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GLM-5.3 Flash

Budget

by Z.ai (Zhipu AI)

GLM-5.3 Flash is not a cheaper GLM-5.3. It is a different model, released August 26, 2026, and the first natively multimodal member of the GLM-5 family: text, image, and video in one stack rather than a vision head bolted onto a text model. Architecturally it is a 320 billion parameter mixture-of-experts activating roughly 18 billion per token across 45 layers, with hybrid linear and sparse attention (IndexPool and mHC) and a 30 trillion token multimodal pretrain. Z.ai cites roughly 3.0x less attention compute and a 4.4x smaller KV cache than text GLM-5.3. Context is 1 million tokens, weights are MIT licensed on Hugging Face at zai-org/GLM-5.3-Flash, and the model ran on OpenCode and OpenRouter under the stealth id ox-alpha before launch. Pricing is the headline and also the trap: list is $0.15 per million input tokens, $0.03 cached, and $0.50 output, roughly a tenth of the $1.40 input rate on text GLM-5.3, but a 50 percent launch promotion runs at $0.075/$0.25 through September 9, 2026 at 16:00 UTC. Budget the list rate. On the self-reported table the movement is concentrated in agentic work: DeepSWE 63.4 against GLM-5.2 at 46.2, AutomationBench 48.8 against 26.2, Toolathlon 78.4 against 59.9. Terminal Bench 2.1 at 84.3 is a 3.3 point gain and HLE with tools at 55.3 against 54.7 is a wash. On vision it leads DeepSeek V4 Flash Vision Exp on Chartography (78.0 to 64.3) and OfficeQA-Pro (62.4 to 57.9), and it loses BabyVision to Gemini 3.7 Flash 53.4 to 70.9. One operational constraint: thinking cannot be turned off, since thinking.type accepts enabled only.

Input Price

$0.15

per 1M tokens

Output Price

$0.50

per 1M tokens

Context Window

1.0M

tokens

Released

2026-08

Open source

Capabilities

textvisionvideotool-usecodereasoning

Key Strengths

  • First natively multimodal GLM-5: text, image, and video input
  • MIT weights at 18B active parameters with a 1M context window
  • List $0.15/$0.50, roughly a tenth of text GLM-5.3 on input
  • DeepSWE 63.4 and AutomationBench 48.8, up 17.2 and 22.6 on GLM-5.2
  • Roughly 3.0x less attention compute and a 4.4x smaller KV cache than GLM-5.3
  • 3x the usable Coding Plan quota versus GLM-5.3

Best For

  • Multimodal coding and computer-use loops at flash pricing
  • Chart, document, and video understanding at high volume
  • Self-hosted multimodal agents on MIT terms
  • Long-context agentic pipelines where GLM-5.3 is too expensive per call

Benchmark Scores

BenchmarkScoreDescription
Humanity's Last Exam (tools)55.3Multidisciplinary expert-level reasoning with tool access

Scores sourced from public benchmark datasets. See full benchmark leaderboard for all models.

Pricing Details

Input tokens

$0.15

per 1M tokens

Output tokens

$0.50

per 1M tokens

Estimated cost per 1K requests

$0.40

~1K input + ~500 output tokens avg

Prices are subject to change. Check the official documentation for current pricing. See the cost calculator for detailed estimates.

Open Source Model

GLM-5.3 Flash is free to download and self-host under the MIT. Hosted API pricing varies by provider (e.g., Together, Fireworks, Groq). See our open source LLM guide for deployment options.

Related Models

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