I like to compare models with a similar score on cost per task and output tokens per task since those measure two things I'm interested in: cost efficiency and token efficiency. Here's how GLM-5.3 compares to other models in a similar score and against GLM-5.2 to save a few clicks for others who care about these metrics:
Model Score Cost / Task Output Tokens / Task
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GLM-5.3 (max) 59.5 $0.68 41,107
GLM-5.2 (max) 53.0 $0.56 32,200
Claude Opus 5 (high) 61.5 $1.52 21,353
GPT-5.6 Sol (max) 60.9 $1.23 16,879
Grok 4.6 (high) 60.9 $0.84 21,735
Kimi K3 (max) 59.7 $0.84 25,474
GPT-5.6 Sol (xhigh) 59.0 $0.87 11,098
Claude Opus 5 (medium) 58.6 $0.98 12,459
Qwen3.8 Max 58.1 $1.13 38,287
Qwen3.8 2.4T A95B 57.7 $0.95 32,472
Claude Opus 4.8 (max) 57.3 $1.65 33,557
GPT-5.6 Sol (high) 57.3 $0.52 7,545
Muse Spark 1.2 (xhigh) 56.8 $0.40 30,430
GPT-5.6 Terra (max) 56.6 $0.51 20,838
GPT-5.5 (xhigh) 56.3 $0.69 16,893
Gemini 3.7 Flash (high) 56.0 $0.40 36,847
Very impressive score for the size, though token use is higher than k3 and far higher than proprietary models, and its price to performance isn't all that far ahead of k3 as a result
Is it worth using these models if I have a claude code subscription already? The appeal of lower cost is nice but I haven't gotten over the switching cost yet.
Use a unified proxy that lets you switch between models seamlessly. We are far from an equilibrium in this market and you will continue to have FOMO no matter who you pick if you go all in on one company
I like to compare models with a similar score on cost per task and output tokens per task since those measure two things I'm interested in: cost efficiency and token efficiency. Here's how GLM-5.3 compares to other models in a similar score and against GLM-5.2 to save a few clicks for others who care about these metrics:
Edited for accuracy and more models.these $/task figures aren't very useful in my experience. it doesn't tell you how well it did the task.
generally I choose models by their intelligence and then personal preference from direct experience.
Muse Spark has a nice balance. not to mentions the Contribs version is old deepseek flash prices.
I found the sweetspot here: GPT-5.6 Sol (high) 57.3 $0.52 7,545
Beware of the benchmarks listed. SciCode and EnterpriseOps for instance: https://shukla.io/blog/2026-08/gym.html
Very impressive score for the size, though token use is higher than k3 and far higher than proprietary models, and its price to performance isn't all that far ahead of k3 as a result
>token use is higher than k3 and far higher than proprietary models
GLM sets effort to max by default historically.
Aa also benchmarked k3 at max
Is it worth using these models if I have a claude code subscription already? The appeal of lower cost is nice but I haven't gotten over the switching cost yet.
Use a unified proxy that lets you switch between models seamlessly. We are far from an equilibrium in this market and you will continue to have FOMO no matter who you pick if you go all in on one company
At least by API usage, they aren't yet lower cost than subscriptions. Not sure about GLM's subscription plans though.
no, at subscription prices claude is a better value than GLM.
They're only a better value if you're paying API rates
Tied for #1 by agentic index (with Opus 5).
...do I take out a double mortgage to buy a 4 Spark cluster?
No, you use openrouter and spend 10% as much as using a proprietary model.
$20k is personal loan territory, not a second mortgage lol
Not with my credit!