List of All LLM Models
Discover and compare 500+ large language models with real-time rankings, benchmarks, and community votes.
Microsoft: Phi 4 Multimodal Instruct
By Microsoft
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/).
Release Date
08 Mar 2025
Context Size
131.07K
Perplexity: Sonar Reasoning Pro
By Perplexity
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.
Release Date
07 Mar 2025
Context Size
128K
Perplexity: Sonar Pro
By Perplexity
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.
Release Date
07 Mar 2025
Context Size
200K
Perplexity: Sonar Deep Research
By Perplexity
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
Release Date
07 Mar 2025
Context Size
128K
DeepSeek: DeepSeek R1 Zero
By DeepSeek
DeepSeek-R1-Zero is a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step. It's 671B parameters in size, with 37B active in an inference pass. It demonstrates remarkable performance on reasoning. With RL, DeepSeek-R1-Zero naturally emerged with numerous powerful and interesting reasoning behaviors. DeepSeek-R1-Zero encounters challenges such as endless repetition, poor readability, and language mixing. See [DeepSeek R1](/deepseek/deepseek-r1) for the SFT model.
Release Date
06 Mar 2025
Context Size
163.84K
Qwen: QwQ 32B
By Qwen
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.
Release Date
05 Mar 2025
Context Size
131.07K
Qwen: Qwen2.5 32B Instruct
By Qwen
Qwen2.5 32B Instruct is the instruction-tuned variant of the latest Qwen large language model series. It provides enhanced instruction-following capabilities, improved proficiency in coding and mathematical reasoning, and robust handling of structured data and outputs such as JSON. It supports long-context processing up to 128K tokens and multilingual tasks across 29+ languages. The model has 32.5 billion parameters, 64 layers, and utilizes an advanced transformer architecture with RoPE, SwiGLU, RMSNorm, and Attention QKV bias. For more details, please refer to the [Qwen2.5 Blog](https://qwenlm.github.io/blog/qwen2.5/) .
Release Date
03 Mar 2025
Context Size
131.07K
MoonshotAI: Moonlight 16B A3B Instruct
By moonshotai
Moonlight-16B-A3B-Instruct is a 16B-parameter Mixture-of-Experts (MoE) language model developed by Moonshot AI. It is optimized for instruction-following tasks with 3B activated parameters per inference. The model advances the Pareto frontier in performance per FLOP across English, coding, math, and Chinese benchmarks. It outperforms comparable models like Llama3-3B and Deepseek-v2-Lite while maintaining efficient deployment capabilities through Hugging Face integration and compatibility with popular inference engines like vLLM12.
Release Date
28 Feb 2025
Context Size
8.19K
Nous: DeepHermes 3 Llama 3 8B Preview
By Nous Research
DeepHermes 3 Preview is the latest version of our flagship Hermes series of LLMs by Nous Research, and one of the first models in the world to unify Reasoning (long chains of thought that improve answer accuracy) and normal LLM response modes into one model. We have also improved LLM annotation, judgement, and function calling. DeepHermes 3 Preview is one of the first LLM models to unify both "intuitive", traditional mode responses and long chain of thought reasoning responses into a single model, toggled by a system prompt.
Release Date
28 Feb 2025
Context Size
131.07K
OpenAI: GPT-4.5 (Preview)
By OpenAI
GPT-4.5 (Preview) is a research preview of OpenAI’s latest language model, designed to advance capabilities in reasoning, creativity, and multi-turn conversation. It builds on previous iterations with improvements in world knowledge, contextual coherence, and the ability to follow user intent more effectively. The model demonstrates enhanced performance in tasks that require open-ended thinking, problem-solving, and communication. Early testing suggests it is better at generating nuanced responses, maintaining long-context coherence, and reducing hallucinations compared to earlier versions. This research preview is intended to help evaluate GPT-4.5’s strengths and limitations in real-world use cases as OpenAI continues to refine and develop future models. Read more at the [blog post here.](https://openai.com/index/introducing-gpt-4-5/)
Release Date
27 Feb 2025
Context Size
128K
Google: Gemini 2.0 Flash Lite
By Google
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.
Release Date
25 Feb 2025
Context Size
1.05M
Anthropic: Claude 3.7 Sonnet (thinking)
By Anthropic
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)
Release Date
24 Feb 2025
Context Size
200K
Anthropic: Claude 3.7 Sonnet (thinking)
By anthropic
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...
