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moonshotaiListed Jan 1

MoonshotAI: Kimi K2.5

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over…

262.1K contextImage inputTool callingNo reported score
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$0.50in$2.50out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/int4 · quantization=int4
deepseek-aiListed Dec 1

DeepSeek-V3.2

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a…

163.8K contextTool callingStructured outputNo reported score
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$0.259in$0.80out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
qwenListed Oct 6

Qwen: Qwen3 VL 30B A3B Thinking

Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Thinking variant enhances reasoning in STEM, math, and complex tasks.…

262.1K context30BImage inputTool callingNo reported score
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$0.29in$1.00out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
QwenListed Sep 30

Qwen3-VL-30B-A3B-Instruct

Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date. This generation delivers comprehensive upgrades across the board: superior text understanding & generation, deeper visual…

262.1K context30BImage inputTool callingNo reported score
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deepseekListed Sep 29

DeepSeek: DeepSeek V3.2 Exp

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained…

163.8K contextTool callingStructured outputNo reported score
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$0.27in$0.41out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
deepseekListed Sep 22

DeepSeek: DeepSeek V3.1 Terminus

DeepSeek-V3.1 Terminus is an update to DeepSeek V3.1 that maintains the model's original capabilities while addressing issues reported by users, including language consistency and agent capabilities,…

163.8K contextTool callingStructured outputNo reported score
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$0.27in$1.00out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
deepseek-aiListed Aug 21

DeepSeek-V3.1

DeepSeek-V3.1 is post-trained on the top of DeepSeek-V3.1-Base, which is built upon the original V3 base checkpoint through a two-phase long context extension approach, following the methodology outlined in…

163.8K contextTool callingStructured outputNo reported score
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$0.27in$1.00out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
openaiListed Aug 4

gpt-oss-20b

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for…

131.1K context20BTool callingStructured outputNo reported score
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$0.04in$0.18out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
openaiListed Aug 4

gpt-oss-120b

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. The model supports…

131.1K context120BTool callingStructured outputNo reported score
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$0.15in$0.60out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
qwenListed Jul 31

Qwen: Qwen3 Coder 30B A3B Instruct

Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and…

262.1K context30BTool callingStructured outputNo reported score
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$0.07in$0.28out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
qwenListed Jul 29

Qwen: Qwen3 30B A3B Instruct 2507

Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality…

262.1K context30BTool callingStructured outputNo reported score
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$0.09in$0.30out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
z-aiListed Jul 20

Z.ai: GLM 4.5 Air

GLM-4.5-Air is the lightweight variant of our latest flagship model family, also purpose-built for agent-centric applications. Like GLM-4.5, it adopts the Mixture-of-Experts (MoE) architecture but with a…

131.1K contextTool callingReasoningNo reported score
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$0.14in$0.86out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
tencentListed Jul 8

Tencent: Hunyuan A13B Instruct

Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive…

131.1K contextStructured outputReasoningNo reported score
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$0.14in$0.57out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
deepseekListed May 28

DeepSeek: R1 0528

May 28th update to the original DeepSeek R1 Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...

163.8K contextTool callingStructured outputNo reported score
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$0.50in$2.18out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
QwenListed Apr 27

Qwen3-32B

Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers…

131.1K context32BTool callingStructured outputNo reported score
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$0.14in$0.57out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8
deepseekListed Mar 24

DeepSeek: DeepSeek V3 0324

DeepSeek V3, a 685B-parameter, mixture-of-experts model, is the latest iteration of the flagship chat model family from the DeepSeek team. It succeeds the DeepSeek V3 model and performs really well...

163.8K contextTool callingStructured outputNo reported score
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$0.25in$1.00out/ 1M tokens · USDSiliconFlow · via OpenRoutersiliconflow/fp8 · quantization=fp8