Alibaba Cloud DashScope provides AI model APIs including Qwen LLMs, vision, audio, and embedding models.
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Rankings are based on community-submitted tests and periodic health probes. Advisory only, not official data.
Compare 69 model rows across audit recency, latest speed tests, throughput, latency, and per-token pricing.
| Model | Input ($/M) | Output ($/M) | Audit | Speed | Latency |
|---|---|---|---|---|---|
qwen3.7-plus | - | - | — | 43.4 t/s | 32.06 s |
qwen3.7-max | - | - | — | 49.0 t/s | 24.19 s |
| - | - | — | 44.3 t/s | 19.58 s | |
| - | - | — | 35.7 t/s | 2.15 s | |
qwen3.6-27b | - | - | 10010086100 | 47.9 t/s | 23.69 s |
qwen3.6-flash | - | - | — | 105.9 t/s | 8.21 s |
| - | - | — | 35.3 t/s | 7.49 s | |
| - | - | 10010086100 | 107.7 t/s | 3.32 s | |
| - | - | — | 37.6 t/s | 1.85 s | |
qvq-max-2025-03-25 | - | - | — | 39.5 t/s | 14.51 s |
qwen-math-turbo | - | - | — | 48.4 t/s | 1.37 s |
| - | - | — | 44.6 t/s | 14.24 s | |
qwen-vl-plus-2025-05-07 | - | - | — | 99.2 t/s | 0.88 s |
| - | - | — | 47.5 t/s | 26.05 s | |
qwen3-coder-next | - | - | — | 147.1 t/s | 0.97 s |
| - | - | — | 30.2 t/s | 15.15 s | |
| - | - | — | 40.0 t/s | 21.87 s | |
| - | - | — | 114.8 t/s | 8.57 s | |
| - | - | — | 67.8 t/s | 7.80 s | |
| - | - | — | 25.3 t/s | 24.05 s | |
| - | - | — | 34.7 t/s | 23.13 s | |
| - | - | — | 45.0 t/s | 2.06 s | |
tongyi-xiaomi-analysis-pro | - | - | — | 65.8 t/s | 0.64 s |
qwen-vl-plus-2025-07-10 | - | - | — | 112.4 t/s | 0.56 s |
qwen-plus-2025-04-28 | - | - | — | 43.5 t/s | 0.57 s |
qwen-plus-2025-12-01 | - | - | — | 54.3 t/s | 0.80 s |
| - | - | — | 52.5 t/s | 17.22 s | |
deepseek-r1-distill-llama-70b | - | - | — | 24.7 t/s | 23.28 s |
| - | - | — | 73.7 t/s | 6.13 s | |
| - | - | — | 40.7 t/s | 1.24 s | |
qwen-14b-chat | - | - | — | 50.7 t/s | 0.90 s |
qwen-coder-plus-latest | - | - | — | 53.0 t/s | 0.96 s |
qwen-flash | - | - | — | 126.7 t/s | 0.96 s |
qwen-flash-2025-07-28 | - | - | — | 91.8 t/s | 1.48 s |
qwen-max | - | - | — | 24.5 t/s | 0.98 s |
qwen-max-0428 | - | - | — | 16.9 t/s | 0.97 s |
qwen-max-latest | - | - | — | 31.0 t/s | 0.94 s |
qwen-mt-turbo | - | - | — | 4366.6 t/s | 0.60 s |
qwen-plus | - | - | — | 36.0 t/s | 0.87 s |
qwen-plus-latest | - | - | — | 34.3 t/s | 0.88 s |
qwen-turbo-latest | - | - | — | 51.7 t/s | 1.01 s |
qwen-vl-max | - | - | — | 26.5 t/s | 1.12 s |
qwen-vl-plus | - | - | — | 69.8 t/s | 1.00 s |
qwen1.5-7b-chat | - | - | — | 60.0 t/s | 0.89 s |
qwen2.5-14b-instruct | - | - | — | 49.9 t/s | 0.96 s |
qwen2.5-14b-instruct-1m | - | - | — | 51.7 t/s | 1.37 s |
qwen2.5-72b-instruct | - | - | — | 28.2 t/s | 0.97 s |
qwen2.5-7b-instruct-1m | - | - | — | 92.6 t/s | 0.93 s |
qwen2.5-coder-0.5b-instruct | - | - | — | 60.4 t/s | 0.75 s |
qwen2.5-coder-32b-instruct | - | - | — | 28.0 t/s | 1.02 s |
qwen2.5-coder-3b-instruct | - | - | — | 38.5 t/s | 1.00 s |
| - | - | — | 140.1 t/s | 4.85 s | |
qwen3-235b-a22b-instruct-2507 | - | - | — | 43.2 t/s | 0.95 s |
