Provides cost-effective generative AI cloud services based on open-source models for text, image, video, and audio generation.
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Rankings are based on community-submitted tests and periodic health probes. Advisory only, not official data.
SiliconFlow offers generative AI cloud services built on open-source models. Primary capabilities include text conversation, image generation, video generation, and speech synthesis. The platform emphasizes high cost-effectiveness for these AI generation tasks. Typical use cases involve leveraging these multimodal AI services for various creative and conversational applications.
Compare 62 model rows across audit recency, latest speed tests, throughput, latency, and per-token pricing.
| Model | Input ($/M) | Output ($/M) | Audit | Speed | Latency |
|---|---|---|---|---|---|
| - | - | — | 52.1 t/s | 10.99 s | |
| - | - | 888486100 | 83.1 t/s | 1.16 s | |
Qwen/Qwen3.6-27B | - | - | — | 36.1 t/s | 41.10 s |
| - | - | 846880100 | 38.4 t/s | 0.49 s | |
| - | - | — | 73.4 t/s | 15.12 s | |
Qwen/Qwen3.6-35B-A3B | - | - | — | 115.8 t/s | 8.56 s |
| - | - | — | 49.6 t/s | 9.04 s | |
ByteDance-Seed/Seed-OSS-36B-Instruct | - | - | — | 61.6 t/s | 12.78 s |
| - | - | — | 89.9 t/s | 6.43 s | |
PaddlePaddle/PaddleOCR-VL-1.5 | - | - | — | 279.6 t/s | 4.15 s |
| - | - | — | 34.2 t/s | 33.63 s | |
| - | - | — | 136.6 t/s | 6.06 s | |
| - | - | — | 32.8 t/s | 29.36 s | |
| - | - | — | 95.6 t/s | 16.29 s | |
Qwen/Qwen3-Omni-30B-A3B-Instruct | - | - | — | 128.8 t/s | 0.47 s |
| - | - | — | 54.7 t/s | 7.54 s | |
| - | - | — | 71.4 t/s | 9.63 s | |
| - | - | — | 43.6 t/s | 27.77 s | |
| - | - | — | 84.2 t/s | 3.37 s | |
| - | - | — | 44.6 t/s | 14.30 s | |
| - | - | — | 62.3 t/s | 16.76 s | |
| - | - | — | 74.7 t/s | 16.10 s | |
deepseek-ai/DeepSeek-R1-0528-Qwen3-8B | - | - | — | 48.5 t/s | 27.88 s |
deepseek-ai/DeepSeek-R1-Distill-Llama-70B | - | - | — | 22.6 t/s | 6.14 s |
| - | - | — | 15.5 t/s | 0.96 s | |
| - | - | — | 14.9 t/s | 2.66 s | |
inclusionAI/Ling-1T | - | - | — | 12.5 t/s | 1.10 s |
internlm/internlm2_5-7b-chat | - | - | — | 69.3 t/s | 0.57 s |
LoRA/Qwen/Qwen2.5-14B-Instruct | - | - | — | 58.1 t/s | 1.02 s |
LoRA/Qwen/Qwen2.5-32B-Instruct | - | - | — | 64.7 t/s | 0.84 s |
LoRA/Qwen/Qwen2.5-72B-Instruct | - | - | — | 24.6 t/s | 3.37 s |
Pro/Qwen/Qwen2-7B-Instruct | - | - | — | 83.8 t/s | 0.60 s |
Pro/Qwen/Qwen2.5-Coder-7B-Instruct | - | - | — | 28.3 t/s | 0.63 s |
| - | - | — | 73.5 t/s | 0.71 s | |
Pro/THUDM/GLM-4.1V-9B-Thinking | - | - | — | 65.0 t/s | 15.30 s |
Qwen/Qwen2.5-72B-Instruct | - | - | — | 32.5 t/s | 0.79 s |
Qwen/Qwen2.5-72B-Instruct-128K | - | - | — | 20.3 t/s | 0.90 s |
Qwen/Qwen2.5-7B-Instruct | - | - | — | 39.4 t/s | 1.40 s |
Qwen/Qwen2.5-Coder-32B-Instruct | - | - | — | 23.6 t/s | 1.18 s |
Qwen/Qwen2.5-VL-72B-Instruct | - | - | — | 28.1 t/s | 0.92 s |
Qwen/Qwen3-235B-A22B-Instruct-2507 | - | - | — | 21.0 t/s | 1.49 s |
Qwen/Qwen3-Coder-30B-A3B-Instruct | - | - | — | 38.2 t/s | 0.78 s |
Qwen/Qwen3-VL-8B-Instruct | - | - | — | 106.5 t/s | 0.92 s |
tencent/Hunyuan-MT-7B | - | - | — | 46.6 t/s | 1.32 s |
