danielrosehill/Open-Router-API-Pricing-Analysis huggingface dataset:
Model: Google: Gemma 3 12B (free)
Vendor: Google
Hugging Face ID: google/gemma-3-12b-it
Description: Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 12B is the second largest in the family of Gemma 3 models after [Gemma 3 27B](google/gemma-3-27b-it)
Context length: 32768 tokens
Tokenizer: Gemini
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 0.0
Completion price per 1M tokens (USD): 0.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.0
Output/input cost ratio: 0.0
Supported parameters: max_tokens, seed, temperature, top_p
Model: Google: Gemma 3 12B
Vendor: Google
Hugging Face ID: google/gemma-3-12b-it
Description: Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 12B is the second largest in the family of Gemma 3 models after [Gemma 3 27B](google/gemma-3-27b-it)
Context length: 131072 tokens
Tokenizer: Gemini
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 131072.0
Prompt price per 1M tokens (USD): 0.03
Completion price per 1M tokens (USD): 0.0999999999999999
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.065
Output/input cost ratio: 3.33
Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: Cohere: Command A
Vendor: Cohere
Hugging Face ID: CohereForAI/c4ai-command-a-03-2025
Description: Command A is an open-weights 111B parameter model with a 256k context window focused on delivering great performance across agentic, multilingual, and coding use cases.
Compared to other leading proprietary and open-weights models Command A delivers maximum performance with minimum hardware costs, excelling on business-critical agentic and multilingual tasks.
Context length: 256000 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 2.5
Completion price per 1M tokens (USD): 10.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 6.25
Output/input cost ratio: 4.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: OpenAI: GPT-4o-mini Search Preview
Vendor: OpenAI
Description: GPT-4o mini Search Preview is a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries.
Context length: 128000 tokens
Tokenizer: GPT
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 16384.0
Prompt price per 1M tokens (USD): 0.15
Completion price per 1M tokens (USD): 0.6
Image price (USD): 0.000217
Request price (USD): 0.0275
Median price per 1M tokens (USD): 0.375
Output/input cost ratio: 4.0
Supported parameters: max_tokens, response_format, structured_outputs, web_search_options
Model: OpenAI: GPT-4o Search Preview
Vendor: OpenAI
Description: GPT-4o Search Previewis a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries.
Context length: 128000 tokens
Tokenizer: GPT
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 16384.0
Prompt price per 1M tokens (USD): 2.5
Completion price per 1M tokens (USD): 10.0
Image price (USD): 0.003613
Request price (USD): 0.035
Median price per 1M tokens (USD): 6.25
Output/input cost ratio: 4.0
Supported parameters: max_tokens, response_format, structured_outputs, web_search_options
Model: Google: Gemma 3 27B (free)
Vendor: Google
Description: Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to [Gemma 2](google/gemma-2-27b-it)
Context length: 131072 tokens
Tokenizer: Gemini
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Prompt price per 1M tokens (USD): 0.0
Completion price per 1M tokens (USD): 0.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.0
Output/input cost ratio: 0.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: Google: Gemma 3 27B
Vendor: Google
Description: Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to [Gemma 2](google/gemma-2-27b-it)
Context length: 131072 tokens
Tokenizer: Gemini
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 16384.0
Prompt price per 1M tokens (USD): 0.09
Completion price per 1M tokens (USD): 0.16
Image price (USD): 2.56e-05
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.125
Output/input cost ratio: 1.78
Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p
Model: TheDrummer: Skyfall 36B V2
Vendor: TheDrummer
Hugging Face ID: TheDrummer/Skyfall-36B-v2
Description: Skyfall 36B v2 is an enhanced iteration of Mistral Small 2501, specifically fine-tuned for improved creativity, nuanced writing, role-playing, and coherent storytelling.
Context length: 32768 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 32768.0
Prompt price per 1M tokens (USD): 0.5
Completion price per 1M tokens (USD): 0.7999999999999999
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.6499999999999999
Output/input cost ratio: 1.6
Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, seed, stop, temperature, top_k, top_p
Model: Microsoft: Phi 4 Multimodal Instruct
Vendor: Microsoft
Hugging Face ID: microsoft/Phi-4-multimodal-instruct
Description: Phi-4 Multimodal Instruct is a versatile 5.6B parameter foundation model that combines advanced reasoning and instruction-following capabilities across both text and visual inputs, providing accurate text outputs. The unified architecture enables efficient, low-latency inference, suitable for edge and mobile deployments. Phi-4 Multimodal Instruct supports text inputs in multiple languages including Arabic, Chinese, English, French, German, Japanese, Spanish, and more, with visual input optimized primarily for English. It delivers impressive performance on multimodal tasks involving mathematical, scientific, and document reasoning, providing developers and enterprises a powerful yet compact model for sophisticated interactive applications. For more information, see the [Phi-4 Multimodal blog post](https://azure.microsoft.com/en-us/blog/empowering-innovation-the-next-generation-of-the-phi-family/).

