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GLM-5.3-Flash

Z.aiReleased Aug 26, 2026z-ai/glm-5.3-flash
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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.

Context
1.31M
Max output
131K
Input /1M
$0.07
Output /1M
$0.25
Blended /1M
$0.12
AcceptsTextImageVideoProducesTextTokenizer GLM

Providers

5 providers serve this model. FastRouter routes each request to the best available one, and you can bring your own key for any of them.

TE
Telnyx
telnyx
Input /1M$0.07
Output /1M$0.25
Context1.31M
Max output131K
Latency—
Throughput—
Supports tool callingSupports structured (JSON) outputSupports reasoning
DeepInfra logo
DeepInfra
deepinfra
Input /1M$0.07
Output /1M$0.25
Context1.31M
Max output131K
Latency—
Throughput—
Supports tool callingSupports structured (JSON) outputSupports reasoning
Together AI logo
Together AI
together
Input /1M$0.15
Output /1M$0.50
Context1.31M
Max output131K
Latency—
Throughput—
Supports tool callingSupports structured (JSON) outputSupports reasoning
Baseten logo
Baseten
baseten
Input /1M$0.15
Output /1M$0.50
Context1.31M
Max output131K
Latency—
Throughput—
Supports tool callingSupports structured (JSON) outputSupports reasoning
Z.AI logo
Z.AI
z-ai
Input /1M$0.15
Output /1M$0.50
Context1.31M
Max output131K
Latency—
Throughput—
Supports tool callingSupports structured (JSON) outputSupports reasoning

Supported parameters

Request parameters you can send with this model.

Core (Sampling & basic generation)

max_tokens
Maximum tokens to generate.
stop
Sequences where generation stops.
temperature
Controls randomness of output.
top_k
Limits sampling to top K tokens.
top_p
Nucleus sampling threshold.

Reasoning (Reasoning Controls)

reasoning
Provider-specific reasoning configuration.

Tool Use (Function Calls & Tools)

tool_choice
How the model should use tools.
tools
Tool/function definitions available to the model.

Output & Format (Response Formatting)

response_format
Structured output format configuration.

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-flash", # 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-FlashXz-ai/glm-5.3-flashx

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.

Compare GLM-5.3-Flash with

Side by side: price per provider, context window, benchmarks and speed.

Model scores sourced from ArtificialAnalysis