| - | - | — | 72.0 t/s | 0.95 s | |
| - | - | — | 74.3 t/s | 0.60 s | |
THUDM/GLM-4.1V-9B-Thinking | - | - | — | 41.2 t/s | 23.48 s |
THUDM/GLM-Z1-9B-0414 | - | - | — | 176.0 t/s | 13.40 s |
Vendor-A/Qwen/Qwen2.5-72B-Instruct | - | - | — | 27.7 t/s | 1.25 s |
| - | - | 10010086100 | 21.4 t/s | 5.27 s | |
| - | - | — | 20.9 t/s | 8.59 s | |
| - | - | — | 34.4 t/s | 22.51 s | |
| - | - | — | 24.2 t/s | 0.98 s | |
| - | - | — | 60.6 t/s | 15.38 s | |
| - | - | — | 73.0 t/s | 6.15 s | |
| - | - | — | 85.7 t/s | 0.39 s | |
| - | - | — | 29.0 t/s | 29.09 s | |
| - | - | — | 22.5 t/s | 9.04 s | |
| - | - | — | 15.0 t/s | 62.39 s | |
| - | - | — | 67.7 t/s | 10.66 s | |
| - | - | — | 11.5 t/s | 60.01 s | |
| - | - | — | 68.6 t/s | 9.89 s |
Showing 62 of 62 model rows
| Time | Model | Speed | Latency |
|---|---|---|---|
| Jun 21, 08:27 PM | zai-org/GLM-5.2 | 52.06 tok/s | 10.99s |
| Jun 18, 05:23 AM | Qwen/Qwen3.6-27B | 36.08 tok/s | 41.10s |
| Jun 15, 02:02 AM | deepseek-ai/DeepSeek-V3.2 | 17.94 tok/s | 2.29s |
| Jun 14, 04:02 PM | Qwen/Qwen3.5-35B-A3B | 136.58 tok/s | 6.06s |
| Jun 14, 04:01 PM | nex-agi/Nex-N2-Pro | 83.12 tok/s | 1.16s |
| May 28, 01:20 PM | deepseek-ai/DeepSeek-V4-Flash | 68.08 tok/s | 2.00s |
| May 28, 01:19 PM | deepseek-ai/DeepSeek-V3.2 | 23.22 tok/s | 1.05s |
| May 24, 10:53 AM | deepseek-ai/deepseek-v4-flash | 38.38 tok/s | 0.49s |
| May 20, 03:41 AM | deepseek-ai/DeepSeek-V4-Flash | 37.88 tok/s | 43.15s |
| May 11, 12:11 PM | Qwen/Qwen3.5-4B | 99.84 tok/s | 9.04s |
Compare SiliconFlow alternatives against 6 nearby API providers using 358 LMSpeed signals across shared model coverage, pricing, benchmark speed, uptime, and free-model availability.
| Provider | Why compare | Models | Free | Avg price | Speed | 30d uptime |
|---|---|---|---|---|---|---|
| SiliconFlow siliconflow Provides cost-effective generative AI cloud services based on open-source models for text, image, video, and audio generation. | Current provider baseline | 60 | 0 | N/A | 53 tok/s | 80.8% |
| OpenRouter openrouter A unified API interface providing access to over 300 models from 60+ providers, including OpenAI, Anthropic, and Google. |
| 221 | 0 | N/A | 86 tok/s | 99.6% |
nvidia-nim NVIDIA NIM provides optimized AI model inference APIs for LLMs, vision, and embedding models through NVIDIA cloud infrastructure. |
| 53 | 0 | N/A | 66 tok/s | 99.4% |
api-kriora-com Provides OpenAI-compatible APIs and managed GPU instances for deploying and scaling open-source AI models. |
| 9 | 0 | N/A | 565 tok/s | 99.8% |
api-fireworks-ai Fireworks AI provides a cloud platform for running and fine-tuning open-source AI models with optimized inference for production applications. |
| 5 | 0 | N/A | 139 tok/s | 99.8% |
550c-cloud 共绩算力 (550c.cloud) is a shared computing platform providing Ollama-hosted open-source AI model inference via OpenAI-compatible API. |
| 4 | 0 | N/A | 112 tok/s | 84.8% |
www-sophnet-com An AI development platform offering API access to models like DeepSeek and Qwen for tasks such as text generation and code creation. |
| 3 | 0 | N/A | 133 tok/s | 99.6% |
