OpenAI: GPT-4.1 Nano vs Z.ai: GLM 4.7 Flash
A side-by-side comparison of OpenAI: GPT-4.1 Nano ($0.35 / 1M tokens) and Z.ai: GLM 4.7 Flash ($0.21 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| OpenAI: GPT-4.1 Nano | Z.ai: GLM 4.7 Flash | |
|---|---|---|
| Provider | OpenAI | Z.ai |
| Input | $0.35 / 1M tokens | $0.21 / 1M tokens |
| Output | $1.40 / 1M tokens | $1.40 / 1M tokens |
| Cache read | $0.11 / 1M tokens | - |
| Web search | $35.00 / 1K searches | - |
| Context window | 1,047,576 | 200,000 |
| Max output | 942,818 | 117,964 |
| Input | image, text, file | text |
| Output | text | text |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Apr 14, 2025 | Jan 19, 2026 |
Key differences
- Z.ai: GLM 4.7 Flash is 40% cheaper on input tokens.
- OpenAI: GPT-4.1 Nano reads 5.2× more context (1,047,576 tokens).
- Only Z.ai: GLM 4.7 Flash supports reasoning effort control.
- A request with 1,000 input and 500 output tokens costs $0.00105 with OpenAI: GPT-4.1 Nano and $0.000912 with Z.ai: GLM 4.7 Flash.
In depth
OpenAI: GPT-4.1 Nano is made by OpenAI, and Z.ai: GLM 4.7 Flash is made by Z.ai. Both are text generation models, so they sit in the same broad category and are aimed at the same kind of work: chat completions, extraction, classification, summarisation and tool driven flows. The main practical difference is where each one comes from and what each provider optimises for, with OpenAI's model leaning on the GPT-4.1 family lineage and Z.ai's model leaning on the GLM line.
The biggest structural difference is the context window. GPT-4.1 Nano accepts up to 1,047,576 tokens, which is roughly five times what GLM 4.7 Flash accepts at 200,000 tokens. That matters if you are feeding in long documents, large codebases or long conversation histories in a single call. Modalities also differ: GPT-4.1 Nano accepts image, text and file input and returns text, while GLM 4.7 Flash accepts text only and returns text. If your input includes images or files, only one of these two will work directly. On reasoning, GLM 4.7 Flash is the one that exposes reasoning behaviour, and its parameter list includes reasoning and include_reasoning, which GPT-4.1 Nano does not list. On price, GLM 4.7 Flash is the cheaper option for input, while output pricing is about the same for both. Check the live price table on this page for the current numbers.
For most day to day tasks, the choice comes down to input shape and context size. If you are sending screenshots, PDFs or other files, or if your prompt regularly runs into hundreds of thousands of tokens, GPT-4.1 Nano is the natural pick because it is the only one of the two that accepts those modalities and the only one with the larger window. If your input is plain text and fits comfortably inside 200,000 tokens, GLM 4.7 Flash is a reasonable default, especially when you want reasoning output or the extra sampling controls it exposes, such as top_k, min_p, repetition_penalty, logit_bias and logprobs. Both support tools, tool_choice, structured_outputs and response_format, so function calling and JSON shaped output are available on either side.
Calling either model through api14 works the same way because the API is OpenAI compatible. You point your client at the api14 base URL, use your api14 key, and set the model field to the id you want. Switching between them is a one line change: use openai/gpt-4.1-nano for the OpenAI model, or z-ai/glm-4.7-flash for the Z.ai model. The request and response shapes stay the same, so existing code that reads choices[0].message.content keeps working. The one thing to watch is parameters: GPT-4.1 Nano uses max_completion_tokens, while GLM 4.7 Flash uses max_tokens, so adjust that field when you switch if you set a token limit.
There are still cases where the other model wins. If you need reasoning traces or fine grained sampling control, GLM 4.7 Flash is the better fit even when your text fits in its window. If you need image or file input, or a very large context, GPT-4.1 Nano is the better fit even though its input pricing is higher. Pick based on the input you actually have and the output behaviour you actually need, then let the live price table settle any remaining tie.
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "openai/gpt-4.1-nano" to "z-ai/glm-4.7-flash" and prompts, streaming and tools keep working.
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-flash",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
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