GLM-5.3 (Runware) by LLM Gateway | AI model information

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Model details

GLM-5.3 (Runware)

GLM-5.3 sits within Z AI's GLM-5 line as a fresh foundation built on a new base rather than a direct continuation of its predecessor. Coverage characterizes the architecture as a mixture-of-experts system with roughly 320 billion total parameters and about 18 billion active per token, concentrating compute on a smaller subset of weights for each forward pass. This sparse-activation design points to a model that aims to deliver high-capacity behavior while keeping the per-token inference footprint comparatively lean, an attractive shape for teams that want serious model power without paying the full parameter cost on every request.

In practical terms, GLM-5.3 is positioned for demanding text workloads such as reasoning, coding, and long-context tasks, where maintaining coherence over very large input spans matters. The GLM-5 line has previously drawn attention for an unusually generous usable context window, and this generation continues that emphasis on stable performance across extended sequences. The result is a text-only foundation that fits naturally into agentic and developer-tooling pipelines, including coding assistants and tool-using workflows, while offering the parameter scale and context headroom needed for complex multi-step problem solving.

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Quick Info

Provider: LLM Gateway
Model key: runware/glm-5.3
Release date: Aug 14, 2026
Last updated: Aug 14, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost: $1.20
Output token cost: $4.00

Limits

Output tokens: 131,072 tokens
Context window: 1,000,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about GLM-5.3 (Runware)

LLM Gateway

CoverageBenchmark

An independent engineering review on webscraping.space analyzes GLM-5.3, released August 14, 2026 by Zhipu AI, emphasizing that the model reuses the same 743B-parameter Mixture-of-Experts base as GLM-5.2 with all reported improvements coming from scaled post-training rather than a new architecture or larger parameter c The piece also discusses the delayed open-weights release, which Z.ai staged behind a safety review window rather than publishing immediately as in earlier 5.x releases, framing that choice as a governance question for the open-source community. It adds practitioner perspective on self-hosting cost and the production i

LLM Gateway

CoverageBenchmark

BenchLM.ai, a third-party benchmark aggregator, tracks GLM-5.3 as released on August 14, 2026 by Z.AI with a 1M-token context window and open weights. The page assigns GLM-5.3 a composite capability score of 68.5/100, ranking it 27th of 232 models, with its strongest eligible category being Agentic (8th of 151) and a C The dashboard surfaces 25 source-displayable benchmark rows out of 417 tracked benchmarks and notes that several categories (Reasoning, Math, Multilingual, Multimodal, Instruction Following) are not currently rank-eligible for GLM-5.3. Capability percentiles reported include 95th in Agentic, 91st in Coding, and 84th in