qwen3-235b-a22b-thinking-2507 | - | - | — | 53.5 t/s | 13.88 s |
qwen3-next-80b-a3b-instruct | - | - | — | 144.5 t/s | 2.22 s |
qwen3-vl-235b-a22b-instruct | - | - | — | 41.5 t/s | 3.23 s |
qwen3-vl-flash | - | - | — | 147.6 t/s | 1.00 s |
qwq-32b | - | - | — | 38.0 t/s | 17.85 s |
tongyi-intent-detect-v3 | - | - | — | 87.5 t/s | 0.72 s |
| - | - | — | 27.2 t/s | 1.27 s | |
| - | - | — | 29.1 t/s | 1.51 s | |
| - | - | — | 33.8 t/s | 16.24 s | |
| - | - | — | 33.3 t/s | 1.46 s | |
| - | - | — | 26.4 t/s | 1.25 s | |
| - | - | — | 33.2 t/s | 1.69 s | |
| - | - | — | 44.6 t/s | 0.77 s | |
| - | - | — | 25.5 t/s | 38.31 s | |
| - | - | — | 36.5 t/s | 42.23 s | |
| - | - | — | 92.2 t/s | 9.98 s |
Showing 69 of 69 model rows
| Time | Model | Speed | Latency |
|---|---|---|---|
| Jun 16, 04:26 AM | qwen3.7-plus | 36.76 tok/s | 35.12s |
| Jun 12, 04:01 PM | qwen3.7-plus | 50.98 tok/s | 29.12s |
| Jun 12, 03:53 PM | qwen3.5-plus | 44.75 tok/s | 19.59s |
| Jun 5, 08:45 AM | qwen3.7-plus | 42.48 tok/s | 31.95s |
| Jun 3, 07:46 AM | qwen3.6-27b | 44.49 tok/s | 22.70s |
| Jun 3, 07:31 AM | qwen3.6-27b | 51.31 tok/s | 24.67s |
| May 28, 07:52 PM | qwen3.7-max | 49.01 tok/s | 24.19s |
| May 28, 02:32 PM | qwen3.6-plus | 53.98 tok/s | 22.58s |
| May 27, 02:22 AM | deepseek-v4-flash | 81.65 tok/s | 4.25s |
| May 26, 05:47 AM | qwen-flash | 117.50 tok/s | 1.76s |
Compare 阿里云百炼 DashScope alternatives against 6 nearby API providers using 314 LMSpeed signals across shared model coverage, pricing, benchmark speed, uptime, and free-model availability.
| Provider | Why compare | Models | Free | Avg price | Speed | 30d uptime |
|---|---|---|---|---|---|---|
| 阿里云百炼 DashScope dashscope Alibaba Cloud DashScope provides AI model APIs including Qwen LLMs, vision, audio, and embedding models. | Current provider baseline | 56 | 0 | N/A | 73 tok/s | 92.1% |
| GLM BigModel Relay glm-bigmodel-relay A third-party API relay providing access to GLM/ChatGLM models through OpenAI-compatible endpoints. |
| 113 | 0 | $0.704/M | 52 tok/s | 97.2% |
mistral-ai-api Mistral AI API provides access to frontier AI models including Mistral Large, Medium, Small, and Codestral for chat, code, and embeddings. |
| 4 | 0 | N/A | 132 tok/s | 96.3% |
google-gemini-api Google Gemini API offers access to Gemini models and an OpenAI-compatible interface for application development and model inference. |
| 1 | 0 | N/A | 157 tok/s | 94.3% |
volcengine-ark Volcengine Ark is ByteDance's enterprise AI platform, offering Doubao series models and third-party LLMs via OpenAI-compatible API. |
| 32 | 0 | N/A | 40 tok/s | 94.7% |
baidu-qianfan Baidu Qianfan is Baidu Intelligent Clouds enterprise AI platform, providing access to ERNIE series models and other LLM capabilities through developer APIs. |
| 26 | 0 | N/A | 81 tok/s | 72.8% |
zhipu-ai Zhipu AI provides the GLM series of large language models including GLM-4, ChatGLM, and CodeGeeX for text, code, and multimodal tasks. |
| 22 | 0 | N/A | 59 tok/s | 95.5% |