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Model comparison

GLM 4.6 Air vs ERNIE 4.5 Turbo

Not a benchmark table. This puts pricing, context, interface fit, and key visibility into one decision card.

Provider
Zhipu AI (GLM) / Baidu Wenxin
china / china
Context
128K / 128K
text->text / text->text
Input price
$0.45 / $0.12
per 1M tokens
Output price
$1.80 / $0.40
per 1M tokens
Left model
GLM 4.6 Air
Zhipu AI (GLM)
FamilyGLM
Modalitytext->text

更适合高频调用和渠道场景。

Right model
ERNIE 4.5 Turbo
Baidu Wenxin
FamilyERNIE
Modalitytext->text

适合高频问答和中国企业助手场景。

Comparison summary

How to choose first

This is a cross-provider comparison. Start with the job boundary, then verify what your key can actually see.

On the listed price snapshot, ERNIE 4.5 Turbo is cheaper on combined input and output, but real routing, discounts, and limits still matter.

When context is similar, compare output quality, API stability, limits, and actually callable models first.

Decision boundary

Do not start with which model is absolutely stronger. Start with the boundary: cost, context, speed, quality, ecosystem, or supply stability.

  • GLM 4.6 Air is worth checking first when the GLM family, 128K context, and text->text capability match the job.
  • ERNIE 4.5 Turbo is worth checking first when the ERNIE family, 128K context, and text->text capability match the job.

Key checking route

If you already hold a key, the valuable check is provider identity, callable models, and whether balance, limits, or subscription status are visible.

  • Zhipu AI (GLM): GLM 4.6 Air, GLM, text->text
  • Baidu Wenxin: ERNIE 4.5 Turbo, ERNIE, text->text

Commercial fit

Commercially, do not look at model names alone. Combine price, limits, region, upstream stability, and ongoing monitoring.

  • GLM 4.6 Air: 更适合高频调用和渠道场景。
  • ERNIE 4.5 Turbo: 适合高频问答和中国企业助手场景。