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x-ai/grok-3 | x-ai/grok-3 | xAI: Grok 3 | 1,749,582,908 | Grok 3 is the latest model from xAI. It's their flagship model that excels at enterprise use cases like data extraction, coding, and text summarization. Possesses deep domain knowledge in... | 131,072 | {
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google/gemini-2.5-pro-preview | google/gemini-2.5-pro-preview-06-05 | Google: Gemini 2.5 Pro Preview 06-05 | 1,749,137,257 | Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy... | 1,048,576 | {
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deepseek/deepseek-r1-0528 | deepseek/deepseek-r1-0528 | deepseek-ai/DeepSeek-R1-0528 | DeepSeek: R1 0528 | 1,748,455,170 | May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) 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... | 163,840 | {
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anthropic/claude-opus-4 | anthropic/claude-4-opus-20250522 | Anthropic: Claude Opus 4 | 1,747,931,245 | Claude Opus 4 is benchmarked as the world’s best coding model, at time of release, bringing sustained performance on complex, long-running tasks and agent workflows. It sets new benchmarks in... | 200,000 | {
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anthropic/claude-sonnet-4 | anthropic/claude-4-sonnet-20250522 | Anthropic: Claude Sonnet 4 | 1,747,930,371 | Claude Sonnet 4 significantly enhances the capabilities of its predecessor, Sonnet 3.7, excelling in both coding and reasoning tasks with improved precision and controllability. Achieving state-of-the-art performance on SWE-bench (72.7%),... | 1,000,000 | {
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google/gemma-3n-e4b-it:free | google/gemma-3n-e4b-it | google/gemma-3n-E4B-it | Google: Gemma 3n 4B (free) | 1,747,776,824 | Gemma 3n E4B-it is optimized for efficient execution on mobile and low-resource devices, such as phones, laptops, and tablets. It supports multimodal inputs—including text, visual data, and audio—enabling diverse tasks... | 8,192 | {
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google/gemma-3n-e4b-it | google/gemma-3n-e4b-it | google/gemma-3n-E4B-it | Google: Gemma 3n 4B | 1,747,776,824 | Gemma 3n E4B-it is optimized for efficient execution on mobile and low-resource devices, such as phones, laptops, and tablets. It supports multimodal inputs—including text, visual data, and audio—enabling diverse tasks... | 32,768 | {
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mistralai/mistral-medium-3 | mistralai/mistral-medium-3 | Mistral: Mistral Medium 3 | 1,746,627,341 | Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost... | 131,072 | {
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google/gemini-2.5-pro-preview-05-06 | google/gemini-2.5-pro-preview-03-25 | Google: Gemini 2.5 Pro Preview 05-06 | 1,746,578,513 | Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy... | 1,048,576 | {
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arcee-ai/spotlight | arcee-ai/spotlight | Arcee AI: Spotlight | 1,746,481,552 | Spotlight is a 7‑billion‑parameter vision‑language model derived from Qwen 2.5‑VL and fine‑tuned by Arcee AI for tight image‑text grounding tasks. It offers a 32 k‑token context window, enabling rich multimodal... | 131,072 | {
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arcee-ai/maestro-reasoning | arcee-ai/maestro-reasoning | Arcee AI: Maestro Reasoning | 1,746,481,269 | Maestro Reasoning is Arcee's flagship analysis model: a 32 B‑parameter derivative of Qwen 2.5‑32 B tuned with DPO and chain‑of‑thought RL for step‑by‑step logic. Compared to the earlier 7 B... | 131,072 | {
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arcee-ai/virtuoso-large | arcee-ai/virtuoso-large | Arcee AI: Virtuoso Large | 1,746,478,885 | Virtuoso‑Large is Arcee's top‑tier general‑purpose LLM at 72 B parameters, tuned to tackle cross‑domain reasoning, creative writing and enterprise QA. Unlike many 70 B peers, it retains the 128 k... | 131,072 | {
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arcee-ai/coder-large | arcee-ai/coder-large | Arcee AI: Coder Large | 1,746,478,663 | Coder‑Large is a 32 B‑parameter offspring of Qwen 2.5‑Instruct that has been further trained on permissively‑licensed GitHub, CodeSearchNet and synthetic bug‑fix corpora. It supports a 32k context window, enabling multi‑file... | 32,768 | {
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meta-llama/llama-guard-4-12b | meta-llama/llama-guard-4-12b | meta-llama/Llama-Guard-4-12B | Meta: Llama Guard 4 12B | 1,745,975,193 | Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM... | 163,840 | {
