- 1M context
- Reasoning
- Responses API
GLM 5.3 Prime on QuickSilver Pro
GLM 5.3 Prime through one OpenAI-compatible API. Supported features: text input, text output, streaming, reasoning and tool calling.
- 1M context
- 131K max output
- Tools
- Reasoning · on by default
- Streaming
- No JSON Schema output
You pay · input / output per 1M
$2.24 / $7.04
Z.ai list source: docs.z.ai/guides/overview/pricing
At a glance
- Context
- 1M tokens
- Input / 1M
- $2.24
- Output / 1M
- $7.04
- Thinks by default
- Yes
- Max output
- 131K
- Latency · live
- —
Reasoning and complex software engineering.
When is GLM 5.3 Prime the right call?
Curated from catalog capabilities and published prices, not a benchmark.
When to use
Use GLM 5.3 Prime when your application needs these capabilities: text input, text output, streaming, reasoning and tool calling.
- Long documents and codebases, up to 1M tokens of context
- Agents that call tools
- Multi-step reasoning, on by default
- Responses API clients as well as Chat Completions
When to use something else
Choose a different model if your workflow requires capabilities beyond those listed here. Test your workload before committing to a model.
- Output price matters mostGLM 5.3 costs 0.313× this model’s output price and keeps the 1M context.GLM 5.3 $0.60 / $2.20 · 1M
- You need strict JSON Schema outputGLM 5.2 lists JSON Schema output, at 0.313× the output price.GLM 5.2 $0.70 / $2.20 · 1M
- You need image inputGemini 3.5 Flash accepts image input, at 1.087× the output price.Gemini 3.5 Flash $1.275 / $7.65 · 1M
Quickstart (curl)
Get an API key →curl https://api.quicksilverpro.io/v1/chat/completions \
-H "Authorization: Bearer $QSP_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5.3-prime",
"messages": [{"role": "user", "content": "Hello!"}]
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key=os.environ["QSP_KEY"],
)
response = client.chat.completions.create(
model="glm-5.3-prime",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.quicksilverpro.io/v1",
apiKey: process.env.QSP_KEY,
});
const response = await client.chat.completions.create({
model: "glm-5.3-prime",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);curl https://api.quicksilverpro.io/v1/responses \
-H "Authorization: Bearer $QSP_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "glm-5.3-prime",
"input": "Hello!"
}'import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key=os.environ["QSP_KEY"],
)
response = client.chat.completions.create(
model="glm-5.3-prime",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)OpenAI-compatible. One-line migration via base_url.
Gateway behavior
Compatibility notes for this model.
prompt- Prompts up to 1M tokens.
max_tokens- Up to 131K output tokens.
- /v1/chat/completions: Supported
- /v1/responses: Supported
- streaming: Supported
- tools: Supported
- image input: Not listed for this model
- JSON Schema: Not listed for this model
- reasoning: Supported
Where the price comes from
- Provider reference
- $2.80 / $8.80docs.z.ai/guides/overview/pricing
- Catalog verified
- Prompt cache · not compared
- $0.448 read
usage.cost = prompt_tokens × $2.24/1M + completion_tokens × $7.04/1M
FAQ
Common questions
$2.24 input / $7.04 output per million tokens.
1M context tokens and up to 131K output tokens. Input and output must fit within the context window.
APIs: Chat Completions and Responses. Capabilities: text input, text output, streaming, reasoning and tool calling. Use model="glm-5.3-prime" with base_url=https://api.quicksilverpro.io/v1.