Z.ai: GLM 5.3 Flash (batch): multimodal specs, pricing, and fit
Z.ai: GLM 5.3 Flash (batch) ranks #10 on the AI Hippo board with a 1.0M context window and $0.06 input / $0.20 output per 1M tokens. Specs, cost math, and how it compares.
The quick read
Z.ai: GLM 5.3 Flash (batch) is the value story of this snapshot: from z-ai, it pairs a 1.0M window with some of the lowest token pricing on the board (#10). That combination is exactly what AI Hippo's context-per-dollar score rewards, which is why it sits near the top.
Spec sheet at a glance
By the numbers: 1.0M context window; multimodal (text, image, and file input); 18 exposed API parameters, including tool calling and structured outputs with reasoning support. Use these to judge fit for agentic, long-context, or structured-output workloads.
Pricing & how it compares
Pricing: $0.06 input / $0.20 output per 1M tokens. Its blended $0.13 is at or below the top-20 median ($0.21). On AI Hippo the composite board rewards cheap long-context models such as Meta: Llama 4 Scout, so a lower rank here means weaker value-per-token, not weaker capability.
Head-to-head
Its closest board neighbor is Poolside: Laguna S 2.1 (1.0M ctx, $0.14/1M blended). Side by side, Z.ai: GLM 5.3 Flash (batch) offers 1.0M ctx at $0.13/1M blended: context is similar and, on blended token price, it is cheaper. Pick between them on whichever axis your workload is bound by.
Where it fits
Best-fit workloads: whole-repo & long-document work, screenshot / PDF / image understanding, tool-calling agents, structured-output pipelines, multi-step reasoning, high-volume, cost-sensitive batch.
Cost in practice & verdict
A representative 100K-input + 20K-output task costs about $0.01 on Z.ai: GLM 5.3 Flash (batch). Verdict: strong price-performance for a default, high-volume workhorse where every token counts.