Context length: 131072 tokens
Tokenizer: Other
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Prompt price per 1M tokens (USD): 0.0499999999999999
Completion price per 1M tokens (USD): 0.0999999999999999
Image price (USD): 0.00017685
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.075
Output/input cost ratio: 2.0
Supported parameters: frequency_penalty, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, temperature, top_k, top_p
Model: Perplexity: Sonar Reasoning Pro
Vendor: Perplexity
Description: Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro)

Sonar Reasoning Pro is a premier reasoning model powered by DeepSeek R1 with Chain of Thought (CoT). Designed for advanced use cases, it supports in-depth, multi-step queries with a larger context window and can surface more citations per search, enabling more comprehensive and extensible responses.
Context length: 128000 tokens
Tokenizer: Other
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Prompt price per 1M tokens (USD): 2.0
Completion price per 1M tokens (USD): 8.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 5.0
Output/input cost ratio: 4.0
Supported parameters: frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, temperature, top_k, top_p, web_search_options
Model: Perplexity: Sonar Pro
Vendor: Perplexity
Description: Note: Sonar Pro pricing includes Perplexity search pricing. See [details here](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-reasoning-pro-and-sonar-pro)

For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibility, like double the number of citations per search as Sonar on average. Plus, with a larger context window, it can handle longer and more nuanced searches and follow-up questions. 
Context length: 200000 tokens
Tokenizer: Other
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 8000.0
Prompt price per 1M tokens (USD): 3.0
Completion price per 1M tokens (USD): 15.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 9.0
Output/input cost ratio: 5.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, temperature, top_k, top_p, web_search_options
Model: Perplexity: Sonar Deep Research
Vendor: Perplexity
Description: Sonar Deep Research is a research-focused model designed for multi-step retrieval, synthesis, and reasoning across complex topics. It autonomously searches, reads, and evaluates sources, refining its approach as it gathers information. This enables comprehensive report generation across domains like finance, technology, health, and current events.

Notes on Pricing ([Source](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-deep-research)) 
- Input tokens comprise of Prompt tokens (user prompt) + Citation tokens (these are processed tokens from running searches)
- Deep Research runs multiple searches to conduct exhaustive research. Searches are priced at $5/1000 searches. A request that does 30 searches will cost $0.15 in this step.
- Reasoning is a distinct step in Deep Research since it does extensive automated reasoning through all the material it gathers during its research phase. Reasoning tokens here are a bit different than the CoTs in the answer - these are tokens that we use to reason through the research material prior to generating the outputs via the CoTs. Reasoning tokens are priced at $3/1M tokens
Context length: 128000 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 2.0
Completion price per 1M tokens (USD): 8.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 5.0
Output/input cost ratio: 4.0
Supported parameters: frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, temperature, top_k, top_p, web_search_options
Model: Qwen: QwQ 32B
Vendor: Qwen
Hugging Face ID: Qwen/QwQ-32B
Description: QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problems. QwQ-32B is the medium-sized reasoning model, which is capable of achieving competitive performance against state-of-the-art reasoning models, e.g., DeepSeek-R1, o1-mini.
Context length: 32768 tokens
Tokenizer: Qwen
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.15
Completion price per 1M tokens (USD): 0.3999999999999999
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.2749999999999999
Output/input cost ratio: 2.67
Supported parameters: frequency_penalty, include_reasoning, logit_bias, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p
Model: Google: Gemini 2.0 Flash Lite
Vendor: Google
Description: Gemini 2.0 Flash Lite offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5), all at extremely economical token prices.
Context length: 1048576 tokens
Tokenizer: Gemini
Modality: text+image->text
Input modalities: text, image, file, audio
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 0.075
Completion price per 1M tokens (USD): 0.3
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.1875
Output/input cost ratio: 4.0
Supported parameters: max_tokens, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_p
Model: Anthropic: Claude 3.7 Sonnet (thinking)
Vendor: Anthropic
Description: Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and extended, step-by-step processing for complex tasks. The model demonstrates notable improvements in coding, particularly in front-end development and full-stack updates, and excels in agentic workflows, where it can autonomously navigate multi-step processes. 

