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GLM-5.3-FlashX

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Z.aiReleased Sep 18, 2026z-ai/glm-5.3-flashx
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GLM-5.3-FlashX is Z.ai's high-speed serving variant of GLM-5.3-Flash, delivering inference speeds of up to 200 tokens/s for faster responses. It inherits Flash's 320B-total/18B-active MoE design, native multimodality, hybrid sparse and linear attention architecture, and 1M-token context window. FlashX runs on a purpose-built serving stack (SGLang-based inference engine, W8A8 quantization, mixed INT8/FP8/BF16 cache quantization, and encode-prefill-decode disaggregation), reporting roughly 3x end-to-end throughput over Z.ai's initial baseline on the same hardware. It is suited for interactive coding agents, browser/computer-use loops, visual coding, and other multi-step workflows where latency compounds.

Context
1.05M
Max output
131K
Input /1M
$0.37
Output /1M
$1.25
Blended /1M
$0.59
AcceptsTextImageVideoProducesTextTokenizer GLM

Providers

FastRouter routes your requests to this provider. You can also bring your own key.

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Z.AI
z-ai
Input /1M$0.37
Output /1M$1.25
Context1.05M
Max output131K
Latency—
Throughput—
Supports tool callingSupports structured (JSON) outputSupports reasoning

Supported parameters

Request parameters you can send with this model.

Parameter
Type
Z.AI
Core (Sampling & basic generation)
max_tokensMaximum tokens to generate.
number
1 to 131072
stopSequences where generation stops.
array
temperatureControls randomness of output.
number
0 to 2
top_kLimits sampling to top K tokens.
number
≥ 0
top_pNucleus sampling threshold.
number
0 to 1
Reasoning (Reasoning Controls)
reasoningProvider-specific reasoning configuration.
string
"low", "high", "max"default: max
Tool Use (Function Calls & Tools)
tool_choiceHow the model should use tools.
string
"auto", "required", "none"
toolsTool/function definitions available to the model.
array
Output & Format (Response Formatting)
response_formatStructured output format configuration.
string
"text", "json_object", "json_schema"

Performance

Median throughput and time to first token per provider over the last week.

Throughput

Latency

Make your first API call

OpenAI-compatible. Point your SDK at FastRouter, or call the API directly.

Full API docs
Replace <FASTROUTER_API_KEY> with your key · Get your key →Install
OpenAI SDKHTTP
from openai import OpenAI
client = OpenAI(
base_url="https://api.fastrouter.ai/api/v1", # FastRouter base URL
api_key= "<FASTROUTER_API_KEY>", # Replace with your FastRouter API key
)
completion = client.chat.completions.create(
model="z-ai/glm-5.3-flashx", # Replace with your model ID
messages=[
{ "role": "user", "content": "What is the meaning of life?" }
]
)
print(completion.choices[0].message.content)

Frequently asked questions

More models from Z.ai

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GLM-5.3-Flashz-ai/glm-5.3-flash

GLM-5.3-Flash is Z.ai’s flagship natively multimodal GLM-5-series model with a 1M-token context window, accepting text plus images and video and producing text outputs. It targets fast, high-quality general and coding assistance with strong reasoning at “flash” latency and is released as open weights under the MIT license.

Model scores sourced from ArtificialAnalysis