qwen3.5-flash
Input price$0.03
Output price$0.13
AlibabaText
qwen-turbo
qwen-turbo is Alibaba's model at $0.05 input and $0.20 output per million tokens, with a 1000K context window. On a typical 3:1 input-to-output mix that blends to roughly $0.088 per million tokens, placing it in the budget band of the 68 models tracked here — cheaper than 96% of them.
Context window1000K
Input price$0.05 / 1M
Output price$0.2 / 1M
Output speed240 tok/s
Quality score74
Data updatedUpdated Aug 2026
Price verified2026-08-06 · Official
By price, qwen-turbo ranks 3rd cheapest of 68 on input and 7th on output. Its quality score of 74 ranks 63rd of 68, and on value (quality score ÷ output price) it ranks 8th of 68. Its blended rate sits 97% below the catalog average.
In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $10 per month on qwen-turbo, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $11. Because output is priced 4.0× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.
A 1000K context window holds roughly 1,333 pages of A4 text (at ~750 tokens per page), ranking 22nd of 68 here. That is enough to drop in an entire technical manual or several source files at once, which suits long-document summarization and codebase-wide analysis. Output runs at about 240 tok/s (3rd fastest of 68), fast enough for real-time interaction and high-throughput batches.
We track 6 Alibaba models, and qwen-turbo's blended rate sits 88% below that provider's average. If your task tolerates a little less headroom, qwen3.5-flash (Alibaba) blends about 37% cheaper at a quality score of 82, and is worth benchmarking first. Nothing in the catalog scores higher on quality, so this is the ceiling.
The closest model in Alibaba's line-up is qwen3.5 ($0.10 input / $0.15 output, quality 91). Against it, qwen-turbo scores 17 points lower on quality, runs 155 tok/s faster (about 182%), costs 29% less blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.
Estimated monthly cost
Monthly API spend across four common workloads, next to the cheapest model we track.
| Workload | Usage assumption | This model | Cheapest model |
|---|---|---|---|
| Support chatbot | 2,000 input / 500 output tokens per turn, 50,000 turns per month | $10 | $3.00 |
| RAG document Q&A | 8,000 input / 800 output tokens per query, 20,000 queries per month | $11 | $3.84 |
| Coding assistant | 12,000 input / 2,000 output tokens per request, 10,000 requests per month | $10 | $3.20 |
| Batch summarization | 4,000 input / 400 output tokens per item, 200,000 items per month | $56 | $19 |
Derived directly from the rates on this page. Excludes prompt caching, batch discounts and free tiers.
How it compares
The alternatives worth benchmarking alongside it, from the same dataset.
| Model | Provider | Blended /1M | Quality | Price delta |
|---|---|---|---|---|
| qwen-turbo | Alibaba | $0.088 | 74 | — |
| qwen3.5-flashCheaper option | Alibaba | $0.055 | 82 | -37% |
| qwen3.5Same provider | Alibaba | $0.11 | 91 | +29% |
| Phi-4-miniBest value overall | Microsoft | $0.025 | 68 | -71% |
Best for
ChatbotAffordableFast
Modalities
Text
Where it fits — and where it doesn't
Good fit
- Chat and support: natural multi-turn conversation for user-facing products.
- Long documents: a 1000K window ingests a full contract, paper or large codebase in one pass.
- High throughput and real-time UX: 240 tok/s keeps streamed responses feeling instant.
- High-volume, cost-sensitive batch work: low rates suit classification, tagging and summarization at scale.
Poor fit
- Hard reasoning: a quality score of 74 is on the low side here; pick a stronger model for complex planning or maths.
- Image understanding: this model is text-only, so vision tasks need a multimodal alternative.
Frequently asked questions
How much does the qwen-turbo API cost?
qwen-turbo costs $0.05 per million input tokens and $0.20 per million output tokens. On a 3:1 input-to-output mix that blends to about $0.088 per million tokens.
What does qwen-turbo cost per month?
It depends on volume. Using the four worked scenarios on this page: a support chatbot runs about $10/month, RAG document Q&A about $11/month, a coding assistant about $10/month, and batch summarization about $56/month. Plug your own token counts into the cost calculator for a tailored figure.
How large is the qwen-turbo context window?
1000K tokens — roughly 1,333 pages of A4 text at ~750 tokens per page, ranking 22nd of the 68 models tracked here.
qwen-turbo or qwen3.5-flash — which is better value?
qwen3.5-flash blends to about $0.055 per million tokens versus $0.088 for qwen-turbo — roughly 37% cheaper — at a quality score of 82 against 74. If that quality gap does not show up on your task, take the cheaper one; if it does, stay with qwen-turbo. Benchmark both on your own data before deciding.
What is qwen-turbo best suited for?
Tagged use cases: chatbot, cheap, fast. Chat and support: natural multi-turn conversation for user-facing products. Less suitable: Hard reasoning: a quality score of 74 is on the low side here; pick a stronger model for complex planning or maths.
How current is this qwen-turbo pricing?
Pricing here was last verified on 2026-08-06 against official documentation. llmprice.app runs a daily collection job, but providers can change rates between runs — confirm against Alibaba's official pricing page before you commit.
Estimate the real cost of this model
Bring tokens per request and monthly volume into the calculator to compare total model costs.
Related models
Continue by provider and use case.
View model
qwen-plus
Input price$0.26
Output price$0.78
qwen3.5-plus
Input price$0.4
Output price$2.4
Pricing, speed and quality scores change over time. Confirm official documentation before production use.