Claude 3.7 Sonnet maintains performance parity with its predecessor in standard mode while offering an extended reasoning mode for enhanced accuracy in math, coding, and instruction-following tasks.

Read more at the [blog post here](https://www.anthropic.com/news/claude-3-7-sonnet)
Context length: 200000 tokens
Tokenizer: Claude
Modality: text+image->text
Input modalities: text, image, file
Output modalities: text
Max completion tokens (top provider): 64000.0
Prompt price per 1M tokens (USD): 3.0
Completion price per 1M tokens (USD): 15.0
Image price (USD): 0.0048
Request price (USD): 0.0
Median price per 1M tokens (USD): 9.0
Output/input cost ratio: 5.0
Supported parameters: include_reasoning, max_tokens, reasoning, stop, temperature, tool_choice, tools, top_p
Model: Anthropic: Claude 3.7 Sonnet
Vendor: Anthropic
Description: Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and extended, step-by-step processing for complex tasks. The model demonstrates notable improvements in coding, particularly in front-end development and full-stack updates, and excels in agentic workflows, where it can autonomously navigate multi-step processes. 

Claude 3.7 Sonnet maintains performance parity with its predecessor in standard mode while offering an extended reasoning mode for enhanced accuracy in math, coding, and instruction-following tasks.

Read more at the [blog post here](https://www.anthropic.com/news/claude-3-7-sonnet)
Context length: 200000 tokens
Tokenizer: Claude
Modality: text+image->text
Input modalities: text, image, file
Output modalities: text
Max completion tokens (top provider): 64000.0
Prompt price per 1M tokens (USD): 3.0
Completion price per 1M tokens (USD): 15.0
Image price (USD): 0.0048
Request price (USD): 0.0
Median price per 1M tokens (USD): 9.0
Output/input cost ratio: 5.0
Supported parameters: include_reasoning, max_tokens, reasoning, stop, temperature, tool_choice, tools, top_k, top_p
Model: Mistral: Saba
Vendor: Mistral AI
Description: Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional datasets, it supports multiple Indian-origin languages—including Tamil and Malayalam—alongside Arabic. This makes it a versatile option for a range of regional and multilingual applications. Read more at the blog post [here](https://mistral.ai/en/news/mistral-saba)
Context length: 32768 tokens
Tokenizer: Mistral
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.1999999999999999
Completion price per 1M tokens (USD): 0.6
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.3999999999999999
Output/input cost ratio: 3.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_p
Model: Llama Guard 3 8B
Vendor: Meta
Hugging Face ID: meta-llama/Llama-Guard-3-8B
Description: Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM – it generates text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated.

Llama Guard 3 was aligned to safeguard against the MLCommons standardized hazards taxonomy and designed to support Llama 3.1 capabilities. Specifically, it provides content moderation in 8 languages, and was optimized to support safety and security for search and code interpreter tool calls.

Context length: 131072 tokens
Tokenizer: Llama3
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.02
Completion price per 1M tokens (USD): 0.06
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.04
Output/input cost ratio: 3.0
Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, temperature, top_k, top_p
Model: OpenAI: o3 Mini High
Vendor: OpenAI
Description: OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. 

o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities.

