GLM-5.3-Flash on Fireworks AI

GLM-5 · Zhipu AI

Serverless
Open Source

Last refreshed 2026-11-12. Next refresh: weekly.

Why use GLM-5.3-Flash on Fireworks AI?

Fireworks AI offers GLM-5.3-Flash with pay-as-you-go pricing at $0.15/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.

Compare GLM-5.3-Flash across 5 providers to find the best fit for your use case
Input / 1M
$0.15
Output / 1M
$0.50
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install openai
Auth
export FIREWORKS_API_KEY=...
Call
import os
from openai import OpenAI
client = OpenAI(
    api_key=os.environ["FIREWORKS_API_KEY"],
Model ID
accounts/fireworks/models/glm-5p3-flash

Request example

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["FIREWORKS_API_KEY"],
    base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
    model="accounts/fireworks/models/glm-5p3-flash",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Gotchas

  • Use provider model ID "accounts/fireworks/models/glm-5p3-flash", not the LLMReference slug "glm-5.3-flash".
  • Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
  • The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.

Compare GLM-5.3-Flash Across Providers

ProviderInput (per 1M)Output (per 1M)
Z.ai$0.15$0.50
OpenRouter$0.15$0.50
Together AI$0.15$0.50
Fireworks AI$0.15$0.50
Vercel AI Gateway$0.15$0.50

Pricing

TypePrice (per 1M)
Input tokens$0.15
Output tokens$0.50

Capabilities

VisionMultimodalReasoningJSON / Tool useStructured OutputsPrompt Caching

About GLM-5.3-Flash

GLM-5.3-Flash is Z.ai's first native multimodal model in the GLM-5 series. It is a 320B-total / 18B-active Mixture-of-Experts model with a 1M-token context window and 131,072 max output tokens, supporting image, video, and file input plus function calling, tool use, structured outputs, reasoning, and prompt caching. MIT open weights are ungated on Hugging Face at zai-org/GLM-5.3-Flash. Official API model ID: glm-5.3-flash. The same model was previously tested anonymously as ox-alpha; that name is not a separate catalog slug.

Get Started

Model Specs

Released2026-08-26
Parameters320B (18B active)
Context1M
ArchitectureMixture of Experts

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