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ModelCap

Inference provider

SiliconFlow: AI models and API pricing

Every tracked model SiliconFlow serves through OpenRouter, with SiliconFlow's own input and output price per 1M tokens, the context window it serves, disclosed quantization and measured endpoint uptime. Rows link to the model page, where every provider's deployment is listed side by side.

Snapshot as of 11 August 2026

SiliconFlow serves 23 tracked models through 23 endpoints as of 11 August 2026; the highest-ranked is GLM 5.2 (ModelCap Index #13); mean measured uptime is 98.74%.

Models served
23
On the ModelCap Index
15
Cheapest output price
$0.15/1M

Language models on SiliconFlow (23)

Ranked models first, in ModelCap Index order. Prices are the lowest SiliconFlow lists for the model; the endpoint count shows how many deployments carry it.

Language models served by SiliconFlow, with price, context, quantization and uptime
#ModelModelCap IndexInput $/1MOutput $/1MContextQuantizationUptime (30 min)Endpoints
1GLM 5.2Z.ai#1370.5$1.19$3.741Mfp899.86%1Open weights
2Gemma 4 31BGoogle#2062.8$0.13$0.40262Kfp894.00%1Open weights
3Gemma 4 26B A4BGoogle#2559.2$0.12$0.40262Kfp898.46%1Open weights
4Qwen3.6 27BQwen#3251.9$0.30$3.20262Kfp896.96%1Open weights
5Qwen3.5-122B-A10BQwen#3351.8$0.26$2.08262Kfp899.80%1Open weights
6Nex-N2-ProNex AGI#3847.4$0.50$2.50262K1Open weights
7Qwen3.6 35B A3BQwen#4146.3$0.20$1.60262Kfp899.29%1Open weights
8Qwen3 30B A3B Instruct 2507Qwen#4841.6$0.09$0.30262Kfp891.79%1Open weights
9GLM 4.5 AirZ.ai#5437.5$0.14$0.86131Kfp8100.0%1Open weights
10Hunyuan A13B InstructTencent#5637.4$0.14$0.57131Kfp81
11Qwen3 32BQwen#7229.2$0.14$0.57131Kfp899.76%1Open weights
12Qwen3 Coder 30B A3B InstructQwen#7428.4$0.07$0.28262Kfp8100.0%1Open weights
13Qwen3 VL 30B A3B ThinkingQwen#9025.7$0.29$1.00262Kfp81Open weights
14Kimi K2.7 CodeMoonshot AI#18921.5$0.859$3.80262Kfp81
15Qwen3 VL 30B A3B InstructQwen#2184.1$0.29$1.00262Kfp899.34%1Open weights
16Qwen3.5-9BQwen$0.10$0.15262Kfp898.75%1Open weights
17GLM 5Z.ai$0.95$2.55205Kfp899.90%1Open weights
18GLM 5.1Z.ai$1.19$3.74205Kfp8100.0%1Open weights
19Kimi K2.5Moonshot AI$0.45$2.25262Kint4100.0%1
20Kimi K2.6Moonshot AI$0.77$3.40262Kfp8100.0%1
21Qwen3.5-27BQwen$0.25$2.00262Kfp899.34%1Open weights
22Qwen3.5-35B-A3BQwen$0.24$1.80262Kfp81Open weights
23Step 3.5 FlashStepFun$0.10$0.30262Kfp8100.0%1Open weights

SiliconFlow on ModelCap: common questions

How many AI models does SiliconFlow serve?

23 tracked models as of 11 August 2026: 23 language models (15 with a public ModelCap Index position), across 23 live endpoints observed through OpenRouter.

What is the best model available on SiliconFlow?

GLM 5.2 from Z.ai is the highest-ranked language model SiliconFlow serves, at ModelCap Index position #13 and $3.74 per 1M output tokens on SiliconFlow. The table lists every model in Index order.

What is the cheapest model on SiliconFlow?

Qwen3.5-9B at $0.15 per 1M output tokens ($0.10 per 1M input), the lowest positive language-token price SiliconFlow lists. Free-tier endpoints, where present, show as $0 and are excluded from that comparison.

Which SiliconFlow model has the largest context window?

GLM 5.2, served with a 1M-token context window on SiliconFlow. Providers sometimes serve less than the model's published maximum, so the figure here is the provider's own.

How reliable is SiliconFlow?

Mean measured uptime across SiliconFlow endpoints is 98.74% over the last 30 minutes, as reported by OpenRouter at the time of the snapshot. Per-model uptime is in the table; it is a live operational signal, not a service-level guarantee.

Where do the SiliconFlow prices come from?

From the OpenRouter catalogue entry for each SiliconFlow endpoint, in USD per 1M tokens, re-observed on every ModelCap refresh. Where SiliconFlow exposes several deployments of one model at different prices, the table shows the lowest and notes the count; the model page lists each deployment.

How current is this page?

It re-renders within a minute of every dataset refresh; this snapshot was published 11 August 2026. Offers retained from a failed refresh are marked stale in the data and are not counted here.

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