The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.
Context length: 200000 tokens
Tokenizer: GPT
Modality: text->text
Input modalities: text, file
Output modalities: text
Max completion tokens (top provider): 100000.0
Prompt price per 1M tokens (USD): 1.1
Completion price per 1M tokens (USD): 4.4
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 2.75
Output/input cost ratio: 4.0
Supported parameters: max_tokens, response_format, seed, structured_outputs, tool_choice, tools
Model: Google: Gemini 2.0 Flash
Vendor: Google
Description: Gemini Flash 2.0 offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5). It introduces notable enhancements in multimodal understanding, coding capabilities, complex instruction following, and function calling. These advancements come together to deliver more seamless and robust agentic experiences.
Context length: 1048576 tokens
Tokenizer: Gemini
Modality: text+image->text
Input modalities: text, image, file, audio
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 0.0999999999999999
Completion price per 1M tokens (USD): 0.3999999999999999
Image price (USD): 2.58e-05
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.2499999999999999
Output/input cost ratio: 4.0
Supported parameters: max_tokens, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_p
Model: Qwen: Qwen VL Plus
Vendor: Qwen
Description: Qwen's Enhanced Large Visual Language Model. Significantly upgraded for detailed recognition capabilities and text recognition abilities, supporting ultra-high pixel resolutions up to millions of pixels and extreme aspect ratios for image input. It delivers significant performance across a broad range of visual tasks.

Context length: 7500 tokens
Tokenizer: Qwen
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 1500.0
Prompt price per 1M tokens (USD): 0.21
Completion price per 1M tokens (USD): 0.63
Image price (USD): 0.0002688
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.42
Output/input cost ratio: 3.0
Supported parameters: max_tokens, presence_penalty, response_format, seed, temperature, top_p
Model: AionLabs: Aion-1.0
Vendor: Aion Labs
Description: Aion-1.0 is a multi-model system designed for high performance across various tasks, including reasoning and coding. It is built on DeepSeek-R1, augmented with additional models and techniques such as Tree of Thoughts (ToT) and Mixture of Experts (MoE). It is Aion Lab's most powerful reasoning model.
Context length: 131072 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 32768.0
Prompt price per 1M tokens (USD): 4.0
Completion price per 1M tokens (USD): 8.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 6.0
Output/input cost ratio: 2.0
Supported parameters: include_reasoning, max_tokens, reasoning, temperature, top_p
Model: AionLabs: Aion-1.0-Mini
Vendor: Aion Labs
Hugging Face ID: FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-32B-Preview
Description: Aion-1.0-Mini 32B parameter model is a distilled version of the DeepSeek-R1 model, designed for strong performance in reasoning domains such as mathematics, coding, and logic. It is a modified variant of a FuseAI model that outperforms R1-Distill-Qwen-32B and R1-Distill-Llama-70B, with benchmark results available on its [Hugging Face page](https://huggingface.co/FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-32B-Preview), independently replicated for verification.
Context length: 131072 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 32768.0
Prompt price per 1M tokens (USD): 0.7
Completion price per 1M tokens (USD): 1.4
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 1.0499999999999998
Output/input cost ratio: 2.0
Supported parameters: include_reasoning, max_tokens, reasoning, temperature, top_p
Model: AionLabs: Aion-RP 1.0 (8B)
Vendor: Aion Labs
Description: Aion-RP-Llama-3.1-8B ranks the highest in the character evaluation portion of the RPBench-Auto benchmark, a roleplaying-specific variant of Arena-Hard-Auto, where LLMs evaluate each other’s responses. It is a fine-tuned base model rather than an instruct model, designed to produce more natural and varied writing.
Context length: 32768 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 32768.0
Prompt price per 1M tokens (USD): 0.1999999999999999
Completion price per 1M tokens (USD): 0.1999999999999999
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.1999999999999999
Output/input cost ratio: 1.0
Supported parameters: max_tokens, temperature, top_p
Model: Qwen: Qwen VL Max
Vendor: Qwen
Description: Qwen VL Max is a visual understanding model with 7500 tokens context length. It excels in delivering optimal performance for a broader spectrum of complex tasks.

