39 / 1M tokens
Context window	65,536	204,800
Max output	16,384	131,072
Input	text, image	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Aug 11, 2025	Dec 22, 2025

Key differences

Both have about the same input price.
Z.ai: GLM 4.5V is 18% cheaper on output tokens.
Z.ai: GLM 4.7 reads 3.1× more context (204,800 tokens).
Only Z.ai: GLM 4.7 supports structured JSON output.
A request with 1,000 input and 500 output tokens costs $0.00525 with Z.ai: GLM 4.5V and $0.00595 with Z.ai: GLM 4.7.

In depth

Z.ai: GLM 4.5V and Z.ai: GLM 4.7 are both text generation models from Z.ai, offered through api14 under the model ids z-ai/glm-4.5v and z-ai/glm-4.7. They belong to the same GLM family and share a provider, so the choice between them is less about vendor trust and more about the shape of the job you are running. GLM 4.5V was released on 2025-08-11, while GLM 4.7 arrived later, on 2025-12-22.

The clearest split is in context and input handling. GLM 4.7 has a context window of 204800 tokens, which is substantially larger than the 65536 tokens available on GLM 4.5V. GLM 4.5V accepts both text and image input and returns text, so it is the one to reach for when your prompt includes a screenshot, diagram, chart or scanned page. GLM 4.7 accepts text input only. On the parameter side, GLM 4.7 supports structured outputs, which GLM 4.5V does not, and it also exposes logit_bias, min_p and top_a, while GLM 4.5V does not list those. Both models support tools and tool_choice, both support reasoning and include_reasoning, and both accept the common sampling controls such as temperature, top_p, top_k, frequency_penalty, presence_penalty, repetition_penalty, seed, stop, max_tokens and response_format.

For practical work, pick GLM 4.5V when the task involves reading an image alongside text, such as extracting values from a chart, describing a UI mockup or answering questions about a screenshot. Pick GLM 4.7 when the job is text only and either needs a long context, such as summarizing or querying a large document set in one call, or needs structured outputs to get back a reliably shaped JSON object. If you are doing plain text generation with a modest prompt and no schema requirement, either model can serve, and the deciding factors become context length and cost.

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 z-ai/glm-4.5v or z-ai/glm-4.7. Everything else in the request body, such as messages, temperature, max_tokens and tools, keeps the same shape. Switching between the two is therefore a one line change to the model id, which makes it easy to A/B a prompt across both.

There are still cases where GLM 4.5V is the better pick even though GLM 4.7 is newer. If your input includes an image, GLM 4.7 cannot take it at all, so GLM 4.5V is the only option of the two. GLM 4.5V is also the cheaper model on output tokens, while input pricing is about the same across the two, so for output heavy text workloads where the smaller context is enough, GLM 4.5V can be the more economical call.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "z-ai/glm-4.5v" to "z-ai/glm-4.7" and prompts, streaming and tools keep working.

Z.ai: GLM 4.5V details & playground →Z.ai: GLM 4.7 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-4.7",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

More comparisons

GLM 4.5V vs GLM 4.7: API price, context & features · api14