GLM-4.7
zai/glm-4-7Von Z.AI / Zhipu · Familie: glm · veröffentlicht 2025-12-22 · Wissensstand: 2025-04
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Fähigkeiten
Model fit scores
0–100 · higher is betterThese 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.
Coding66
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)6/20
- Provider availability10/10
Agents75
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit15/15
- Provider availability10/10
JSON / structured output44
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume14/20
Cost efficiency56
- Headline price (log-scaled)51/95
- Has prompt-cache pricing5/5
Long context56
- Context window (100K → 2M)46/90
- Has published price for full window10/10
Production-readiness96
- Number of independent providers40/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers6/10
- 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.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $4.10 < $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 | $8.20 < $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 | $2.30 < $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 | $7.00 < $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 | $8.52 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Preis-Details
Empfohlene Preise von zai · glm-4.7
Günstigster Anbieter: zai-coding-plan · Unknown Eingabe + Unknown Ausgabe
Bei 36 Anbietern verfügbar
| Anbieter | Anbieter-Modell-ID | Eingabe / 1M | Ausgabe / 1M | Kontext | Veröffentlicht |
|---|---|---|---|---|---|
| Z.AI zai | glm-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Z.AI Coding Plan zai-coding-plan | glm-4.7 | Unknown | Unknown | 205K | 2025-12-22 |
| Zhipu AI Coding Plan zhipuai-coding-plan | glm-4.7 | Unknown | Unknown | 205K | 2025-12-22 |
| Zhipu AI zhipuai | glm-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Amazon Bedrock amazon-bedrock | zai.glm-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| OpenRouter openrouter | z-ai/glm-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Vercel AI Gateway vercel | zai/glm-4.7 | $0.430 | $1.75 | 203K | 2025-12-22 |
| Deep Infra deepinfra | zai-org/GLM-4.7 | $0.430 | $1.75 | 203K | 2025-12-22 |
| Hugging Face huggingface | zai-org/GLM-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| 302.AI 302ai | glm-4.7 | $0.286 | $1.14 | 205K | 2025-12-22 |
| NanoGPT nano-gpt | TEE/glm-4.7 | $0.850 | $3.30 | 131K | 2026-01-29 |
| NanoGPT nano-gpt | zai-org/glm-4.7 | $0.150 | $0.800 | 200K | 2026-01-29 |
| Abacus abacus | zai-org/glm-4.7 | $0.600 | $2.20 | 128K | 2025-06-01 |
| SiliconFlow (China) siliconflow-cn | Pro/zai-org/GLM-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Moark moark | GLM-4.7 | $3.50 | $14.00 | 205K | 2025-12-22 |
| Jiekou.AI jiekou | zai-org/glm-4.7 | $0.600 | $2.20 | 205K | 2026-01 |
| ZenMux zenmux | z-ai/glm-4.7 | $0.280 | $1.14 | 200K | 2025-12-23 |
| NovitaAI novita-ai | zai-org/glm-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Chutes chutes | zai-org/GLM-4.7-FP8 | $0.299 | $1.20 | 203K | 2026-01-27 |
| DInference dinference | glm-4.7 | $0.450 | $1.65 | 200K | 2025-12-22 |
| Qiniu qiniu-ai | z-ai/glm-4.7 | Unknown | Unknown | 200K | 2025-12-23 |
| Kilo Gateway kilo | z-ai/glm-4.7 | $0.380 | $1.98 | 203K | 2025-12-22 |
| OpenCode Zen opencode | glm-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Ollama Cloud ollama-cloud | glm-4.7 | Unknown | Unknown | 203K | 2025-12-22 |
| Baseten baseten | zai-org/GLM-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Alibaba Coding Plan alibaba-coding-plan | glm-4.7 | Unknown | Unknown | 203K | 2025-12-22 |
| Venice AI venice | zai-org-glm-4.7 | $0.550 | $2.65 | 198K | 2025-12-24 |
| Cerebras cerebras | zai-glm-4.7 | $2.25 | $2.75 | 131K | 2026-01-10 |
| KUAE Cloud Coding Plan kuae-cloud-coding-plan | GLM-4.7 | Unknown | Unknown | 205K | 2025-12-22 |
| Meganova meganova | zai-org/GLM-4.7 | $0.200 | $0.800 | 203K | 2025-12-22 |
| Synthetic synthetic | hf:zai-org/GLM-4.7 | $0.550 | $2.19 | 200K | 2025-12-22 |
| Alibaba Coding Plan (China) alibaba-coding-plan-cn | glm-4.7 | Unknown | Unknown | 203K | 2025-12-22 |
| Cortecs cortecs | glm-4.7 | $0.450 | $2.23 | 198K | 2025-12-22 |
| SiliconFlow siliconflow | zai-org/GLM-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| LLM Gateway llmgateway | glm-4.7 | $0.600 | $2.20 | 205K | 2025-12-22 |
| Berget.AI berget | zai-org/GLM-4.7 | $0.770 | $2.75 | 128K | 2026-01-19 |
Datenunterschiede zwischen Anbietern
- context_window varies: 128000, 131000, 131072, 198000, 200000, 202752, 204800, 205000
- release_date varies (span 242d): 2025-06-01, 2025-12-22, 2025-12-23, 2025-12-24, 2026-01, 2026-01-10, 2026-01-19, 2026-01-27, 2026-01-29
Anbieter melden unterschiedliche Werte für dieses Modell. Die Schnellinfos oben nutzen den repräsentativen Anbieter; pro Anbieter siehe Tabelle.
Frequently asked questions
How much does GLM-4.7 cost?
GLM-4.7 costs $0.600 per 1M input tokens and $2.20 per 1M output tokens, sourced from zai. 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-4.7?
GLM-4.7 has a context window of 205K tokens, with a max output of 131K tokens per reply. This is the total combined size of prompt + completion.
Does GLM-4.7 support tool calling?
Yes. GLM-4.7 supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does GLM-4.7 support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for GLM-4.7 in our data source. Verify with Z.AI / Zhipu's official documentation before relying on it in production.
Can GLM-4.7 accept image input?
No. GLM-4.7 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is GLM-4.7 open-weight?
Yes. GLM-4.7's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to GLM-4.7?
If GLM-4.7 doesn't fit, consider GLM-5, GLM-5.1, GLM-4.6. 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.
Explore more
Direct comparisons
More Z.AI / Zhipu models
- GLM-5$1.00 in / $3.20 out
- GLM-5.1$1.40 in / $4.40 out
- GLM-4.6$0.60 in / $2.20 out
- GLM-4.7-Flash$0.06 in / $0.40 out
- GLM-4.5$0.60 in / $2.20 out
Capability lists this model is in
Zuletzt aktualisiert:
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.