Context length: 131072 tokens
Tokenizer: Qwen
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 0.7999999999999999
Completion price per 1M tokens (USD): 3.2
Image price (USD): 0.001024
Request price (USD): 0.0
Median price per 1M tokens (USD): 2.0
Output/input cost ratio: 4.0
Supported parameters: max_tokens, presence_penalty, response_format, seed, temperature, tool_choice, tools, top_p
Model: Qwen: Qwen-Turbo
Vendor: Qwen
Description: Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.
Context length: 1000000 tokens
Tokenizer: Qwen
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 0.0499999999999999
Completion price per 1M tokens (USD): 0.1999999999999999
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.1249999999999999
Output/input cost ratio: 4.0
Supported parameters: max_tokens, presence_penalty, response_format, seed, temperature, tool_choice, tools, top_p
Model: Qwen: Qwen2.5 VL 72B Instruct
Vendor: Qwen
Hugging Face ID: Qwen/Qwen2.5-VL-72B-Instruct
Description: Qwen2.5-VL is proficient in recognizing common objects such as flowers, birds, fish, and insects. It is also highly capable of analyzing texts, charts, icons, graphics, and layouts within images.
Context length: 32768 tokens
Tokenizer: Qwen
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 32768.0
Prompt price per 1M tokens (USD): 0.08
Completion price per 1M tokens (USD): 0.33
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.205
Output/input cost ratio: 4.12
Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: Qwen: Qwen-Plus
Vendor: Qwen
Description: Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.
Context length: 131072 tokens
Tokenizer: Qwen
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 0.3999999999999999
Completion price per 1M tokens (USD): 1.2
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.7999999999999999
Output/input cost ratio: 3.0
Supported parameters: max_tokens, presence_penalty, response_format, seed, temperature, tool_choice, tools, top_p
Model: Qwen: Qwen-Max 
Vendor: Qwen
Description: Qwen-Max, based on Qwen2.5, provides the best inference performance among [Qwen models](/qwen), especially for complex multi-step tasks. It's a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-trained with curated Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) methodologies. The parameter count is unknown.
Context length: 32768 tokens
Tokenizer: Qwen
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 8192.0
Prompt price per 1M tokens (USD): 1.6
Completion price per 1M tokens (USD): 6.4
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 4.0
Output/input cost ratio: 4.0
Supported parameters: max_tokens, presence_penalty, response_format, seed, temperature, tool_choice, tools, top_p
Model: OpenAI: o3 Mini
Vendor: OpenAI
Description: OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding.

This model supports the `reasoning_effort` parameter, which can be set to "high", "medium", or "low" to control the thinking time of the model. The default is "medium". OpenRouter also offers the model slug `openai/o3-mini-high` to default the parameter to "high".

The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities.

The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.
Context length: 200000 tokens
Tokenizer: GPT
Modality: text->text
Input modalities: text, file
Output modalities: text
Max completion tokens (top provider): 100000.0
Prompt price per 1M tokens (USD): 1.1
Completion price per 1M tokens (USD): 4.4
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 2.75
Output/input cost ratio: 4.0
Supported parameters: max_tokens, response_format, seed, structured_outputs, tool_choice, tools
Model: Mistral: Mistral Small 3 (free)
Vendor: Mistral AI
Hugging Face ID: mistralai/Mistral-Small-24B-Instruct-2501
Description: Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed for efficient local deployment.

The model achieves 81% accuracy on the MMLU benchmark and performs competitively with larger models like Llama 3.3 70B and Qwen 32B, while operating at three times the speed on equivalent hardware. [Read the blog post about the model here.](https://mistral.ai/news/mistral-small-3/)
Context length: 32768 tokens
Tokenizer: Mistral
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.0
Completion price per 1M tokens (USD): 0.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.0
Output/input cost ratio: 0.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, repetition_penalty, seed, stop, temperature, top_k, top_p
Model: Mistral: Mistral Small 3
Vendor: Mistral AI
Hugging Face ID: mistralai/Mistral-Small-24B-Instruct-2501
Description: Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed for efficient local deployment.

