{"json":[{"id":"meta-llama/Llama-3.3-70B-Instruct","name":"meta-llama/Llama-3.3-70B-Instruct","websiteUrl":"https://llama.meta.com/","modelUrl":"https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"meta-llama/Llama-3.3-70B-Instruct","description":"Ideal for everyday use. A fast and extremely capable model matching closed source models' capabilities. Now with the latest Llama 3.3 weights!","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/meta-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."},{"title":"Recipe help","prompt":"How do I make a delicious lemon cheesecake?"}],"parameters":{"temperature":0.6,"truncate":7167,"max_new_tokens":1024,"stop":["<|endoftext|>","<|eot_id|>"],"stop_sequences":["<|endoftext|>","<|eot_id|>"]},"preprompt":"","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":true},{"id":"Qwen/Qwen3-235B-A22B","name":"Qwen/Qwen3-235B-A22B","websiteUrl":"https://qwenlm.github.io/blog/qwen3/","modelUrl":"https://huggingface.co/Qwen/Qwen3-235B-A22B","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"Qwen/Qwen3-235B-A22B","description":"Qwen's flagship model featuring optional reasoning. Exceptional performance with benchmarks rivaling R1 and o1.","reasoning":true,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12) /nothink"},{"title":"Build a website","prompt":"Generate a snazzy static landing page for a local coffee shop using HTML and CSS. You can use tailwind using ."},{"title":"Larger number","prompt":"9.11 or 9.9 which number is larger?"}],"parameters":{"temperature":0.6,"stop":["<|endoftext|>","<|im_end|>"],"stop_sequences":["<|endoftext|>","<|im_end|>"]},"preprompt":"You are Qwen, created by Alibaba Cloud. You are a helpful assistant.","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":true},{"id":"Qwen/Qwen2.5-72B-Instruct","name":"Qwen/Qwen2.5-72B-Instruct","websiteUrl":"https://qwenlm.github.io/blog/qwen2.5/","modelUrl":"https://huggingface.co/Qwen/Qwen2.5-72B-Instruct","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"Qwen/Qwen2.5-72B-Instruct","description":"The latest Qwen open model with improved role-playing, long text generation and structured data understanding.","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."},{"title":"Recipe help","prompt":"How do I make a delicious lemon cheesecake?"}],"parameters":{"temperature":0.6,"truncate":28672,"max_new_tokens":3072,"stop":["<|endoftext|>","<|im_end|>"],"stop_sequences":["<|endoftext|>","<|im_end|>"]},"preprompt":"You are Qwen, created by Alibaba Cloud. You are a helpful assistant.","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":true},{"id":"CohereLabs/c4ai-command-r-plus-08-2024","name":"CohereLabs/c4ai-command-r-plus-08-2024","websiteUrl":"https://docs.cohere.com/docs/command-r-plus","modelUrl":"https://huggingface.co/CohereLabs/c4ai-command-r-plus-08-2024","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"CohereLabs/c4ai-command-r-plus-08-2024","description":"Cohere's largest language model, optimized for conversational interaction and tool use. Now with the 2024 update!","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/cohere-logo.png","promptExamples":[{"title":"Generate image","prompt":"Generate the portrait of a scientific mouse in its laboratory."},{"title":"Review code","prompt":"Review this pull request: https://github.com/huggingface/chat-ui/pull/1131/files"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."}],"parameters":{"temperature":0.3,"truncate":28672,"max_new_tokens":2048,"stop":["<|END_OF_TURN_TOKEN|>","<|im_end|>"],"stop_sequences":["<|END_OF_TURN_TOKEN|>","<|im_end|>"]},"preprompt":"","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":false},{"id":"deepseek-ai/DeepSeek-R1-Distill-Qwen-32B","name":"deepseek-ai/DeepSeek-R1-Distill-Qwen-32B","websiteUrl":"https://deepseek.com/","modelUrl":"https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"deepseek-ai/DeepSeek-R1-Distill-Qwen-32B","description":"The first reasoning model from DeepSeek, distilled into a 32B dense model. Outperforms o1-mini on multiple benchmarks.","reasoning":true,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/deepseek-logo.png","promptExamples":[{"title":"Rs in strawberry","prompt":"how many R in strawberry?"