Compare GLM 5.2 from Z.AI and Groq Llama 4 Scout 17B 16e Instruct from Llama on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
GLM 5.2
Groq Llama 4 Scout 17B 16e InstructGLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow engineering standards more consistently, and complete the full development workflow from requirements to multi-platform deployment in a single task.
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Daily traffic served through AIHubMix — how demand for each model is trending.
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.
Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
Groq Llama 4 Scout 17B 16e Instruct: $0.366/M output tokens; GLM 5.2: $3.9438/M. Use the cost calculator above to estimate your own workload.
GLM 5.2: 1509; Groq Llama 4 Scout 17B 16e Instruct: 1362 (LMArena coding leaderboard).
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