Output tokens cost $2.76 per million on glm-5.2 and $4.68 per million on muse-spark-1.1. Input tokens cost $0.79 per million on glm-5.2 and $1.38 per million on muse-spark-1.1. Cached input tokens are billed at $0.20 per million on glm-5.2 and $1.38 per million on muse-spark-1.1. Discounted rates are shown where a promotion is active. Context lengths are 1,000,000 tokens on glm-5.2 and 1,000,000 tokens on muse-spark-1.1. Time to first token (TTFT) measured on AIHubMix is 1.0s on glm-5.2 and 5.9s on muse-spark-1.1. Measured output throughput is 46.1 tok/s on glm-5.2 and 183.7 tok/s on muse-spark-1.1. On the LMArena coding leaderboard glm-5.2 scores 1507 and muse-spark-1.1 scores 1531.
glm-5.2
muse-spark-1.1GLM-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.
Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context window.
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.
glm-5.2: $2.76/M output tokens; muse-spark-1.1: $4.68/M. Use the cost calculator above to estimate your own workload.
muse-spark-1.1: 1531; glm-5.2: 1507 (LMArena coding leaderboard).
glm-5.2: 1.0s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
glm-5.2 accepts 1,000,000 and muse-spark-1.1 accepts 1,000,000 input tokens.
muse-spark-1.1 at 183.7 tok/s and glm-5.2 at 46.1 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
glm-5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs; muse-spark-1.1 accepts text, image, audio and video input and supports thinking and tool calling.
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
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