AI 模型情報

GLM Z1 9B 0414

zai/glm-z1-9b-0414

出品方: Z.AI / Zhipu · 系列: glm-z · 發布 2025-04-18

$0.086
輸入 / 1M token
$0.086
輸出 / 1M token
32K
上下文長度
8K
最大輸出

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

能力清單

工具呼叫推理結構化輸出附件開放權重? 溫度可調
支援模態: 輸入 text · 輸出 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding3
  • Tool calling0/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)0/20
  • Provider availability3/10
Agents8
  • Tool calling0/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit5/15
  • Provider availability3/10
JSON / structured output20
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control0/10
  • Price-friendly for high-volume20/20
Cost efficiency81
  • Headline price (log-scaled)81/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
Production-readiness73
  • Number of independent providers15/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers8/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$0.47
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$0.95
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$0.21
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$0.77
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$1.08
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定價詳情

推薦定價來自 siliconflow-cn · THUDM/GLM-Z1-9B-0414

$0.086
輸入
$0.086
輸出

於 3 家供應商可用

服務商服務商模型 ID輸入 / 1M輸出 / 1M上下文發布日期
NanoGPT
nano-gpt
THUDM/GLM-Z1-9B-0414$0.200$0.20032K2025-04-14
SiliconFlow (China)
siliconflow-cn
THUDM/GLM-Z1-9B-0414$0.086$0.086131K2025-04-18
SiliconFlow
siliconflow
THUDM/GLM-Z1-9B-0414$0.086$0.086131K2025-04-18

各渠道資料存在不一致

  • context_window varies: 131000, 32000

各服務商對此模型的回報值不一致。上方「核心數據」採用代表性服務商的值;逐項請以下表為準。

Frequently asked questions

How much does GLM Z1 9B 0414 cost?

GLM Z1 9B 0414 costs $0.086 per 1M input tokens and $0.086 per 1M output tokens, sourced from siliconflow-cn. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of GLM Z1 9B 0414?

GLM Z1 9B 0414 has a context window of 32K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.

Does GLM Z1 9B 0414 support tool calling?

No. GLM Z1 9B 0414 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does GLM Z1 9B 0414 support structured output / JSON mode?

No. GLM Z1 9B 0414 does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.

Can GLM Z1 9B 0414 accept image input?

No. GLM Z1 9B 0414 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is GLM Z1 9B 0414 open-weight?

No. GLM Z1 9B 0414 is a proprietary model — only Z.AI / Zhipu (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to GLM Z1 9B 0414?

If GLM Z1 9B 0414 doesn't fit, consider GLM-5, GLM-4.7, GLM-5.1. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

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Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.