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qwen/qwen3-30b-a3b | qwen/qwen3-30b-a3b-04-28 | Qwen/Qwen3-30B-A3B | Qwen: Qwen3 30B A3B | 1,745,878,604 | Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique... | 40,960 | {
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qwen/qwen3-8b | qwen/qwen3-8b-04-28 | Qwen/Qwen3-8B | Qwen: Qwen3 8B | 1,745,876,632 | Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,... | 40,960 | {
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qwen/qwen3-14b | qwen/qwen3-14b-04-28 | Qwen/Qwen3-14B | Qwen: Qwen3 14B | 1,745,876,478 | Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for... | 40,960 | {
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qwen/qwen3-32b | qwen/qwen3-32b-04-28 | Qwen/Qwen3-32B | Qwen: Qwen3 32B | 1,745,875,945 | Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for... | 40,960 | {
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qwen/qwen3-235b-a22b | qwen/qwen3-235b-a22b-04-28 | Qwen/Qwen3-235B-A22B | Qwen: Qwen3 235B A22B | 1,745,875,757 | Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and... | 131,072 | {
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openai/o4-mini-high | openai/o4-mini-high-2025-04-16 | OpenAI: o4 Mini High | 1,744,824,212 | OpenAI o4-mini-high is the same model as [o4-mini](/openai/o4-mini) with reasoning_effort set to high. OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining... | 200,000 | {
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openai/o3 | openai/o3-2025-04-16 | OpenAI: o3 | 1,744,823,457 | o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following.... | 200,000 | {
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openai/o4-mini | openai/o4-mini-2025-04-16 | OpenAI: o4 Mini | 1,744,820,942 | OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning... | 200,000 | {
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openai/gpt-4.1 | openai/gpt-4.1-2025-04-14 | OpenAI: GPT-4.1 | 1,744,651,385 | GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and... | 1,047,576 | {
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openai/gpt-4.1-mini | openai/gpt-4.1-mini-2025-04-14 | OpenAI: GPT-4.1 Mini | 1,744,651,381 | GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard... | 1,047,576 | {
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openai/gpt-4.1-nano | openai/gpt-4.1-nano-2025-04-14 | OpenAI: GPT-4.1 Nano | 1,744,651,369 | For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million... | 1,047,576 | {
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alfredpros/codellama-7b-instruct-solidity | alfredpros/codellama-7b-instruct-solidity | AlfredPros/CodeLlama-7b-Instruct-Solidity | AlfredPros: CodeLLaMa 7B Instruct Solidity | 1,744,641,874 | A finetuned 7 billion parameters Code LLaMA - Instruct model to generate Solidity smart contract using 4-bit QLoRA finetuning provided by PEFT library. | 4,096 | {
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x-ai/grok-3-mini-beta | x-ai/grok-3-mini-beta | xAI: Grok 3 Mini Beta | 1,744,240,195 | Grok 3 Mini is a lightweight, smaller thinking model. Unlike traditional models that generate answers immediately, Grok 3 Mini thinks before responding. It’s ideal for reasoning-heavy tasks that don’t demand... | 131,072 | {
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x-ai/grok-3-beta | x-ai/grok-3-beta | xAI: Grok 3 Beta | 1,744,240,068 | Grok 3 is the latest model from xAI. It's their flagship model that excels at enterprise use cases like data extraction, coding, and text summarization. Possesses deep domain knowledge in... | 131,072 | {
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meta-llama/llama-4-maverick | meta-llama/llama-4-maverick-17b-128e-instruct | meta-llama/Llama-4-Maverick-17B-128E-Instruct | Meta: Llama 4 Maverick | 1,743,881,822 | Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward... | 1,048,576 | {
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meta-llama/llama-4-scout | meta-llama/llama-4-scout-17b-16e-instruct | meta-llama/Llama-4-Scout-17B-16E-Instruct | Meta: Llama 4 Scout | 1,743,881,519 | Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input... | 327,680 | {
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qwen/qwen2.5-vl-32b-instruct | qwen/qwen2.5-vl-32b-instruct | Qwen/Qwen2.5-VL-32B-Instruct | Qwen: Qwen2.5 VL 32B Instruct | 1,742,839,838 | Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual... | 128,000 | {
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deepseek/deepseek-chat-v3-0324 | deepseek/deepseek-chat-v3-0324 | deepseek-ai/DeepSeek-V3-0324 | DeepSeek: DeepSeek V3 0324 | 1,742,824,755 | 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](/deepseek/deepseek-chat-v3) model and performs really well... | 163,840 | {
