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GLM 5.3 Flash

Runs MCP tools

Z.ai’s small multimodal GLM 5.3, and its high-speed FlashX variant. Both carry a window of over 1M tokens.

Vendor
Z.ai
Released
26 August 2026
Context
1.31M tokens
Input
Text, image, video

Paste a server URL, pick a model, and watch it call your tools in a real conversation. No install.

No server of your own? Leave it blank and use one of the public mock servers.

MCP Evals

Can GLM 5.3 Flash actually complete tasks with your server?

One chat shows the tool calls work. An eval writes real tasks from your tool schemas, has GLM 5.3 Flash drive each one, and reports where it got the wrong answer even though every call succeeded. Pick GLM 5.3 Flash as the driver.

Run evals →See a sample

What GLM 5.3 Flash is

GLM 5.3 Flash is the efficient tier of Z.ai’s GLM 5.3 generation, released on OpenRouter on 26 August 2026, eight days after the full GLM 5.3. It takes text, image and video input and uses the same hybrid sparse-and-linear attention design as the larger model, which is how a Flash-class model carries a 1.31M-token window. FlashX followed on 18 September: the same model served for throughput, up to 200 tokens/s by Z.ai’s figure, with a smaller 1M window.

What Z.ai says

  • Z.ai positions Flash for efficient coding and long-horizon agent tasks.
  • FlashX: inference speeds of up to 200 tokens/s, per Z.ai’s description on OpenRouter.

These are the vendor’s own claims, not measurements of ours. Run the model against your own server to find out whether they hold for your tools.

How it reaches MCP

  • Through an MCP client that translates your tools into OpenAI-style function calls — what happens when you run it here
  • Z.ai’s OpenAI-compatible API, so most MCP client libraries can point at it with a base-URL change
  • OpenRouter, with the id z-ai/glm-5.3-flash or z-ai/glm-5.3-flashx

What to watch for

  • Flash and FlashX do not accept the same request parameters. OpenRouter lists parallel_tool_calls, structured_outputs and seed for Flash and none of the three for FlashX. A client that relies on parallel tool calls or strict structured output will behave differently on FlashX even though the weights are the same.
  • FlashX is about speed, not quality. Pick it over Flash only if latency per turn is the thing you are measuring.
  • Video input is supported, but MCP tool results come back as text or image content. Video never reaches the model through a tool call, so it plays no part in tool testing.

Run the complex-schema mock on Flash, then the same prompt on FlashX. If process_order gets different arguments on the two, check whether your client asks for parallel calls or structured output. That is the parameter gap, not a model difference. All the mock servers →

Variants available here

ModelModel ID
GLM 5.3 Flashz-ai/glm-5.3-flash
GLM 5.3 FlashXz-ai/glm-5.3-flashx

Go deeper

Frequently asked questions

What is the difference between GLM 5.3 Flash and GLM 5.3 FlashX?
Same model, served differently. FlashX is tuned for throughput (up to 200 tokens/s per Z.ai), has a 1M window rather than 1.31M, and on OpenRouter does not accept parallel_tool_calls, structured_outputs or seed.
Does GLM 5.3 Flash support tool calling?
Yes. OpenRouter lists tools and tool_choice for both Flash and FlashX, and Flash also accepts parallel_tool_calls. MCP servers work through any client that translates MCP tools into function calls.
How is GLM 5.3 Flash different from GLM 5.3?
GLM 5.3 is Z.ai’s large reasoning model. Flash is the smaller, faster tier and adds image and video input, which the full GLM 5.3 does not take. Both have a 1.31M window.
Do I need a Z.ai account to try it?
No. Runs here go through MCP Playground’s own OpenRouter routing. You only need your own key when you wire GLM into your product.

Sources

GLM 5.3 Flash for MCP: Specs & Tool Calling — Test Free | MCP Playground