},{"title":"Larger number","prompt":"9.11 or 9.9 which number is larger?"},{"title":"Measuring 6 liters","prompt":"I have a 6- and a 12-liter jug. I want to measure exactly 6 liters."}],"parameters":{"stop_sequences":null},"preprompt":"","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":true},{"id":"nvidia/Llama-3.1-Nemotron-70B-Instruct-HF","name":"nvidia/Llama-3.1-Nemotron-70B-Instruct-HF","websiteUrl":"https://www.nvidia.com/","modelUrl":"https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"nvidia/Llama-3.1-Nemotron-70B-Instruct-HF","description":"Nvidia's latest Llama fine-tune, topping alignment benchmarks and optimized for instruction following.","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/nvidia-logo.png","promptExamples":[{"title":"Rs in strawberry","prompt":"how many R in strawberry?"},{"title":"Larger number","prompt":"9.11 or 9.9 which number is larger?"},{"title":"Measuring 6 liters","prompt":"I have a 6- and a 12-liter jug. I want to measure exactly 6 liters."}],"parameters":{"temperature":0.5,"truncate":28672,"max_new_tokens":2048,"stop":["<|eot_id|>","<|im_end|>"],"stop_sequences":["<|eot_id|>","<|im_end|>"]},"preprompt":"","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":false,"unlisted":false,"hasInferenceAPI":true},{"id":"Qwen/QwQ-32B","name":"Qwen/QwQ-32B","websiteUrl":"https://qwenlm.github.io/blog/qwq-32b/","modelUrl":"https://huggingface.co/Qwen/QwQ-32B","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"Qwen/QwQ-32B","description":"QwQ is the latest reasoning model released by the Qwen team, approaching the capabilities of R1 in benchmarks.","reasoning":true,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png","promptExamples":[{"title":"Rs in strawberry","prompt":"how many R in strawberry?"},{"title":"Larger number","prompt":"9.11 or 9.9 which number is larger?"},{"title":"Measuring 6 liters","prompt":"I have a 6- and a 12-liter jug. I want to measure exactly 6 liters."}],"parameters":{"stop_sequences":null},"preprompt":"You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step.","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":true},{"id":"google/gemma-3-27b-it","name":"google/gemma-3-27b-it","websiteUrl":"https://blog.google/technology/developers/gemma-3/","modelUrl":null,"tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"google/gemma-3-27b-it","description":"Google's latest open model with great multilingual performance, supports image inputs natively.","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/google-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."},{"title":"Recipe help","prompt":"How do I make a delicious lemon cheesecake?"}],"parameters":{"stop_sequences":null},"preprompt":"","multimodal":true,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":false},{"id":"mistralai/Mistral-Small-3.1-24B-Instruct-2503","name":"mistralai/Mistral-Small-3.1-24B-Instruct-2503","websiteUrl":"https://mistral.ai/news/mistral-nemo/","modelUrl":"https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"mistralai/Mistral-Small-3.1-24B-Instruct-2503","description":"A small model with good capabilities in language understanding and commonsense reasoning.","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/mistral-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."},{"title":"Recipe help","prompt":"How do I make a delicious lemon cheesecake?"}],"parameters":{"stop_sequences":null},"preprompt":"","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":false},{"id":"Qwen/Qwen2.5-VL-32B-Instruct","name":"Qwen/Qwen2.5-VL-32B-Instruct","websiteUrl":"https://qwenlm.github.io/blog/qwen2.5-vl/","modelUrl":"https://huggingface.co/Qwen/Qwen2.5-VL-32B-Instruct","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"Qwen/Qwen2.5-VL-32B-Instruct","description":"The latest multimodal model from Qwen! Supports image inputs natively.","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/qwen-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."},{"title":"Recipe help","prompt":"How do I make a delicious lemon cheesecake?"