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{
"qwen2-7b-instruct": {
"feature": "qwen2-7b-instruct \u2012 Chinese & English LLM for language, coding, mathematics and reasoning; costs $0.20 per M input tokens and $0.20 per M output tokens on Together AI.",
"input_price": 0.2,
"output_price": 0.2,
"model": "qwen/qwen2-7b-instruct"
},
"qwen2-7b-instruct_think": {
"feature": "qwen2-7b-instruct \u2012 Chinese & English LLM for language, coding, mathematics and reasoning; costs $0.20 per M input tokens and $0.20 per M output tokens on Together AI.",
"input_price": 0.2,
"output_price": 0.2,
"model": "qwen/qwen2-7b-instruct"
},
"qwen2.5-7b-instruct": {
"feature": "qwen2.5-7b-instruct \u2012 upgraded Qwen with stronger multilingual capability; priced at $0.30 /M input and $0.30 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "qwen/qwen2.5-7b-instruct"
},
"qwen2.5-7b-instruct_think": {
"feature": "qwen2.5-7b-instruct \u2012 upgraded Qwen with stronger multilingual capability; priced at $0.30 /M input and $0.30 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "qwen/qwen2.5-7b-instruct"
},
"gemma-7b": {
"feature": "gemma-7b \u2012 Google\u2019s lightweight 7 B model for text and code; Together cost is $0.20 /M input and $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "google/gemma-7b"
},
"gemma-7b_think": {
"feature": "gemma-7b \u2012 Google\u2019s lightweight 7 B model for text and code; Together cost is $0.20 /M input and $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "google/gemma-7b"
},
"codegemma-7b": {
"feature": "codegemma-7b \u2012 Gemma variant focused on code generation & completion; $0.20 /M input, $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "google/codegemma-7b"
},
"codegemma-7b_think": {
"feature": "codegemma-7b \u2012 Gemma variant focused on code generation & completion; $0.20 /M input, $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "google/codegemma-7b"
},
"gemma-2-9b-it": {
"feature": "gemma-2-9b-it \u2012 2.9 B instruction-tuned Gemma for general text; ultralow $0.10 /M input and $0.10 /M output.",
"input_price": 0.1,
"output_price": 0.1,
"model": "google/gemma-2-9b-it"
},
"gemma-2-9b-it_think": {
"feature": "gemma-2-9b-it \u2012 2.9 B instruction-tuned Gemma for general text; ultralow $0.10 /M input and $0.10 /M output.",
"input_price": 0.1,
"output_price": 0.1,
"model": "google/gemma-2-9b-it"
},
"llama-3.1-8b-instruct": {
"feature": "llama-3.1-8b-instruct \u2012 Meta\u2019s 8 B Llama-3 series for chat & reasoning; $0.20 /M input and $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "meta/llama-3.1-8b-instruct"
},
"llama-3.1-8b-instruct_think": {
"feature": "llama-3.1-8b-instruct \u2012 Meta\u2019s 8 B Llama-3 series for chat & reasoning; $0.20 /M input and $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "meta/llama-3.1-8b-instruct"
},
"granite-3.0-8b-instruct": {
"feature": "granite-3.0-8b-instruct \u2012 IBM small LLM supporting RAG, summarization & code; $0.20 /M input, $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "ibm/granite-3.0-8b-instruct"
},
"granite-3.0-8b-instruct_think": {
"feature": "granite-3.0-8b-instruct \u2012 IBM small LLM supporting RAG, summarization & code; $0.20 /M input, $0.20 /M output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "ibm/granite-3.0-8b-instruct"
},
"llama3-chatqa-1.5-8b": {
"feature": "llama3-chatqa-1.5-8b \u2012 NVIDIA fine-tuned 8 B for QA & reasoning; $0.20 /M input and output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "nvidia/llama3-chatqa-1.5-8b"
},
"llama3-chatqa-1.5-8b_think": {
"feature": "llama3-chatqa-1.5-8b \u2012 NVIDIA fine-tuned 8 B for QA & reasoning; $0.20 /M input and output.",
"input_price": 0.2,
"output_price": 0.2,
"model": "nvidia/llama3-chatqa-1.5-8b"
},
"mistral-nemo-12b-instruct": {
"feature": "mistral-nemo-12b-instruct \u2012 12 B model combining Mistral and NeMo tech; $0.30 /M input, $0.30 /M output.",
"input_price": 0.3,
"output_price": 0.3,
"model": "nv-mistralai/mistral-nemo-12b-instruct"
},
"mistral-nemo-12b-instruct_think": {
"feature": "mistral-nemo-12b-instruct \u2012 12 B model combining Mistral and NeMo tech; $0.30 /M input, $0.30 /M output.",
"input_price": 0.3,
"output_price": 0.3,
"model": "nv-mistralai/mistral-nemo-12b-instruct"
},
"mistral-7b-instruct-v0.3": {
"feature": "mistral-7b-instruct-v0.3 \u2012 fast 7 B model for instruction following; $0.20 /M in & out.",
"input_price": 0.2,
"output_price": 0.2,
"model": "mistralai/mistral-7b-instruct-v0.3"
},
"mistral-7b-instruct-v0.3_think": {
"feature": "mistral-7b-instruct-v0.3 \u2012 fast 7 B model for instruction following; $0.20 /M in & out.",
"input_price": 0.2,
"output_price": 0.2,
