GLM-5.3-Flash

Linas Beliūnas's Substack reconstructs how an anonymous model called "Ox Alpha" appeared on OpenRouter and OpenCode on August 20, 2026, with a 1M-token context and text, image, and video input, and within six days had become the most-used model on OpenRouter at roughly 2.3 times the volume of the next entry. On August The piece highlights that Stripe had agreed to acquire OpenRouter the day before Ox Alpha's appearance, with Stripe CEO Patrick Collison publicly calling it "very impressive," and frames GLM-5.3-Flash as the cheapest model at its Artificial Analysis Intelligence Index score. It credits creation to Zhipu AI operating in

GLM 5.3 Flash launched on August 26, 2026 with MIT-licensed weights on Hugging Face, native image and video input, and a 1M-token advertised context window evaluated at 300K, priced at $0.15 in / $0.50 out per million tokens on the Z.ai API. By contrast, the GLM 5.3 flagship shipped on August 14, 2026 as an API-only 74 The comparison highlights that the two launch tables mostly use different benchmark versions, making most cross-model comparisons invalid: the flagship reports Terminal-Bench 3.0 (28.3) while Flash reports Terminal-Bench 2.1 (84.3). DeepSWE v1.1 is the only shared benchmark, where Flash scores 63.4 versus the flagship'

Z.ai released GLM-5.3-Flash on August 26, 2026, as an open-weight model under the MIT license with 320 billion total parameters and only about 18 billion active parameters per token, designed around the idea of frontier-level capabilities at lower inference cost. The article confirms the model offers a 1-million-token The Medium explainer positions GLM-5.3-Flash as part of a broader shift in the AI model race away from raw parameter counts and toward how much intelligence a model can deliver per unit of compute actually used. It describes Z.ai, formerly known as Zhipu AI, as the creator and frames the model as a frontier-tier sparse

GLM 5.3 Flash is positioned as dramatically cheaper than the GLM 5.3 flagship while delivering close performance: 320B total / 18B active parameters versus 753B / 40B, both with 1M context windows, and API pricing of $0.15 / $0.50 per million tokens for Flash versus $1.40 / $4.40 for the flagship. On Artificial Analysi Contrary to the "Flash = faster" assumption, Artificial Analysis measures output speed at roughly 85 tokens/second for GLM 5.3 versus about 49 tok/s for Flash, with time-to-first-token of 1.46s for Flash versus 1.57s. Flash wins on image understanding, visual coding, browser agents, computer-use agents, and Coding Plan

LLM-Stats ranks GLM-5.3-Flash 17 overall on its composite LLM Stats Score of 50.3 at a blended price of $0.17 per million tokens, placing it between DeepSeek-V4-Flash-0731 and Muse Spark 1.3 on the cost-efficiency frontier. Capability tier breakdowns show Tool Calling at rank 7 of 193 (Top 10%), Reasoning at 16 of 362, Per-benchmark scores sourced from z.ai include GDPval-AA Elo of 1773/3000 (rank 2, Artificial Analysis methodology), CharXiv-R of 0.89/1 (rank 8, with temp=1.0 top_p=0.95 at 256K context), and Terminal-Bench 2.1 results. Performance by conversation depth holds steady around 14.3–14.6 across turns 1 through 2-10 within

BenchLM aggregates verified benchmark coverage for GLM-5.3-Flash with a composite capability score of 66.1/100, a Multimodal & Grounded rank of 10 (noted as "particularly strong for screenshots, documents, charts, and grounded multimodal workflows"), an Agentic rank of 19 of 154 (60.2, 88th percentile, 6 verified bench The aggregator notes 19 of the tracked benchmark slots are empty, and several categories are not measured: Reasoning, Math, Multilingual, and Instruction Following all lack published numbers. Speed and time-to-first-token are not measured, and no comparable first-party hosted API token rate is published, leaving only a

A technical deep dive on the Local AI Zone GitHub Pages blog breaks down GLM-5.3-Flash as a 320B-parameter MoE with 18B active per token, native FP8 inference, a 1,048,576-token context window, and the first natively multimodal model in the GLM-5 series, released on August 26, 2026 with MIT weights on Hugging Face. The The article documents a changelog versus GLM-4.6, GLM-5.2, and GLM-5.3, full benchmark results, training pipeline notes, the vLLM inference recipe, and the developer API surface priced at $0.15/$0.50 per million tokens. It also reconstructs the Ox Alpha identity reveal, noting that the anonymous model topped OpenRouter

Z.ai released GLM 5.3 Flash on August 26, 2026, shipping a 320-billion-parameter mixture-of-experts model that activates only 18 billion parameters per token, with MIT-licensed weights on Hugging Face from day one, according to a release recap on Fello AI. The model is the first natively multimodal release in the GLM-5 API pricing is set at $0.15 per million input tokens and $0.50 per million output tokens, sharply below the $1.40 and $4.40 listed for the GLM 5.3 flagship, and the page notes that the 744B weights for GLM 5.3 itself remain unreleased, with no GLM 5.3 repository yet on Z.ai's Hugging Face organisation. The article, upd