GLM 5.2 Short Flex
neuralwatt/glm-5-2-short-flexBy neuralwatt · family: glm · released 2026-06-17
⚠ This is a community fine-tune or derivative — not an official vendor release.
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capabilities
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.
Coding57
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)6/20
- Provider availability1/10
Agents66
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit15/15
- Provider availability1/10
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 context55
- Context window (100K → 2M)45/90
- Has published price for full window10/10
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 | $4.75 < $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 | $9.50 < $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 | $2.58 < $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 | $8.05 < $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 | $10.05 $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Pricing detail
Recommended pricing from neuralwatt · glm-5.2-short-flex
Available on 1 providers
| Provider | Provider model id | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|---|
| Neuralwatt neuralwatt | glm-5.2-short-flex | $0.725 | $2.25 | 200K | 2026-06-17 |
Frequently asked questions
How much does GLM 5.2 Short Flex cost?
GLM 5.2 Short Flex costs $0.725 per 1M input tokens and $2.25 per 1M output tokens, sourced from neuralwatt. 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 Short Flex?
GLM 5.2 Short Flex has a context window of 200K tokens, with a max output of 200K tokens per reply. This is the total combined size of prompt + completion.
Does GLM 5.2 Short Flex support tool calling?
Yes. GLM 5.2 Short Flex 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 Short Flex support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for GLM 5.2 Short Flex in our data source. Verify with neuralwatt's official documentation before relying on it in production.
Can GLM 5.2 Short Flex accept image input?
No. GLM 5.2 Short Flex only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is GLM 5.2 Short Flex open-weight?
Yes. GLM 5.2 Short Flex'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.
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.
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Capability lists this model is in
Last updated:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.