The model achieves 81% accuracy on the MMLU benchmark and performs competitively with larger models like Llama 3.3 70B and Qwen 32B, while operating at three times the speed on equivalent hardware. [Read the blog post about the model here.](https://mistral.ai/news/mistral-small-3/)
Context length: 32768 tokens
Tokenizer: Mistral
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 16384.0
Prompt price per 1M tokens (USD): 0.0499999999999999
Completion price per 1M tokens (USD): 0.08
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.065
Output/input cost ratio: 1.6
Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p
Model: DeepSeek: R1 Distill Qwen 32B
Vendor: DeepSeek
Hugging Face ID: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
Description: DeepSeek R1 Distill Qwen 32B is a distilled large language model based on [Qwen 2.5 32B](https://huggingface.co/Qwen/Qwen2.5-32B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models.\n\nOther benchmark results include:\n\n- AIME 2024 pass@1: 72.6\n- MATH-500 pass@1: 94.3\n- CodeForces Rating: 1691\n\nThe model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.
Context length: 131072 tokens
Tokenizer: Qwen
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.27
Completion price per 1M tokens (USD): 0.27
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.27
Output/input cost ratio: 1.0
Supported parameters: frequency_penalty, include_reasoning, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: DeepSeek: R1 Distill Qwen 14B
Vendor: DeepSeek
Hugging Face ID: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
Description: DeepSeek R1 Distill Qwen 14B is a distilled large language model based on [Qwen 2.5 14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It outperforms OpenAI's o1-mini across various benchmarks, achieving new state-of-the-art results for dense models.

Other benchmark results include:

- AIME 2024 pass@1: 69.7
- MATH-500 pass@1: 93.9
- CodeForces Rating: 1481

The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.
Context length: 32768 tokens
Tokenizer: Qwen
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 16384.0
Prompt price per 1M tokens (USD): 0.15
Completion price per 1M tokens (USD): 0.15
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.15
Output/input cost ratio: 1.0
Supported parameters: frequency_penalty, include_reasoning, logit_bias, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: Perplexity: Sonar Reasoning
Vendor: Perplexity
Description: Sonar Reasoning is a reasoning model provided by Perplexity based on [DeepSeek R1](/deepseek/deepseek-r1).

It allows developers to utilize long chain of thought with built-in web search. Sonar Reasoning is uncensored and hosted in US datacenters. 
Context length: 127000 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 1.0
Completion price per 1M tokens (USD): 5.0
Image price (USD): 0.0
Request price (USD): 0.005
Median price per 1M tokens (USD): 3.0
Output/input cost ratio: 5.0
Supported parameters: frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, temperature, top_k, top_p, web_search_options
Model: Perplexity: Sonar
Vendor: Perplexity
Description: Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources. It is designed for companies seeking to integrate lightweight question-and-answer features optimized for speed.
Context length: 127072 tokens
Tokenizer: Other
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Prompt price per 1M tokens (USD): 1.0
Completion price per 1M tokens (USD): 1.0
Image price (USD): 0.0
Request price (USD): 0.005
Median price per 1M tokens (USD): 1.0
Output/input cost ratio: 1.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, temperature, top_k, top_p, web_search_options
Model: DeepSeek: R1 Distill Llama 70B (free)
Vendor: DeepSeek
Hugging Face ID: deepseek-ai/DeepSeek-R1-Distill-Llama-70B
Description: DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across multiple benchmarks, including:

