Qwen QwQ 32B Preview
nano-gpt/qwq-32b-preview出品方： nano-gpt · 发布 2025-02-27
⚠ 本模型为社区微调 / 衍生版本，非厂商官方发布。
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
能力清单
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.
Coding1
- Tool calling0/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability1/10
Agents16
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output19
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control0/10
- Price-friendly for high-volume19/20
Cost efficiency72
- Headline price (log-scaled)72/95
- 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 | $1.10 < $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 | $2.20 < $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 | $0.50 < $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 | $1.80 < $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 | $2.52 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
定价详情
推荐定价来自 nano-gpt · qwen/qwq-32b-preview
在 1 家渠道可用
| 服务商 | 服务商模型 ID | 输入 / 1M | 输出 / 1M | 上下文 | 发布日期 |
|---|---|---|---|---|---|
| NanoGPT nano-gpt | qwen/qwq-32b-preview | $0.200 | $0.200 | 33K | 2025-02-27 |
Frequently asked questions
How much does Qwen QwQ 32B Preview cost?
Qwen QwQ 32B Preview costs $0.200 per 1M input tokens and $0.200 per 1M output tokens, sourced from nano-gpt. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Qwen QwQ 32B Preview?
Qwen QwQ 32B Preview has a context window of 33K tokens, with a max output of 33K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen QwQ 32B Preview support tool calling?
No. Qwen QwQ 32B Preview does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does Qwen QwQ 32B Preview support structured output / JSON mode?
No. Qwen QwQ 32B Preview does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.
Can Qwen QwQ 32B Preview accept image input?
No. Qwen QwQ 32B Preview only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Qwen QwQ 32B Preview open-weight?
No. Qwen QwQ 32B Preview is a proprietary model — only nano-gpt (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Qwen QwQ 32B Preview?
If Qwen QwQ 32B Preview doesn't fit, consider ERNIE X1.1, Brave (Research), MiroThinker 1.7 Deep Research Mini. 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 nano-gpt models
- ERNIE X1.1$0.15 in / $0.60 out
- Brave (Research)$5.00 in / $5.00 out
- MiroThinker 1.7 Deep Research Mini$1.25 in / $10.00 out
- Baichuan 4 Turbo$2.42 in / $2.42 out
- v0 1.0 MD$3.00 in / $15.00 out
最近更新：
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.