}],"parameters":{"stop_sequences":null},"preprompt":"","multimodal":true,"multimodalAcceptedMimetypes":null,"tools":false,"unlisted":false,"hasInferenceAPI":false},{"id":"microsoft/Phi-4","name":"microsoft/Phi-4","websiteUrl":"https://techcommunity.microsoft.com/blog/aiplatformblog/introducing-phi-4-microsoft%E2%80%99s-newest-small-language-model-specializing-in-comple/4357090","modelUrl":"https://huggingface.co/microsoft/Phi-4","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"microsoft/Phi-4","description":"One of the best small models, super fast for simple tasks.","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/microsoft-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."},{"title":"Recipe help","prompt":"How do I make a delicious lemon cheesecake?"}],"parameters":{"temperature":0.6,"truncate":28672,"max_new_tokens":3072,"stop":["<|end|>","<|endoftext|>","<|assistant|>"],"stop_sequences":["<|end|>","<|endoftext|>","<|assistant|>"]},"preprompt":"","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":false},{"id":"NousResearch/Hermes-3-Llama-3.1-8B","name":"NousResearch/Hermes-3-Llama-3.1-8B","websiteUrl":"https://nousresearch.com/","modelUrl":"https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B","tokenizer":null,"datasetName":null,"datasetUrl":null,"displayName":"NousResearch/Hermes-3-Llama-3.1-8B","description":"Nous Research's latest Hermes 3 release in 8B size. Follows instruction closely.","reasoning":false,"logoUrl":"https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/nous-logo.png","promptExamples":[{"title":"Write an email","prompt":"As a restaurant owner, write a professional email to the supplier to get these products every week: \n\n- Wine (x10)\n- Eggs (x24)\n- Bread (x12)"},{"title":"Code a game","prompt":"Code a basic snake game in python, give explanations for each step."},{"title":"Recipe help","prompt":"How do I make a delicious lemon cheesecake?"}],"parameters":{"temperature":0.6,"truncate":14336,"max_new_tokens":1536,"stop":["<|im_end|>"],"stop_sequences":["<|im_end|>"]},"preprompt":"","multimodal":false,"multimodalAcceptedMimetypes":null,"tools":true,"unlisted":false,"hasInferenceAPI":false}],"meta":{"values":{"0.tokenizer":["undefined"],"0.datasetName":["undefined"],"0.datasetUrl":["undefined"],"0.multimodalAcceptedMimetypes":["undefined"],"1.tokenizer":["undefined"],"1.datasetName":["undefined"],"1.datasetUrl":["undefined"],"1.multimodalAcceptedMimetypes":["undefined"],"2.tokenizer":["undefined"],"2.datasetName":["undefined"],"2.datasetUrl":["undefined"],"2.multimodalAcceptedMimetypes":["undefined"],"3.tokenizer":["undefined"],"3.datasetName":["undefined"],"3.datasetUrl":["undefined"],"3.multimodalAcceptedMimetypes":["undefined"],"4.tokenizer":["undefined"],"4.datasetName":["undefined"],"4.datasetUrl":["undefined"],"4.parameters.stop_sequences":["undefined"],"4.multimodalAcceptedMimetypes":["undefined"],"5.tokenizer":["undefined"],"5.datasetName":["undefined"],"5.datasetUrl":["undefined"],"5.multimodalAcceptedMimetypes":["undefined"],"6.tokenizer":["undefined"],"6.datasetName":["undefined"],"6.datasetUrl":["undefined"],"6.parameters.stop_sequences":["undefined"],"6.multimodalAcceptedMimetypes":["undefined"],"7.modelUrl":["undefined"],"7.tokenizer":["undefined"],"7.datasetName":["undefined"],"7.datasetUrl":["undefined"],"7.parameters.stop_sequences":["undefined"],"7.multimodalAcceptedMimetypes":["undefined"],"8.tokenizer":["undefined"],"8.datasetName":["undefined"],"8.datasetUrl":["undefined"],"8.parameters.stop_sequences":["undefined"],"8.multimodalAcceptedMimetypes":["undefined"],"9.tokenizer":["undefined"],"9.datasetName":["undefined"],"9.datasetUrl":["undefined"],"9.parameters.stop_sequences":["undefined"],"9.multimodalAcceptedMimetypes":["undefined"],"10.tokenizer":["undefined"],"10.datasetName":["undefined"],"10.datasetUrl":["undefined"],"10.multimodalAcceptedMimetypes":["undefined"],"11.tokenizer":["undefined"],"11.datasetName":["undefined"],"11.datasetUrl":["undefined"],"11.multimodalAcceptedMimetypes":["undefined"]},"referentialEqualities":{"0.parameters.stop":["0.parameters.stop_sequences"],"1.parameters.stop":["1.parameters.stop_sequences"],"2.parameters.stop":["2.parameters.stop_sequences"],"3.parameters.stop":["3.parameters.stop_sequences"],"5.parameters.stop":["5.parameters.stop_sequences"],"10.parameters.stop":["10.parameters.stop_sequences"],"11.parameters.stop":["11.parameters.stop_sequences"]}}}