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Z.ai: GLM 5.3 Flash

z-ai/glm-5.3-flash

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

Modalities

In / Out Price

50% off

$0.075 / $0.25per 1M

Context

1M

Released

Aug 26, 2026

Providers

This model is hosted by one provider. OpenRouter forwards every request to it directly — no routing decisions to make.

50% off
$0.15$0.075$0.50$0.25$0.03$0.0153.28s27 tps
100.00%

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted Average

Weighted Avg Input Price

$0.02348

/M tokens

Weighted Avg Output Price

$0.2621

/M tokens

GLM 5.3 Flash — Price History

Aug 2600.0060.0120.0180.024$/1M
$0.02348$0.2621$0.075$0.2588.3%100.0%

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput

27tok/s

P50, best across providers

Latency

3.28s

P50, best provider

Throughput
P99
Avg94 tok/s
P95
Avg66 tok/s
P90
Avg56 tok/s
P75
Avg46 tok/s
P50
Avg33 tok/s
E2E Latency
P50
Avg14.47 s
P75
Avg25.17 s
P90
Avg44.30 s
P95
Avg62.95 s
P99
Avg140.39 s

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

99.91%

Availability (3d)

99.62%

Availability over the last 3 days

Aug 24, 12 AM - Aug 27, 12 AM
Availability 99.62%
MonTueWedNow

Availability over the last 24 hours

Aug 26, 12:00 AM4:00 AM8:00 AM12:00 PM4:00 PM8:00 PM12:00 AM60%70%80%90%100%
OpenRouter Availability
99.53%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Aug 26

Activity

Token volume and request traffic to this model over time.

Aug 26350M700M1.05B1.4B
Prompt
704M
Reasoning
4.85M
Completion
3.31M

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.

Quick Start

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

1

Get your API key

Create an API key from your OpenRouter dashboard and set it as an environment variable:

Create API Key
export OPENROUTER_API_KEY=sk-or-v1-...
2

Make your first request

Use z-ai/glm-5.3-flash with the OpenRouter API:

OpenRouter supports reasoning-enabled models that can show their step-by-step thinking process. Use the reasoning parameter in your request to enable reasoning, and access the reasoning_details array in the response to see the model's internal reasoning before the final answer. When continuing a conversation, preserve the complete reasoning_details when passing messages back to the model so it can continue reasoning from where it left off. Learn more about reasoning tokens.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

import { OpenRouter } from "@openrouter/sdk";
const openrouter = new OpenRouter({
apiKey: "<OPENROUTER_API_KEY>"
});
// Stream the response to get reasoning tokens in usage
const stream = await openrouter.chat.send({
chatRequest: {
model: "z-ai/glm-5.3-flash",
messages: [
{
role: "user",
content: "How many r's are in the word 'strawberry'?"
}
],
stream: true
}
});
let response = "";
for await (const chunk of stream) {
const content = chunk.choices[0]?.delta?.content;
if (content) {
response += content;
process.stdout.write(content);
}
// Usage information comes in the final chunk
if (chunk.usage) {
console.log("\nReasoning tokens:", chunk.usage.completionTokensDetails?.reasoningTokens);
}
}

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

3

Enable streaming

Add "stream": true to your request body to receive responses as server-sent events:

curl -N https://openrouter.ai/api/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-d '{
"model": "z-ai/glm-5.3-flash",
"stream": true,
"messages": [
{"role": "user", "content": "Hello"}
]
}'

Endpoint

Sends a request for a model response for the given chat conversation. Supports both streaming and non-streaming modes.

POSThttps://openrouter.ai/api/v1/chat/completions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelz-ai/glm-5.3-flash

Creates a streaming or non-streaming response using the OpenAI Responses API format.

Docs
POSThttps://openrouter.ai/api/v1/responses
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelz-ai/glm-5.3-flash

Creates a message using the Anthropic Messages API format. Supports text, images, PDFs, tools, and extended thinking.

Docs
POSThttps://openrouter.ai/api/v1/messages
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelz-ai/glm-5.3-flash

Parameters

NameTypeDefaultDescription
reasoningmapControls reasoning behavior for models that support thinking tokens, including whether reasoning is enabled, the reasoning effort, maximum reasoning tokens, and whether reasoning is excluded from the response.
max_tokensintegerThis sets the upper limit for the number of tokens the model can generate in response.
temperaturefloat1This setting influences the variety in the model's responses.
top_pfloat0.95This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
toolsarrayTool calling parameter, following OpenAI's tool calling request shape.
tool_choicestring or objectControls which (if any) tool is called by the model.
top_kinteger0This limits the model's choice of tokens at each step, making it choose from a smaller set.
response_formatmapForces the model to produce specific output format.

Frequently asked questions

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