GLM-5 — API Pricing & Benchmarks

GLM-5 is Zhipu AI (Z.ai)'s mid reasoning model, released in 2026-02. The API costs $1.00 per 1M input tokens and $3.20 per 1M output tokens ($1.55 blended at a 3:1 ratio), with cached input at $0.20. It supports a 200K-token context window. On the independently measured Artificial Analysis Intelligence Index it scores 40.6, ranking #41 of 68 models tracked on this site, with a median output speed of 48 tokens/sec.

Explore provider routes and additional benchmark sources for GLM-5

ProviderZhipu AI (Z.ai)
Input price / 1M tokens$1.00
Output price / 1M tokens$3.20
Cached input / 1M tokens$0.20
Blended price (3:1)$1.55
Context window200K
Max output tokens128K
Knowledge cutoff
Licenseopen weights
Input modalitiesT
Output speed (tok/s)48
Released2026-02
Artificial Analysis Intelligence Index40.6
LMArena Elo1446
GPQA Diamond82%
Humanity's Last Exam29.3%

Where GLM-5 fits

On a blended 3:1 basis GLM-5 costs $1.55 per 1M tokens, cheaper than 55% of the 80 priced models in this index. It sits in the mid-tier bracket where most production chat, RAG and summarization workloads run: meaningfully cheaper than flagships while keeping most of their capability. Measured output speed of 48 tokens/sec is below the index median of 104 — typical of reasoning-heavy models, and worth checking against interactive latency budgets. The weights are open, so it can be self-hosted for data-residency or cost reasons instead of consumed via API. Cached input is priced at $0.20 (80% below standard input), which rewards prompt structures with long stable prefixes — see our caching guide.

Price history

PeriodInput $/1MOutput $/1MCached $/1M
2026-07-18 → current$1.00$3.20$0.20

No list-price changes recorded since tracking began. Full dataset: price-history.json (CC BY 4.0).

Alternatives at a similar price

About Zhipu AI (Z.ai)

Zhipu AI (Z.ai) publishes the GLM series as open weights. GLM-5.3 benchmarks within a few points of the proprietary frontier at roughly a third of the price, and GLM-5.3-Flash keeps most of that score at small-model pricing.

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