GLM-5.3 Flash
A large language model in the GLM series developed by Zhipu AI, belonging to the Flash (lightweight and fast) variant. The model features code comprehension and repair capabilities.
Core Facts
GLM-5.3 Flash's capabilities are on par with Anthropic's Opus 4.8, but its inference cost is only a fraction of the latter's.
Zhipu AI has launched the GLM-5.3 Flash lightweight model.
GLM 5.3 Flash's input price is only $0.15 per million tokens and output is $0.50, making it approximately one-twentieth to one-thirtieth the price of GPT-5.
Timeline (last 90 days)
According to user measurements, GLM-5.3 High Speed generates at about 493 tokens per second, more than twice the peak of GLM-5.3 Flash.
If GLM is used to generate 10 drafts and the best one is selected, the result would be extremely close to Opus 5.5, while still being 20 times cheaper.
GLM 5.3 Flash's input price is only $0.15 per million tokens and output is $0.50, making it approximately one-twentieth to one-thirtieth the price of GPT-5.
With two to three attempts, GLM-5.3 Flash scored 82%, which is within the margin of error of GPT-5.6 Luna's 81%.
Under the condition of only one attempt per task, GLM-5.3 Flash scored 85%.
The domestic chip route is an important enabler of GLM-5.3 Flash's 1/100 pricing, as freedom from dependence on imported computing power allows for a redesigned inference cost structure.
GLM-5.3 Flash achieved nearly 20% weekly token call share on the OpenRouter platform, ranking first among all models.
GLM-5.3 Flash relies entirely on domestically produced chips for training and inference, without depending on overseas AI chips such as those from NVIDIA.
The content creator recommends a primary-plus-secondary model combination strategy: retaining flagship models such as GPT for critical delivery tasks, and using high cost-performance models such as GLM-5.3 Flash for batch, repetitive, trial-and-error tasks.
According to a content creator's hands-on testing, GLM-5.3 Flash scored close to Claude Opus 4.8 on the Terminal Bench 2.1 complex terminal task test.
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All Facts (12)
GLM-5.3 Flash's capabilities are on par with Anthropic's Opus 4.8, but its inference cost is only a fraction of the latter's.
75%VerifiedZhipu AI has launched the GLM-5.3 Flash lightweight model.
85%Partially VerifiedGLM 5.3 Flash's input price is only $0.15 per million tokens and output is $0.50, making it approximately one-twentieth to one-thirtieth the price of GPT-5.
65%UnverifiedAccording to user measurements, GLM-5.3 High Speed generates at about 493 tokens per second, more than twice the peak of GLM-5.3 Flash.
50%UnverifiedThe domestic chip route is an important enabler of GLM-5.3 Flash's 1/100 pricing, as freedom from dependence on imported computing power allows for a redesigned inference cost structure.
50%UnverifiedGLM-5.3 Flash relies entirely on domestically produced chips for training and inference, without depending on overseas AI chips such as those from NVIDIA.
50%UnverifiedThe content creator recommends a primary-plus-secondary model combination strategy: retaining flagship models such as GPT for critical delivery tasks, and using high cost-performance models such as GLM-5.3 Flash for batch, repetitive, trial-and-error tasks.
50%UnverifiedGLM-5.3 Flash took first place in the GDPVL AAVR test.
50%UnverifiedAccording to a content creator's hands-on testing, GLM-5.3 Flash scored close to Claude Opus 4.8 on the Terminal Bench 2.1 complex terminal task test.
50%UnverifiedIn a music player hands-on test, GPT 5.6 Sol cost approximately 44 yuan and took 43 minutes, while GLM-5.3 Flash cost 0.37 yuan and took less time.
50%UnverifiedWith a success rate comparable to DeepSeek V4 Pro, the per-task cost of GLM-5.3 Flash is only one-eighth that of V4 Pro.
50%UnverifiedIf GLM is used to generate 10 drafts and the best one is selected, the result would be extremely close to Opus 5.5, while still being 20 times cheaper.
50%