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Open-weight GLM-5.3 reportedly matches top proprietary LLMs at one-fifth the cost per task
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An independent benchmark claims GLM-5.3 achieves 100% pass rates across coding, data, real-world, security, and tool-use tasks for $0.28 per lap, undercutting Anthropic and OpenAI models on cost.
If the results hold, GLM-5.3 could shift cost-sensitive deployments toward open-weight models without sacrificing reliability. The benchmark’s methodology, real-world tasks, blind rubric scoring, and refusal-aware cost accounting, sets a replicable standard for comparing model economics. Engineers may need to weigh latency trade-offs (16.3s TTFT) against savings.
Written by elseif from the cluster below · every claim links back to a sourceThe three things worth knowing
GLM-5.3 is the first model in the benchmark to achieve 100% pass rates across all five task categories.
Cost per task for GLM-5.3 is $0.28, compared to $1.43 for the next-best proprietary alternative (gpt-5.5).
The benchmark’s refusal-aware cost accounting reveals that models like fable-5 and opus-5 incur zero cost for blocked tasks, skewing per-task averages if excluded.
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