GLM-5.2
regolo-ai/glm5-2제공: regolo-ai · 패밀리: glm · 출시 2026-06-13
⚠ 이 모델은 커뮤니티 파인튜닝 / 파생본으로, 벤더 공식 릴리스가 아닙니다.
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
기능
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.
Coding71
- Tool calling40/40
- Structured output20/20
- Reasoning10/10
- Context window (100K → 1M)0/20
- Provider availability1/10
Agents91
- Tool calling35/35
- Structured output25/25
- Reasoning15/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output83
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume3/20
Cost efficiency39
- Headline price (log-scaled)39/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Production-readiness50
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers10/10
- Official model (not derivative)0/15
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 | $14.55 $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 | $29.10 < $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 | $7.62 < $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 | $24.48 $0.02 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $31.32 $0.03 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
가격 상세
추천 가격 제공자: regolo-ai · glm5.2
1곳 제공사에서 이용 가능
| 제공자 | 제공자 모델 ID | 입력 / 1M | 출력 / 1M | 컨텍스트 | 출시일 |
|---|---|---|---|---|---|
| Regolo AI regolo-ai | glm5.2 | $2.31 | $6.00 | 96K | 2026-06-13 |
Frequently asked questions
How much does GLM-5.2 cost?
GLM-5.2 costs $2.31 per 1M input tokens and $6.00 per 1M output tokens, sourced from regolo-ai. 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-5.2?
GLM-5.2 has a context window of 96K tokens, with a max output of 96K tokens per reply. This is the total combined size of prompt + completion.
Does GLM-5.2 support tool calling?
Yes. GLM-5.2 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-5.2 support structured output / JSON mode?
Yes. GLM-5.2 supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can GLM-5.2 accept image input?
No. GLM-5.2 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is GLM-5.2 open-weight?
Yes. GLM-5.2'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-5.2?
If GLM-5.2 doesn't fit, consider Brick Complexity Pro, Apertus 70B, Faster Whisper Large v3. 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 are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More regolo-ai models
- Brick Complexity Pro$0.12 in / $0.46 out
- Apertus 70B$0.46 in / $2.42 out
- Faster Whisper Large v3Unknown pricing
- Brick v1 BetaUnknown pricing
Capability lists this model is in
마지막 업데이트:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.