- AIME 2024 pass@1: 70.0
- MATH-500 pass@1: 94.5
- CodeForces Rating: 1633

The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.
Context length: 8192 tokens
Tokenizer: Llama3
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 4096.0
Prompt price per 1M tokens (USD): 0.0
Completion price per 1M tokens (USD): 0.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.0
Output/input cost ratio: 0.0
Supported parameters: frequency_penalty, include_reasoning, logit_bias, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, seed, stop, temperature, top_k, top_p
Model: DeepSeek: R1 Distill Llama 70B
Vendor: DeepSeek
Hugging Face ID: deepseek-ai/DeepSeek-R1-Distill-Llama-70B
Description: DeepSeek R1 Distill Llama 70B is a distilled large language model based on [Llama-3.3-70B-Instruct](/meta-llama/llama-3.3-70b-instruct), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). The model combines advanced distillation techniques to achieve high performance across multiple benchmarks, including:

- AIME 2024 pass@1: 70.0
- MATH-500 pass@1: 94.5
- CodeForces Rating: 1633

The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.
Context length: 131072 tokens
Tokenizer: Llama3
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 131072.0
Prompt price per 1M tokens (USD): 0.03
Completion price per 1M tokens (USD): 0.13
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.08
Output/input cost ratio: 4.33
Supported parameters: frequency_penalty, include_reasoning, logit_bias, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p
Model: DeepSeek: R1 (free)
Vendor: DeepSeek
Hugging Face ID: deepseek-ai/DeepSeek-R1
Description: DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.

Fully open-source model & [technical report](https://api-docs.deepseek.com/news/news250120).

MIT licensed: Distill & commercialize freely!
Context length: 163840 tokens
Tokenizer: DeepSeek
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.0
Completion price per 1M tokens (USD): 0.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.0
Output/input cost ratio: 0.0
Supported parameters: frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: DeepSeek: R1
Vendor: DeepSeek
Hugging Face ID: deepseek-ai/DeepSeek-R1
Description: DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.

Fully open-source model & [technical report](https://api-docs.deepseek.com/news/news250120).

MIT licensed: Distill & commercialize freely!
Context length: 163840 tokens
Tokenizer: DeepSeek
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.3
Completion price per 1M tokens (USD): 1.2
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.75
Output/input cost ratio: 4.0
Supported parameters: frequency_penalty, include_reasoning, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p
Model: MiniMax: MiniMax-01
Vendor: Minimax
Hugging Face ID: MiniMaxAI/MiniMax-Text-01
Description: MiniMax-01 is a combines MiniMax-Text-01 for text generation and MiniMax-VL-01 for image understanding. It has 456 billion parameters, with 45.9 billion parameters activated per inference, and can handle a context of up to 4 million tokens.

The text model adopts a hybrid architecture that combines Lightning Attention, Softmax Attention, and Mixture-of-Experts (MoE). The image model adopts the “ViT-MLP-LLM” framework and is trained on top of the text model.

To read more about the release, see: https://www.minimaxi.com/en/news/minimax-01-series-2
Context length: 1000192 tokens
Tokenizer: Other
Modality: text+image->text
Input modalities: text, image
Output modalities: text
Max completion tokens (top provider): 1000192.0
Prompt price per 1M tokens (USD): 0.1999999999999999
Completion price per 1M tokens (USD): 1.1
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.65
Output/input cost ratio: 5.5
Supported parameters: max_tokens, temperature, top_p
Model: Mistral: Codestral 2501
Vendor: Mistral AI
Description: [Mistral](/mistralai)'s cutting-edge language model for coding. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. 

Learn more on their blog post: https://mistral.ai/news/codestral-2501/
Context length: 262144 tokens
Tokenizer: Mistral
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.3
Completion price per 1M tokens (USD): 0.8999999999999999
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.6
Output/input cost ratio: 3.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_p
Model: Microsoft: Phi 4
Vendor: Microsoft
Hugging Face ID: microsoft/phi-4
Description: [Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. 

At 14 billion parameters, it was trained on a mix of high-quality synthetic datasets, data from curated websites, and academic materials. It has undergone careful improvement to follow instructions accurately and maintain strong safety standards. It works best with English language inputs.