"model": "mistralai/mistral-7b-instruct-v0.3"
},
"llama-3.3-nemotron-super-49b-v1": {
"feature": "llama-3.3-nemotron-super-49b-v1 \u2012 49 B Nemotron with high accuracy; $0.90 /M input and output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "nvidia/llama-3.3-nemotron-super-49b-v1"
},
"llama-3.3-nemotron-super-49b-v1_think": {
"feature": "llama-3.3-nemotron-super-49b-v1 \u2012 49 B Nemotron with high accuracy; $0.90 /M input and output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "nvidia/llama-3.3-nemotron-super-49b-v1"
},
"llama-3.1-nemotron-51b-instruct": {
"feature": "llama-3.1-nemotron-51b-instruct \u2012 51 B NVIDIA alignment model; $0.90 /M in & out.",
"input_price": 0.9,
"output_price": 0.9,
"model": "nvidia/llama-3.1-nemotron-51b-instruct"
},
"llama-3.1-nemotron-51b-instruct_think": {
"feature": "llama-3.1-nemotron-51b-instruct \u2012 51 B NVIDIA alignment model; $0.90 /M in & out.",
"input_price": 0.9,
"output_price": 0.9,
"model": "nvidia/llama-3.1-nemotron-51b-instruct"
},
"llama3-chatqa-1.5-70b": {
"feature": "llama3-chatqa-1.5-70b \u2012 70 B chat-optimized Llama; $0.90 /M input and output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "nvidia/llama3-chatqa-1.5-70b"
},
"llama3-chatqa-1.5-70b_think": {
"feature": "llama3-chatqa-1.5-70b \u2012 70 B chat-optimized Llama; $0.90 /M input and output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "nvidia/llama3-chatqa-1.5-70b"
},
"llama-3.1-70b-instruct": {
"feature": "llama-3.1-70b-instruct \u2012 Meta 70 B for complex conversations; $0.90 /M input/output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "meta/llama3-70b-instruct"
},
"llama-3.1-70b-instruct_think": {
"feature": "llama-3.1-70b-instruct \u2012 Meta 70 B for complex conversations; $0.90 /M input/output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "meta/llama3-70b-instruct"
},
"llama3-70b-instruct": {
"feature": "llama3-70b-instruct \u2012 alternate naming of Meta\u2019s 70 B; $0.90 /M input & output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "meta/llama-3.1-8b-instruct"
},
"llama3-70b-instruct_think": {
"feature": "llama3-70b-instruct \u2012 alternate naming of Meta\u2019s 70 B; $0.90 /M input & output.",
"input_price": 0.9,
"output_price": 0.9,
"model": "meta/llama-3.1-8b-instruct"
},
"granite-34b-code-instruct": {
"feature": "granite-34b-code-instruct \u2012 34 B IBM coder model; $0.80 /M input and output.",
"input_price": 0.8,
"output_price": 0.8,
"model": "ibm/granite-34b-code-instruct"
},
"granite-34b-code-instruct_think": {
"feature": "granite-34b-code-instruct \u2012 34 B IBM coder model; $0.80 /M input and output.",
"input_price": 0.8,
"output_price": 0.8,
"model": "ibm/granite-34b-code-instruct"
},
"mixtral-8x7b-instruct-v0.1": {
"feature": "mixtral-8\u00d77b-instruct-v0.1 \u2012 56 B MoE (8\u00d77 B) for creative text; $0.60 /M input/output.",
"input_price": 0.6,
"output_price": 0.6,
"model": "mistralai/mixtral-8x7b-instruct-v0.1"
},
"mixtral-8x7b-instruct-v0.1_think": {
"feature": "mixtral-8\u00d77b-instruct-v0.1 \u2012 56 B MoE (8\u00d77 B) for creative text; $0.60 /M input/output.",
"input_price": 0.6,
"output_price": 0.6,
"model": "mistralai/mixtral-8x7b-instruct-v0.1"
},
"deepseek-r1": {
"feature": "deepseek-r1 \u2012 671 B-param reasoning powerhouse; Together charges $3 /M input tokens and $7 /M output tokens.",
"input_price": 0.55,
"output_price": 2.19,
"model": "deepseek-ai/deepseek-r1"
},
"deepseek-r1_think": {
"feature": "deepseek-r1 \u2012 671 B-param reasoning powerhouse; Together charges $3 /M input tokens and $7 /M output tokens.",
"input_price": 0.55,
"output_price": 2.19,
"model": "deepseek-ai/deepseek-r1"
},
"mixtral-8x22b-instruct-v0.1": {
"feature": "mixtral-8\u00d722b-instruct-v0.1 \u2012 176 B MoE (8\u00d722 B); $1.20 /M input and output.",
"input_price": 1.2,
"output_price": 1.2,
"model": "mistralai/mixtral-8x22b-instruct-v0.1"
},
"mixtral-8x22b-instruct-v0.1_think": {
"feature": "mixtral-8\u00d722b-instruct-v0.1 \u2012 176 B MoE (8\u00d722 B); $1.20 /M input and output.",
"input_price": 1.2,
"output_price": 1.2,
"model": "mistralai/mixtral-8x22b-instruct-v0.1"
},
"palmyra-creative-122b": {
"feature": "palmyra-creative-122b \u2012 122 B parameter model from Writer, optimized for creative and marketing content generation; $1.80 /M input and $1.80 /M output.",
"input_price": 1.8,
"output_price": 1.8,
"model": "writer/palmyra-creative-122b"
},
"palmyra-creative-122b_think": {
"feature": "palmyra-creative-122b \u2012 122 B parameter model from Writer, optimized for creative and marketing content generation; $1.80 /M input and $1.80 /M output.",
"input_price": 1.8,
"output_price": 1.8,
"model": "writer/palmyra-creative-122b"
}
} |