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openai/o1-pro | openai/o1-pro | OpenAI: o1-pro | 1,742,423,211 | The o1 series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o1-pro model uses more compute to think harder and provide... | 200,000 | {
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mistralai/mistral-small-3.1-24b-instruct | mistralai/mistral-small-3.1-24b-instruct-2503 | mistralai/Mistral-Small-3.1-24B-Instruct-2503 | Mistral: Mistral Small 3.1 24B | 1,742,238,937 | Mistral Small 3.1 24B Instruct is an upgraded variant of Mistral Small 3 (2501), featuring 24 billion parameters with advanced multimodal capabilities. It provides state-of-the-art performance in text-based reasoning and... | 128,000 | {
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allenai/olmo-2-0325-32b-instruct | allenai/olmo-2-0325-32b-instruct | allenai/OLMo-2-0325-32B-Instruct | AllenAI: Olmo 2 32B Instruct | 1,741,988,556 | OLMo-2 32B Instruct is a supervised instruction-finetuned variant of the OLMo-2 32B March 2025 base model. It excels in complex reasoning and instruction-following tasks across diverse benchmarks such as GSM8K,... | 128,000 | {
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google/gemma-3-4b-it:free | google/gemma-3-4b-it | google/gemma-3-4b-it | Google: Gemma 3 4B (free) | 1,741,905,510 | 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,... | 32,768 | {
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google/gemma-3-4b-it | google/gemma-3-4b-it | google/gemma-3-4b-it | Google: Gemma 3 4B | 1,741,905,510 | 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,... | 131,072 | {
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google/gemma-3-12b-it:free | google/gemma-3-12b-it | google/gemma-3-12b-it | Google: Gemma 3 12B (free) | 1,741,902,625 | 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,... | 32,768 | {
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google/gemma-3-12b-it | google/gemma-3-12b-it | google/gemma-3-12b-it | Google: Gemma 3 12B | 1,741,902,625 | 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,... | 131,072 | {
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cohere/command-a | cohere/command-a-03-2025 | CohereForAI/c4ai-command-a-03-2025 | Cohere: Command A | 1,741,894,342 | 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... | 256,000 | {
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openai/gpt-4o-mini-search-preview | openai/gpt-4o-mini-search-preview-2025-03-11 | OpenAI: GPT-4o-mini Search Preview | 1,741,818,122 | 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. | 128,000 | {
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openai/gpt-4o-search-preview | openai/gpt-4o-search-preview-2025-03-11 | OpenAI: GPT-4o Search Preview | 1,741,817,949 | GPT-4o Search Previewis a specialized model for web search in Chat Completions. It is trained to understand and execute web search queries. | 128,000 | {
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rekaai/reka-flash-3 | rekaai/reka-flash-3 | RekaAI/reka-flash-3 | Reka Flash 3 | 1,741,812,813 | Reka Flash 3 is a general-purpose, instruction-tuned large language model with 21 billion parameters, developed by Reka. It excels at general chat, coding tasks, instruction-following, and function calling. Featuring a... | 65,536 | {
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google/gemma-3-27b-it:free | google/gemma-3-27b-it | google/gemma-3-27b-it | Google: Gemma 3 27B (free) | 1,741,756,359 | 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,... | 131,072 | {
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google/gemma-3-27b-it | google/gemma-3-27b-it | google/gemma-3-27b-it | Google: Gemma 3 27B | 1,741,756,359 | 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,... | 131,072 | {
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thedrummer/skyfall-36b-v2 | thedrummer/skyfall-36b-v2 | TheDrummer/Skyfall-36B-v2 | TheDrummer: Skyfall 36B V2 | 1,741,636,566 | Skyfall 36B v2 is an enhanced iteration of Mistral Small 2501, specifically fine-tuned for improved creativity, nuanced writing, role-playing, and coherent storytelling. | 32,768 | {
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perplexity/sonar-reasoning-pro | perplexity/sonar-reasoning-pro | Perplexity: Sonar Reasoning Pro | 1,741,313,308 | 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... | 128,000 | {
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perplexity/sonar-pro | perplexity/sonar-pro | Perplexity: Sonar Pro | 1,741,312,423 | 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 extensibilit... | 200,000 | {
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perplexity/sonar-deep-research | perplexity/sonar-deep-research | Perplexity: Sonar Deep Research | 1,741,311,246 | 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... | 128,000 | {
