GLM 5.3 Flash

Z.aiReleased Aug 26, 2026

GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks.

Input, per 1M tokens: $0.18$0.17 for holders
Output, per 1M tokens: $0.60$0.55 for holders
Context: 1M tokens
Tokens this week: None yet

Price

Agents pay these prices from their AI budget. $BINF holders pay up to 8% less for the credit they buy.

Charge	Agents	Holders	Per
Inputper 1M tokens	$0.18	$0.17	per 1M tokens
Outputper 1M tokens	$0.60	$0.55	per 1M tokens
Cached inputper 1M tokens	$0.036	$0.033	per 1M tokens

Price history

What an agent paid per million tokens, by day.

Unchanged since Sep 29, 2026: $0.18 in and $0.60 out per million tokens.

Usage through bInference

Every call our agents make to this model, by day. Counts only: no prompt or answer is stored.

Last 7 days: 0
Last 30 days: 0
All time: 0

InputOutputReasoning

Where it runs

The hosts serving this model now, and how often each answered over the last day.

Use it

Two settings: our address and your agent’s key. The model is set in each call.

import OpenAI from "openai";const client = new OpenAI({  baseURL: "https://binference.io/api/v1",Address  apiKey: process.env.BINF_API_KEY,Key});const reply = await client.chat.completions.create({  model: "z-ai/glm-5.3-flash",  messages: [{ role: "user", content: "Summarize today's trades" }],  max_tokens: 1024,});

curl https://binference.io/api/v1/chat/completions \Address  -H "Authorization: Bearer $BINF_API_KEY" \Key  -H "Content-Type: application/json" \  -d '{    "model": "z-ai/glm-5.3-flash",    "messages": [{ "role": "user", "content": "Hello" }],    "max_tokens": 1024  }'

Questions

Agents

Holders

Inputper 1M tokens

$0.18

$0.17

per 1M tokens

Outputper 1M tokens

$0.60

$0.55

per 1M tokens

Cached inputper 1M tokens

$0.036

$0.033

per 1M tokens

Host	Answered, last day	Context
OpenInferenceFp4fp4, answering	98.5%	1M
Relace, answering	99.7%	1M
Sail ResearchUSfp8, answering	99.6%	1M
DeepInfraFp4fp4, answering	99.7%	1M
NovitaFp8fp8, answering	98.9%	1M
InferenceNetFp4fp4, having trouble	99.2%	1M
GMICloudFp8fp8, answering	99.2%	1M
AtlasCloudFp8fp8, answering	97.2%	1M
DecartFp4fp4, answering	99.1%	1M
StreamLakeFp8fp8, answering	96.8%	1M
PhalaFp8fp8, answering	98.9%	1M
Near AIFp8fp8, answering	98.1%	1M
Io NetFp8fp8, answering	97%	262K
InceptronFp8fp8, answering	97.1%	1M
ModalNvfp4nvfp4, answering	99.7%	1M
BaseTenFp8fp8, answering	99.6%	1M
CrusoeFp4fp4, answering	99.7%	1M
CoreWeaveNvfp4nvfp4, answering	99.7%	1M
Fireworks, answering	99.1%	1M
Friendli, answering	97.2%	1M
SiliconFlowFp8fp8, answering	98.6%	1M
DigitalOcean, answering	99.7%	1M
Together, answering	99.8%	1M
Reka, answering	99.8%	262K
ParasailFp8fp8, answering	99.6%	1M
BaseTenFp8fp8, answering	99.6%	1M
Venice, answering	98.8%	1M
Z.AIFp8fp8, answering	99.3%	1M
MorphFp8fp8, answering	97.8%	1M
NextBitFp8fp8, answering	99.9%	1M
FireworksUS, answering	99.2%	1M
Cloudflare, answering	98.9%	1M
Wafer, answering	99.8%	1M

Host

Answered, last day

Context

OpenInferenceFp4fp4

98.5%

Relace

99.7%

Sail ResearchUSfp8

99.6%

DeepInfraFp4fp4

99.7%

NovitaFp8fp8

98.9%

InferenceNetFp4fp4

99.2%

GMICloudFp8fp8

99.2%

AtlasCloudFp8fp8

97.2%

DecartFp4fp4

99.1%

StreamLakeFp8fp8

96.8%

PhalaFp8fp8

98.9%

Near AIFp8fp8

98.1%

Io NetFp8fp8

97%

262K

InceptronFp8fp8

97.1%

ModalNvfp4nvfp4

99.7%

BaseTenFp8fp8

99.6%

CrusoeFp4fp4

99.7%

CoreWeaveNvfp4nvfp4

99.7%

Fireworks

99.1%

Friendli

97.2%

SiliconFlowFp8fp8

98.6%

DigitalOcean

99.7%

Together

99.8%

Reka

99.8%

262K

ParasailFp8fp8

99.6%

BaseTenFp8fp8

99.6%

Venice

98.8%

Z.AIFp8fp8

99.3%

MorphFp8fp8

97.8%

NextBitFp8fp8

99.9%

FireworksUS

99.2%

Cloudflare

98.9%

Wafer

99.8%

import OpenAI from "openai";const client = new OpenAI({ baseURL: "https://binference.io/api/v1",Address apiKey: process.env.BINF_API_KEY,Key});const reply = await client.chat.completions.create({ model: "z-ai/glm-5.3-flash", messages: [{ role: "user", content: "Summarize today's trades" }], max_tokens: 1024,});

curl https://binference.io/api/v1/chat/completions \Address -H "Authorization: Bearer $BINF_API_KEY" \Key -H "Content-Type: application/json" \ -d '{ "model": "z-ai/glm-5.3-flash", "messages": [{ "role": "user", "content": "Hello" }], "max_tokens": 1024 }'

GLM 5.3 Flash

Price

Price history

Usage through bInference

Where it runs

Use it

Questions

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GLM 5.3 Flash

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Where it runs

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GLM 5.3 Flash

Price

Price history

Usage through bInference

Where it runs

Use it

Questions

How much does GLM 5.3 Flash cost?

How does my agent use GLM 5.3 Flash?

How much can GLM 5.3 Flash read at once?

What can GLM 5.3 Flash do?

Are my prompts stored?

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GLM 5.3 Flash

Price

Price history

Usage through bInference

Where it runs

Where it runs

Use it

Questions

How much does GLM 5.3 Flash cost?

How does my agent use GLM 5.3 Flash?

How much can GLM 5.3 Flash read at once?

What can GLM 5.3 Flash do?

Are my prompts stored?

More from Z.ai

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Where it runs