Qwen 3.32B
vercel/3-32bPar vercel · famille: qwen · sorti 2025-04-28 · fin de connaissance: 2025-04
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Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Capacités
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.
Coding53
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)2/20
- Provider availability1/10
Agents56
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit5/15
- Provider availability1/10
JSON / structured output48
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume18/20
Cost efficiency65
- Headline price (log-scaled)65/95
- Has prompt-cache pricing0/5
Long context45
- Context window (100K → 2M)35/90
- 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 | $1.12 < $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 | $2.24 < $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 | $0.64 < $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 | $1.92 < $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 | $2.30 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Détail des tarifs
Tarif recommandé de vercel · alibaba/qwen-3-32b
Disponible chez 1 fournisseurs
| Fournisseur | ID modèle fournisseur | Entrée / 1M | Sortie / 1M | Contexte | Publié le |
|---|---|---|---|---|---|
| Vercel AI Gateway vercel | alibaba/qwen-3-32b | $0.160 | $0.640 | 128K | 2025-04-28 |
Frequently asked questions
How much does Qwen 3.32B cost?
Qwen 3.32B costs $0.160 per 1M input tokens and $0.640 per 1M output tokens, sourced from vercel. 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 3.32B?
Qwen 3.32B has a context window of 128K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen 3.32B support tool calling?
Yes. Qwen 3.32B 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 Qwen 3.32B support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Qwen 3.32B in our data source. Verify with vercel's official documentation before relying on it in production.
Can Qwen 3.32B accept image input?
No. Qwen 3.32B only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Qwen 3.32B open-weight?
No. Qwen 3.32B is a proprietary model — only vercel (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Qwen 3.32B?
If Qwen 3.32B doesn't fit, consider Kling v3.0 Motion Control, Kling v2.6 Image-to-Video, Kling v2.5 Turbo Text-to-Video. 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 vercel models
- Kling v3.0 Motion ControlUnknown pricing
- Kling v2.6 Image-to-VideoUnknown pricing
- Kling v2.5 Turbo Text-to-VideoUnknown pricing
- Kling v3.0 Image-to-VideoUnknown pricing
- Kling v2.5 Turbo Image-to-VideoUnknown pricing
Capability lists this model is in
Dernière mise à jour :
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.