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qwen/qwq-32b | qwen/qwq-32b | Qwen/QwQ-32B | Qwen: QwQ 32B | 1,741,208,814 | 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,... | 131,072 | {
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google/gemini-2.0-flash-lite-001 | google/gemini-2.0-flash-lite-001 | Google: Gemini 2.0 Flash Lite | 1,740,506,212 | 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),... | 1,048,576 | {
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anthropic/claude-3.7-sonnet | anthropic/claude-3-7-sonnet-20250219 | Anthropic: Claude 3.7 Sonnet | 1,740,422,110 | 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... | 200,000 | {
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anthropic/claude-3.7-sonnet:thinking | anthropic/claude-3-7-sonnet-20250219 | Anthropic: Claude 3.7 Sonnet (thinking) | 1,740,422,110 | 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... | 200,000 | {
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mistralai/mistral-saba | mistralai/mistral-saba-2502 | Mistral: Saba | 1,739,803,239 | 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... | 32,768 | {
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meta-llama/llama-guard-3-8b | meta-llama/llama-guard-3-8b | meta-llama/Llama-Guard-3-8B | Llama Guard 3 8B | 1,739,401,318 | 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)... | 131,072 | {
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openai/o3-mini-high | openai/o3-mini-high-2025-01-31 | OpenAI: o3 Mini High | 1,739,372,611 | 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... | 200,000 | {
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google/gemini-2.0-flash-001 | google/gemini-2.0-flash-001 | Google: Gemini 2.0 Flash | 1,738,769,413 | 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... | 1,048,576 | {
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qwen/qwen-vl-plus | qwen/qwen-vl-plus | Qwen: Qwen VL Plus | 1,738,731,255 | 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... | 131,072 | {
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aion-labs/aion-1.0 | aion-labs/aion-1.0 | AionLabs: Aion-1.0 | 1,738,697,557 | 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... | 131,072 | {
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aion-labs/aion-1.0-mini | aion-labs/aion-1.0-mini | FuseAI/FuseO1-DeepSeekR1-QwQ-SkyT1-32B-Preview | AionLabs: Aion-1.0-Mini | 1,738,697,107 | 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... | 131,072 | {
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aion-labs/aion-rp-llama-3.1-8b | aion-labs/aion-rp-llama-3.1-8b | AionLabs: Aion-RP 1.0 (8B) | 1,738,696,718 | 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... | 32,768 | {
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} | 2023-12-31 | null | {
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qwen/qwen-vl-max | qwen/qwen-vl-max-2025-01-25 | Qwen: Qwen VL Max | 1,738,434,304 | 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.
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qwen/qwen-turbo | qwen/qwen-turbo-2024-11-01 | Qwen: Qwen-Turbo | 1,738,410,974 | Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks. | 131,072 | {
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qwen/qwen2.5-vl-72b-instruct | qwen/qwen2.5-vl-72b-instruct | Qwen/Qwen2.5-VL-72B-Instruct | Qwen: Qwen2.5 VL 72B Instruct | 1,738,410,311 | 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. | 32,768 | {
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qwen/qwen-plus | qwen/qwen-plus-2025-01-25 | Qwen: Qwen-Plus | 1,738,409,840 | Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination. | 1,000,000 | {
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qwen/qwen-max | qwen/qwen-max-2025-01-25 | Qwen: Qwen-Max | 1,738,402,289 | 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... | 32,768 | {
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openai/o3-mini | openai/o3-mini-2025-01-31 | OpenAI: o3 Mini | 1,738,351,721 | 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... | 200,000 | {
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mistralai/mistral-small-24b-instruct-2501 | mistralai/mistral-small-24b-instruct-2501 | mistralai/Mistral-Small-24B-Instruct-2501 | Mistral: Mistral Small 3 | 1,738,255,409 | 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... | 32,768 | {
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deepseek/deepseek-r1-distill-qwen-32b | deepseek/deepseek-r1-distill-qwen-32b | deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | DeepSeek: R1 Distill Qwen 32B | 1,738,194,830 | 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... | 32,768 | {