Release Date
24 Feb 2025
Context Size
200K
Perplexity: R1 1776
By Perplexity
R1 1776 is a version of DeepSeek-R1 that has been post-trained to remove censorship constraints related to topics restricted by the Chinese government. The model retains its original reasoning capabilities while providing direct responses to a wider range of queries. R1 1776 is an offline chat model that does not use the perplexity search subsystem. The model was tested on a multilingual dataset of over 1,000 examples covering sensitive topics to measure its likelihood of refusal or overly filtered responses. [Evaluation Results](https://cdn-uploads.huggingface.co/production/uploads/675c8332d01f593dc90817f5/GiN2VqC5hawUgAGJ6oHla.png) Its performance on math and reasoning benchmarks remains similar to the base R1 model. [Reasoning Performance](https://cdn-uploads.huggingface.co/production/uploads/675c8332d01f593dc90817f5/n4Z9Byqp2S7sKUvCvI40R.png) Read more on the [Blog Post](https://perplexity.ai/hub/blog/open-sourcing-r1-1776)
Release Date
19 Feb 2025
Context Size
128K
Mistral: Saba
By Mistral AI
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)
Release Date
17 Feb 2025
Context Size
32.77K
Dolphin3.0 R1 Mistral 24B
By Cognitive Computations
Dolphin 3.0 R1 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases. The R1 version has been trained for 3 epochs to reason using 800k reasoning traces from the Dolphin-R1 dataset. Dolphin aims to be a general purpose reasoning instruct model, similar to the models behind ChatGPT, Claude, Gemini. Part of the [Dolphin 3.0 Collection](https://huggingface.co/collections/QuixiAI/dolphin-30) Curated and trained by [Eric Hartford](https://huggingface.co/ehartford), [Ben Gitter](https://huggingface.co/bigstorm), [BlouseJury](https://huggingface.co/BlouseJury) and [DphnAI](https://huggingface.co/dphn)
Release Date
13 Feb 2025
Context Size
32.77K
Dolphin3.0 Mistral 24B
By Cognitive Computations
Dolphin 3.0 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases. Dolphin aims to be a general purpose instruct model, similar to the models behind ChatGPT, Claude, Gemini. Part of the [Dolphin 3.0 Collection](https://huggingface.co/collections/QuixiAI/dolphin-30) Curated and trained by [Eric Hartford](https://huggingface.co/ehartford), [Ben Gitter](https://huggingface.co/bigstorm), [BlouseJury](https://huggingface.co/BlouseJury) and [DphnAI](https://huggingface.co/dphn)
Release Date
13 Feb 2025
Context Size
32.77K
Llama Guard 3 8B
By Meta Llama
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.
Release Date
12 Feb 2025
Context Size
131.07K
OpenAI: o3 Mini High
By OpenAI
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.
Release Date
12 Feb 2025
Context Size
200K
Llama 3.1 Tulu 3 405B
By Ai2
Tülu 3 405B is the largest model in the Tülu 3 family, applying fully open post-training recipes at a 405B parameter scale. Built on the Llama 3.1 405B base, it leverages Reinforcement Learning with Verifiable Rewards (RLVR) to enhance instruction following, MATH, GSM8K, and IFEval performance. As part of Tülu 3’s fully open-source approach, it offers state-of-the-art capabilities while surpassing prior open-weight models like Llama 3.1 405B Instruct and Nous Hermes 3 405B on multiple benchmarks. To read more, [click here.](https://allenai.org/blog/tulu-3-405B)
Release Date
08 Feb 2025
Context Size
0
DeepSeek: R1 Distill Llama 8B
By DeepSeek
DeepSeek R1 Distill Llama 8B is a distilled large language model based on [Llama-3.1-8B-Instruct](/meta-llama/llama-3.1-8b-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: 50.4 - MATH-500 pass@1: 89.1 - CodeForces Rating: 1205 The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models. Hugging Face: - [Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B) - [DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B) |
Release Date
07 Feb 2025
Context Size
0
Google: Gemini 2.0 Flash
By Google
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.
Release Date
05 Feb 2025
Context Size
1.05M
Qwen: Qwen VL Plus
By Qwen
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.
Release Date
05 Feb 2025
Context Size
131.07K
AionLabs: Aion-1.0
By Aion Labs
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.
Release Date
04 Feb 2025
Context Size
131.07K
AionLabs: Aion-1.0-Mini
By Aion Labs
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.
Release Date
04 Feb 2025
Context Size
131.07K
AionLabs: Aion-RP 1.0 (8B)
By Aion Labs
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.
Release Date
04 Feb 2025
Context Size
32.77K
Qwen: Qwen VL Max
By Qwen
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.
Release Date
01 Feb 2025
Context Size
131.07K
Qwen: Qwen-Turbo
By Qwen
Qwen-Turbo, based on Qwen2.5, is a 1M context model that provides fast speed and low cost, suitable for simple tasks.
Release Date
01 Feb 2025
Context Size
131.07K
Qwen: Qwen2.5 VL 72B Instruct
By Qwen
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.
Release Date
01 Feb 2025
Context Size
32K
Qwen: Qwen-Plus
By Qwen
Qwen-Plus, based on the Qwen2.5 foundation model, is a 131K context model with a balanced performance, speed, and cost combination.
Release Date
01 Feb 2025
Context Size
1M
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