We use cookies. Cookies and browser storage keep you signed in and remember your preferences. With your permission we also measure how the site is used. You can any time. See our cookie policy.

New here? See how it works A 1-minute tour of the playground, models and your API key.

Writer: Palmyra X5 vs Z.ai: GLM 5.1

A side-by-side comparison of Writer: Palmyra X5 ($2.10 / 1M tokens) and Z.ai: GLM 5.1 ($4.90 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Writer: Palmyra X5	Z.ai: GLM 5.1
Provider	Writer	Z.ai
Input	$2.10 / 1M tokens	$4.90 / 1M tokens
Output	$21.00 / 1M tokens	$15.40 / 1M tokens
Cache read	-	$0.91 / 1M tokens
Context window	1,040,000	204,800
Max output	8,192	131,072
Input	text	text
Output	text	text
Tool calling
Structured output
Reasoning control
Added	Jan 21, 2026	Apr 7, 2026

Key differences

Writer: Palmyra X5 is 57% cheaper on input tokens.
Z.ai: GLM 5.1 is 27% cheaper on output tokens.
Writer: Palmyra X5 reads 5.1× more context (1,040,000 tokens).
Only Z.ai: GLM 5.1 supports tool calling.
Only Z.ai: GLM 5.1 supports structured JSON output.
Only Z.ai: GLM 5.1 supports reasoning effort control.
A request with 1,000 input and 500 output tokens costs $0.01 with Writer: Palmyra X5 and $0.01 with Z.ai: GLM 5.1.

In depth

Writer: Palmyra X5 is made by Writer, and Z.ai: GLM 5.1 is made by Z.ai. Both are text models in the sense that they take text in and return text out, and both are served through api14 as chat models you can drop into an existing OpenAI-compatible client. Palmyra X5 was released by its provider on 21 January 2026, while GLM 5.1 arrived later, on 7 April 2026. That is the whole of the surface-level similarity; past it, the two are built for fairly different jobs.

The clearest split is context. Palmyra X5 carries a context window of 1,040,000 tokens, which is roughly five times the 204,800 tokens GLM 5.1 accepts. If your prompt is a large codebase, a long contract set, a stack of transcripts or a big batch of retrieved documents, Palmyra X5 is the one that will hold it without chunking. GLM 5.1 gives up ground there but wins on control. It is the only one of the two that exposes tools and tool_choice, structured_outputs and response_format, and reasoning and include_reasoning. It also accepts a much wider parameter set overall, including frequency_penalty, presence_penalty, logit_bias, logprobs, top_logprobs, min_p, repetition_penalty, seed and stop, where Palmyra X5 supports a smaller set (max_tokens, stop, temperature, top_k, top_p). On price, input tokens are cheaper on Palmyra X5 and output tokens are cheaper on GLM 5.1, so the cheaper model depends on whether your workload is prompt-heavy or generation-heavy.

For practical selection, reach for Palmyra X5 when the task is dominated by reading: long-document summarisation, question answering over a large corpus, whole-repo review, or any pipeline where you would otherwise have to chunk and stitch. Its parameter set is small but sufficient for straightforward sampling control. Reach for GLM 5.1 when the task is dominated by doing: function calling, agents that need tools, JSON or schema-constrained output, classification with logprobs, or anything where you want a reasoning pass and fine-grained sampling knobs such as seed for reproducibility. If your workload is mostly output tokens (long generations, many completions), GLM 5.1 is also the cheaper side; if it is mostly input tokens (big prompts, short answers), Palmyra X5 is.

Calling either one through api14 is the same code path. Both are OpenAI-compatible, so you keep your existing client, base URL and request shape, and change only the model id string: "writer/palmyra-x5" for Writer's model, "z-ai/glm-5.1" for Z.ai's. Everything else (messages, temperature, max_tokens, streaming) stays where it is. The one caveat is parameters: if you send tools, response_format, reasoning or seed, those belong to GLM 5.1 and will not be honoured by Palmyra X5, so gate them on the model id rather than sending them unconditionally.

There are still cases where the "wrong" model is the right pick. If you need a million-token prompt and also want tools or structured output, you cannot have both from this pair, and you have to decide which constraint is harder: keep Palmyra X5 and handle tool calls in your own code, or keep GLM 5.1 and retrieve or summarise down to its window. Similarly, if you need reproducible sampling via seed or token-level logprobs for evaluation, GLM 5.1 is the only option here regardless of context size.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "writer/palmyra-x5" to "z-ai/glm-5.1" and prompts, streaming and tools keep working.

Writer: Palmyra X5 details & playground →Z.ai: GLM 5.1 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-5.1",
  "messages": [
    {
      "role": "user",
      "content": "Explain vector databases in two sentences."
    }
  ]
});
console.log(result.choices[0].message.content);

More comparisons

Palmyra X5 vs GLM 5.1: API price, context & features · api14