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perplexity/sonar | perplexity/sonar | Perplexity: Sonar | 1,738,013,808 | 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... | 127,072 | {
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deepseek/deepseek-r1-distill-llama-70b | deepseek/deepseek-r1-distill-llama-70b | deepseek-ai/DeepSeek-R1-Distill-Llama-70B | DeepSeek: R1 Distill Llama 70B | 1,737,663,169 | 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... | 131,072 | {
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deepseek/deepseek-r1 | deepseek/deepseek-r1 | deepseek-ai/DeepSeek-R1 | DeepSeek: R1 | 1,737,381,095 | 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.... | 64,000 | {
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minimax/minimax-01 | minimax/minimax-01 | MiniMaxAI/MiniMax-Text-01 | MiniMax: MiniMax-01 | 1,736,915,462 | 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... | 1,000,192 | {
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microsoft/phi-4 | microsoft/phi-4 | microsoft/phi-4 | Microsoft: Phi 4 | 1,736,489,872 | [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... | 16,384 | {
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sao10k/l3.1-70b-hanami-x1 | sao10k/l3.1-70b-hanami-x1 | Sao10K/L3.1-70B-Hanami-x1 | Sao10K: Llama 3.1 70B Hanami x1 | 1,736,302,854 | This is [Sao10K](/sao10k)'s experiment over [Euryale v2.2](/sao10k/l3.1-euryale-70b). | 16,000 | {
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deepseek/deepseek-chat | deepseek/deepseek-chat-v3 | deepseek-ai/DeepSeek-V3 | DeepSeek: DeepSeek V3 | 1,735,241,320 | 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... | 163,840 | {
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sao10k/l3.3-euryale-70b | sao10k/l3.3-euryale-70b-v2.3 | Sao10K/L3.3-70B-Euryale-v2.3 | Sao10K: Llama 3.3 Euryale 70B | 1,734,535,928 | 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). | 131,072 | {
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openai/o1 | openai/o1-2024-12-17 | OpenAI: o1 | 1,734,459,999 | 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... | 200,000 | {
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cohere/command-r7b-12-2024 | cohere/command-r7b-12-2024 | Cohere: Command R7B (12-2024) | 1,734,158,152 | 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... | 128,000 | {
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meta-llama/llama-3.3-70b-instruct:free | meta-llama/llama-3.3-70b-instruct | meta-llama/Llama-3.3-70B-Instruct | Meta: Llama 3.3 70B Instruct (free) | 1,733,506,137 | The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model... | 65,536 | {
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meta-llama/llama-3.3-70b-instruct | meta-llama/llama-3.3-70b-instruct | meta-llama/Llama-3.3-70B-Instruct | Meta: Llama 3.3 70B Instruct | 1,733,506,137 | The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model... | 131,072 | {
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amazon/nova-lite-v1 | amazon/nova-lite-v1 | Amazon: Nova Lite 1.0 | 1,733,437,363 | Amazon Nova Lite 1.0 is a very low-cost multimodal model from Amazon that focused on fast processing of image, video, and text inputs to generate text output. Amazon Nova Lite... | 300,000 | {
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amazon/nova-micro-v1 | amazon/nova-micro-v1 | Amazon: Nova Micro 1.0 | 1,733,437,237 | Amazon Nova Micro 1.0 is a text-only model that delivers the lowest latency responses in the Amazon Nova family of models at a very low cost. With a context length... | 128,000 | {
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amazon/nova-pro-v1 | amazon/nova-pro-v1 | Amazon: Nova Pro 1.0 | 1,733,436,303 | Amazon Nova Pro 1.0 is a capable multimodal model from Amazon focused on providing a combination of accuracy, speed, and cost for a wide range of tasks. As of December... | 300,000 | {
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openai/gpt-4o-2024-11-20 | openai/gpt-4o-2024-11-20 | OpenAI: GPT-4o (2024-11-20) | 1,732,127,594 | The 2024-11-20 version of GPT-4o offers a leveled-up creative writing ability with more natural, engaging, and tailored writing to improve relevance & readability. It’s also better at working with uploaded... | 128,000 | {
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mistralai/mistral-large-2411 | mistralai/mistral-large-2411 | Mistral Large 2411 | 1,731,978,685 | Mistral Large 2 2411 is an update of [Mistral Large 2](/mistralai/mistral-large) released together with [Pixtral Large 2411](/mistralai/pixtral-large-2411) It provides a significant upgrade on the previous [Mistral Large 24.07](/mistralai/mistral-large-2407), with notable... | 131,072 | {
