GLM 5.3 Flash
A large-scale language model released by Zhipu AI with approximately 320 billion parameters. It features native visual support capabilities and belongs to the flagship tier of the GLM model series.
Core Facts
Timeline (last 90 days)
Zhipu credits are converted based on Tokens, and the flagship model GLM 5.3 is about 3 times more expensive than GLM 5.3 Flash.
Zhipu's anonymous free model OX Alpha was the codename for GLM 5.3 Flash during its beta testing; it is now officially launched, usable on all three tiers, and deducts only about one-third of the credits of the flagship model.
When working with large MoE models such as GLM 5.3 Flash, the Miles team adopted a fully asynchronous RL architecture in which inference and training run on separate GPU groups, with a fresh sandbox for each episode.
MiniMax M3.1 Flash is currently offered only in API form, with weights still to be released later.
The summarization step itself has additional overhead: one call to GLM 5.3 Flash costs about $0.00002, and it only needs to be paid when the history exceeds the configured limit, not for every message.
This test used the Dynamic quantized version released by Unsloth, with a file size of about 93GB.
GLM 5.3 Flash is a model developed by Zai, previously appeared on OpenRouter under the name Oakies EFLA, and has processed trillions of tokens on domestic chips.
A Bilibili uploader used llama.cpp to load the 1-bit quantized version of GLM 5.3 Flash on 4 RTX 3090s, achieving a generation speed of 33.5 tok/s.
In the moral dilemma test, GLM 5.3 Flash refused the instruction to throw disobedient crew members out of the airlock, but after the setting was changed to an all-robot crew it reassessed and accepted.
In the FlappyBit Extreme game generation task, the model thought for about 91000 tokens, inference speed dropped to 15 tok/s, and it finally completed the output at 105000 tokens after about 2 hours.
40 more timeline events
All Facts (20)
The Flash version of the GLM series is positioned as a lightweight model with low latency and low cost.
75%VerifiedZhipu AI officially confirmed that the mysterious codename Ox Alpha model is GLM 5.3 Flash.
75%UnverifiedGPT-6 Astra tends to generate better, more usable versions on the first attempt, with a high first-pass success rate and fast speed; DeepSeek V4.1 Flash improves quality through continuous self-checking and iteration but takes longer
60%UnverifiedRunning GLM 5.3 Flash requires a Mac Studio M5 Ultra with 256 GB of memory, a configuration costing approximately $10,000.
60%UnverifiedZhipu's anonymous free model OX Alpha was the codename for GLM 5.3 Flash during its beta testing; it is now officially launched, usable on all three tiers, and deducts only about one-third of the credits of the flagship model.
50%UnverifiedZhipu credits are converted based on Tokens, and the flagship model GLM 5.3 is about 3 times more expensive than GLM 5.3 Flash.
50%UnverifiedWhen working with large MoE models such as GLM 5.3 Flash, the Miles team adopted a fully asynchronous RL architecture in which inference and training run on separate GPU groups, with a fresh sandbox for each episode.
50%UnverifiedMiniMax M3.1 Flash is currently offered only in API form, with weights still to be released later.
50%UnverifiedThe summarization step itself has additional overhead: one call to GLM 5.3 Flash costs about $0.00002, and it only needs to be paid when the history exceeds the configured limit, not for every message.
50%UnverifiedThis test used the Dynamic quantized version released by Unsloth, with a file size of about 93GB.
50%UnverifiedThe llama.cpp framework has not yet implemented the Vision Tower feature, so GLM 5.3 Flash's multimodal capabilities cannot be enabled locally.
50%UnverifiedGLM 5.3 Flash is a model developed by Zai, previously appeared on OpenRouter under the name Oakies EFLA, and has processed trillions of tokens on domestic chips.
50%UnverifiedThe author considers GLM 5.3 Flash to be a better model than GPT-5 in its own right, with stronger visual processing and better tool calling, particularly crushing GPT-5 in performance during hours-long agentic workflows.
50%UnverifiedGLM 5.3 Flash has approximately 320 billion parameters with 18 billion activated per token, is denser than DeepSeek, and its speed is more suitable for long-running tasks than interactive use.
50%UnverifiedGLM 5.3 Flash's training capability is open to all users.
50%UnverifiedThe company claims that GLM 5.3 Flash delivers outstanding performance on three categories of benchmarks: agentic coding, document analysis, and tool calling.
50%UnverifiedGLM 5.3 Flash provides training support for both vision and text modalities.
50%UnverifiedGLM 5.3 Flash topped the leaderboard, primarily because it excels as a conversational partner, though its drawbacks include occasional context leakage and a tendency to break down when usage exceeds 20%.
50%UnverifiedWhen calling GLM 5.3 Flash via OpenRouter, FP4 quantization should be avoided, as FP8 offers the best balance of speed and cost.
50%Unverifiedox alpha is actually GLM 5.3 Flash and has nothing to do with Google.
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