Qwen-MT Turbo
alibaba/mt-turboمن Alibaba (Qwen) · العائلة: qwen · أُصدِر 2025-01 · تاريخ المعرفة: 2024-04
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
القدرات
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.
Coding2
- Tool calling0/40
- Structured output0/20
- Reasoning0/10
- Context window (100K → 1M)0/20
- Provider availability2/10
Agents7
- Tool calling0/35
- Structured output0/25
- Reasoning0/15
- Output token limit5/15
- Provider availability2/10
JSON / structured output29
- Structured output / JSON mode0/50
- Tool calling0/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency67
- Headline price (log-scaled)67/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Production-readiness63
- Number of independent providers10/40
- Has published per-token price20/20
- Context window ≥ 8K8/15
- No data inconsistencies across providers10/10
- 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 | $1.04 < $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 | $2.09 < $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 | $0.56 < $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 | $1.77 < $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 | $2.21 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
تفاصيل التسعير
السعر المُوصى به من alibaba · qwen-mt-turbo
أرخص مزود: alibaba-cn · $0.101 إدخال + $0.280 إخراج
متاح لدى 2 مزود
| المزود | معرف نموذج المزود | إدخال / 1M | إخراج / 1M | السياق | تاريخ الإصدار |
|---|---|---|---|---|---|
| Alibaba alibaba | qwen-mt-turbo | $0.160 | $0.490 | 16K | 2025-01 |
| Alibaba (China) alibaba-cn | qwen-mt-turbo | $0.101 | $0.280 | 16K | 2025-01 |
Frequently asked questions
How much does Qwen-MT Turbo cost?
Qwen-MT Turbo costs $0.160 per 1M input tokens and $0.490 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-MT Turbo?
Qwen-MT Turbo has a context window of 16K tokens, with a max output of 8K tokens per reply. This is the total combined size of prompt + completion.
Does Qwen-MT Turbo support tool calling?
No. Qwen-MT Turbo does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does Qwen-MT Turbo support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for Qwen-MT Turbo in our data source. Verify with Alibaba (Qwen)'s official documentation before relying on it in production.
Can Qwen-MT Turbo accept image input?
No. Qwen-MT Turbo only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is Qwen-MT Turbo open-weight?
No. Qwen-MT 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-MT Turbo?
If Qwen-MT 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
آخر تحديث:
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.