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mistralai/mistral-large-2407 | mistralai/mistral-large-2407 | Mistral Large 2407 | 1,731,978,415 | This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/).... | 131,072 | {
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mistralai/pixtral-large-2411 | mistralai/pixtral-large-2411 | Mistral: Pixtral Large 2411 | 1,731,977,388 | Pixtral Large is a 124B parameter, open-weight, multimodal model built on top of [Mistral Large 2](/mistralai/mistral-large-2411). The model is able to understand documents, charts and natural images. The model is... | 131,072 | {
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qwen/qwen-2.5-coder-32b-instruct | qwen/qwen-2.5-coder-32b-instruct | Qwen/Qwen2.5-Coder-32B-Instruct | Qwen2.5 Coder 32B Instruct | 1,731,368,400 | Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**... | 32,768 | {
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thedrummer/unslopnemo-12b | thedrummer/unslopnemo-12b | TheDrummer/UnslopNemo-12B-v4.1 | TheDrummer: UnslopNemo 12B | 1,731,103,448 | UnslopNemo v4.1 is the latest addition from the creator of Rocinante, designed for adventure writing and role-play scenarios. | 32,768 | {
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anthropic/claude-3.5-haiku | anthropic/claude-3-5-haiku | null | Anthropic: Claude 3.5 Haiku | 1,730,678,400 | Claude 3.5 Haiku features offers enhanced capabilities in speed, coding accuracy, and tool use. Engineered to excel in real-time applications, it delivers quick response times that are essential for dynamic... | 200,000 | {
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anthracite-org/magnum-v4-72b | anthracite-org/magnum-v4-72b | anthracite-org/magnum-v4-72b | Magnum v4 72B | 1,729,555,200 | This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet(https://openrouter.ai/anthropic/claude-3.5-sonnet) and Opus(https://openrouter.ai/anthropic/claude-3-opus).
The model is fine-tuned on top of [Qwen2.5 72B](https://openrouter.ai/qwen/qwen-2.5-72b-instruct). | 16,384 | {
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qwen/qwen-2.5-7b-instruct | qwen/qwen-2.5-7b-instruct | Qwen/Qwen2.5-7B-Instruct | Qwen: Qwen2.5 7B Instruct | 1,729,036,800 | Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge and has greatly improved capabilities in coding and... | 32,768 | {
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nvidia/llama-3.1-nemotron-70b-instruct | nvidia/llama-3.1-nemotron-70b-instruct | nvidia/Llama-3.1-Nemotron-70B-Instruct-HF | NVIDIA: Llama 3.1 Nemotron 70B Instruct | 1,728,950,400 | NVIDIA's Llama 3.1 Nemotron 70B is a language model designed for generating precise and useful responses. Leveraging [Llama 3.1 70B](/models/meta-llama/llama-3.1-70b-instruct) architecture and Reinforcement Learning from Human Feedback (RLHF), it excels... | 131,072 | {
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inflection/inflection-3-pi | inflection/inflection-3-pi | null | Inflection: Inflection 3 Pi | 1,728,604,800 | Inflection 3 Pi powers Inflection's [Pi](https://pi.ai) chatbot, including backstory, emotional intelligence, productivity, and safety. It has access to recent news, and excels in scenarios like customer support and roleplay. Pi... | 8,000 | {
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inflection/inflection-3-productivity | inflection/inflection-3-productivity | null | Inflection: Inflection 3 Productivity | 1,728,604,800 | Inflection 3 Productivity is optimized for following instructions. It is better for tasks requiring JSON output or precise adherence to provided guidelines. It has access to recent news. For emotional... | 8,000 | {
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thedrummer/rocinante-12b | thedrummer/rocinante-12b | TheDrummer/Rocinante-12B-v1.1 | TheDrummer: Rocinante 12B | 1,727,654,400 | Rocinante 12B is designed for engaging storytelling and rich prose. Early testers have reported: - Expanded vocabulary with unique and expressive word choices - Enhanced creativity for vivid narratives -... | 32,768 | {
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meta-llama/llama-3.2-1b-instruct | meta-llama/llama-3.2-1b-instruct | meta-llama/Llama-3.2-1B-Instruct | Meta: Llama 3.2 1B Instruct | 1,727,222,400 | Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate... | 60,000 | {
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meta-llama/llama-3.2-11b-vision-instruct | meta-llama/llama-3.2-11b-vision-instruct | meta-llama/Llama-3.2-11B-Vision-Instruct | Meta: Llama 3.2 11B Vision Instruct | 1,727,222,400 | Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and... | 131,072 | {
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