Qwen Turbo
alibaba/turboPar Alibaba (Qwen) · famille: qwen · sorti 2024-11-01 · fin de connaissance: 2024-04
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.
Coding76
- Tool calling40/40
- Structured output0/20
- Reasoning10/10
- Context window (100K → 1M)20/20
- Provider availability6/10
Agents66
- Tool calling35/35
- Structured output0/25
- Reasoning15/15
- Output token limit10/15
- Provider availability6/10
JSON / structured output50
- Structured output / JSON mode0/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume20/20
Cost efficiency77
- Headline price (log-scaled)77/95
- Has prompt-cache pricing0/5
Long context90
- Context window (100K → 2M)80/90
- Has published price for full window10/10
Production-readiness86
- Number of independent providers30/40
- 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 | $0.35 < $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 | $0.70 < $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 | $0.20 < $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 | $0.60 < $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 | $0.72 < $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 alibaba · qwen-turbo
Fournisseur le moins cher : alibaba-cn · $0.044 entrée + $0.087 sortie
Disponible chez 6 fournisseurs
| Fournisseur | ID modèle fournisseur | Entrée / 1M | Sortie / 1M | Contexte | Publié le |
|---|---|---|---|---|---|
| Alibaba alibaba | qwen-turbo | $0.050 | $0.200 | 1M | 2024-11-01 |
| Alibaba (China) alibaba-cn | qwen-turbo | $0.044 | $0.087 | 1M | 2024-11-01 |
| NanoGPT nano-gpt | qwen-turbo | $0.050 | $0.201 | 1M | 2024-11-01 |
| Qiniu qiniu-ai | qwen-turbo | Unknown | Unknown | 1M | 2025-08-05 |
| Kilo Gateway kilo | qwen/qwen-turbo | $0.033 | $0.130 | 131K | 2024-11-01 |
| LLM Gateway llmgateway | qwen-turbo | $0.050 | $0.200 | 1M | 2024-11-01 |
Incohérences de données entre fournisseurs
- context_window varies: 1000000, 131072
- release_date varies (span 277d): 2024-11-01, 2025-08-05
Les fournisseurs rapportent des valeurs différentes pour ce modèle. Les infos clés ci-dessus utilisent un fournisseur représentatif ; voir le tableau pour le détail par fournisseur.
Frequently asked questions
How much does Qwen Turbo cost?
Qwen Turbo costs $0.050 per 1M input tokens and $0.200 per 1M output tokens, sourced from alibaba. 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 Turbo?
Qwen Turbo has a context window of 1M tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen Turbo support tool calling?
Yes. Qwen Turbo 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 Turbo support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Qwen Turbo in our data source. Verify with Alibaba (Qwen)'s official documentation before relying on it in production.
Can Qwen Turbo accept image input?
No. Qwen Turbo only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Qwen Turbo open-weight?
No. Qwen Turbo is a proprietary model — only Alibaba (Qwen) (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to Qwen Turbo?
If Qwen Turbo doesn't fit, consider Qwen3.5 397B-A17B, Qwen3 32B, Qwen3 235B A22B Instruct 2507. 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
More Alibaba (Qwen) models
- Qwen3.5 397B-A17B$0.60 in / $3.60 out
- Qwen3 32B$0.70 in / $2.80 out
- Qwen3 235B A22B Instruct 2507$0.10 in / $0.10 out
- Qwen3-Coder 480B-A35B Instruct$1.50 in / $7.50 out
- Qwen3-235B-A22B-Thinking-2507$0.10 in / $0.10 out
Capability lists this model is in
Dernière mise à jour :
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.