For more information, please see [Phi-4 Technical Report](https://arxiv.org/pdf/2412.08905)

Context length: 16384 tokens
Tokenizer: Other
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 0.06
Completion price per 1M tokens (USD): 0.14
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.1
Output/input cost ratio: 2.33
Supported parameters: frequency_penalty, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: Sao10K: Llama 3.1 70B Hanami x1
Vendor: Sao10k
Hugging Face ID: Sao10K/L3.1-70B-Hanami-x1
Description: This is [Sao10K](/sao10k)'s experiment over [Euryale v2.2](/sao10k/l3.1-euryale-70b).
Context length: 16000 tokens
Tokenizer: Llama3
Modality: text->text
Input modalities: text
Output modalities: text
Prompt price per 1M tokens (USD): 3.0
Completion price per 1M tokens (USD): 3.0
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 3.0
Output/input cost ratio: 1.0
Supported parameters: frequency_penalty, logit_bias, max_tokens, min_p, presence_penalty, repetition_penalty, seed, stop, temperature, top_k, top_p
Model: DeepSeek: DeepSeek V3
Vendor: DeepSeek
Hugging Face ID: deepseek-ai/DeepSeek-V3
Description: DeepSeek-V3 is the latest model from the DeepSeek team, building upon the instruction following and coding abilities of the previous versions. Pre-trained on nearly 15 trillion tokens, the reported evaluations reveal that the model outperforms other open-source models and rivals leading closed-source models.

For model details, please visit [the DeepSeek-V3 repo](https://github.com/deepseek-ai/DeepSeek-V3) for more information, or see the [launch announcement](https://api-docs.deepseek.com/news/news1226).
Context length: 163840 tokens
Tokenizer: DeepSeek
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 163840.0
Prompt price per 1M tokens (USD): 0.3
Completion price per 1M tokens (USD): 1.2
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.75
Output/input cost ratio: 4.0
Supported parameters: frequency_penalty, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p
Model: Sao10K: Llama 3.3 Euryale 70B
Vendor: Sao10k
Hugging Face ID: Sao10K/L3.3-70B-Euryale-v2.3
Description: Euryale L3.3 70B is a model focused on creative roleplay from [Sao10k](https://ko-fi.com/sao10k). It is the successor of [Euryale L3 70B v2.2](/models/sao10k/l3-euryale-70b).
Context length: 131072 tokens
Tokenizer: Llama3
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 16384.0
Prompt price per 1M tokens (USD): 0.65
Completion price per 1M tokens (USD): 0.75
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.7
Output/input cost ratio: 1.15
Supported parameters: frequency_penalty, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p
Model: OpenAI: o1
Vendor: OpenAI
Description: The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. 

The o1 models are optimized for math, science, programming, and other STEM-related tasks. They consistently exhibit PhD-level accuracy on benchmarks in physics, chemistry, and biology. Learn more in the [launch announcement](https://openai.com/o1).

Context length: 200000 tokens
Tokenizer: GPT
Modality: text+image->text
Input modalities: text, image, file
Output modalities: text
Max completion tokens (top provider): 100000.0
Prompt price per 1M tokens (USD): 15.0
Completion price per 1M tokens (USD): 60.0
Image price (USD): 0.021675
Request price (USD): 0.0
Median price per 1M tokens (USD): 37.5
Output/input cost ratio: 4.0
Supported parameters: max_tokens, response_format, seed, structured_outputs, tool_choice, tools
Model: Cohere: Command R7B (12-2024)
Vendor: Cohere
Description: Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning and multiple steps.

Use of this model is subject to Cohere's [Usage Policy](https://docs.cohere.com/docs/usage-policy) and [SaaS Agreement](https://cohere.com/saas-agreement).
Context length: 128000 tokens
Tokenizer: Cohere
Modality: text->text
Input modalities: text
Output modalities: text
Max completion tokens (top provider): 4000.0
Prompt price per 1M tokens (USD): 0.0375
Completion price per 1M tokens (USD): 0.15
Image price (USD): 0.0
Request price (USD): 0.0
Median price per 1M tokens (USD): 0.09375
Output/input cost ratio: 4.0
Supported parameters: frequency_penalty, max_tokens, presence_penalty, response_format, seed, stop, structured_outputs, temperature, top_k, top_p