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Claude 3.7 Sonnet is Anthropic’s first hybrid reasoning AI model, combining fast, near-instant replies with optional step-by-step “extended thinking” in a single model. It’s their most intelligent Sonnet release yet—excelling at coding, math, planning, vision, and agentic tasks—while maintaining the same cost and speed structure .
Claude 3.7 Sonnet is Anthropic’s first hybrid reasoning AI model, combining fast, near-instant replies with optional step-by-step “extended thinking” in a single model. It’s their most intelligent Sonnet release yet—excelling at coding, math, planning, vision, and agentic tasks—while maintaining the same cost and speed structure .
Claude 3.7 Sonnet is Anthropic’s first hybrid reasoning AI model, combining fast, near-instant replies with optional step-by-step “extended thinking” in a single model. It’s their most intelligent Sonnet release yet—excelling at coding, math, planning, vision, and agentic tasks—while maintaining the same cost and speed structure .
Gemini 1.5 Pro is Google DeepMind’s mid-size multimodal model, using a mixture-of-experts (MoE) architecture to deliver high performance with lower compute. It supports text, images, audio, video, and code, and features an experimental context window up to 1 million tokens—the longest among widely available models. It excels in long-document reasoning, multimodal understanding, and in-context learning.
Gemini 1.5 Pro is Google DeepMind’s mid-size multimodal model, using a mixture-of-experts (MoE) architecture to deliver high performance with lower compute. It supports text, images, audio, video, and code, and features an experimental context window up to 1 million tokens—the longest among widely available models. It excels in long-document reasoning, multimodal understanding, and in-context learning.
Gemini 1.5 Pro is Google DeepMind’s mid-size multimodal model, using a mixture-of-experts (MoE) architecture to deliver high performance with lower compute. It supports text, images, audio, video, and code, and features an experimental context window up to 1 million tokens—the longest among widely available models. It excels in long-document reasoning, multimodal understanding, and in-context learning.
DeepSeek‑R1 is the flagship reasoning-oriented AI model from Chinese startup DeepSeek. It’s an open-source, mixture-of-experts (MoE) model combining model weights clarity and chain-of-thought reasoning trained primarily through reinforcement learning. R1 delivers top-tier benchmark performance—on par with or surpassing OpenAI o1 in math, coding, and reasoning—while being significantly more cost-efficient.
DeepSeek‑R1 is the flagship reasoning-oriented AI model from Chinese startup DeepSeek. It’s an open-source, mixture-of-experts (MoE) model combining model weights clarity and chain-of-thought reasoning trained primarily through reinforcement learning. R1 delivers top-tier benchmark performance—on par with or surpassing OpenAI o1 in math, coding, and reasoning—while being significantly more cost-efficient.
DeepSeek‑R1 is the flagship reasoning-oriented AI model from Chinese startup DeepSeek. It’s an open-source, mixture-of-experts (MoE) model combining model weights clarity and chain-of-thought reasoning trained primarily through reinforcement learning. R1 delivers top-tier benchmark performance—on par with or surpassing OpenAI o1 in math, coding, and reasoning—while being significantly more cost-efficient.
DeepSeek V3 is the latest flagship Mixture‑of‑Experts (MoE) open‑source AI model from DeepSeek. It features 671 billion total parameters (with ~37 billion activated per token), supports up to 128K context length, and excels across reasoning, code generation, language, and multimodal tasks. On standard benchmarks, it rivals or exceeds proprietary models—including GPT‑4o and Claude 3.5—as a high-performance, cost-efficient alternative.
DeepSeek V3 is the latest flagship Mixture‑of‑Experts (MoE) open‑source AI model from DeepSeek. It features 671 billion total parameters (with ~37 billion activated per token), supports up to 128K context length, and excels across reasoning, code generation, language, and multimodal tasks. On standard benchmarks, it rivals or exceeds proprietary models—including GPT‑4o and Claude 3.5—as a high-performance, cost-efficient alternative.
DeepSeek V3 is the latest flagship Mixture‑of‑Experts (MoE) open‑source AI model from DeepSeek. It features 671 billion total parameters (with ~37 billion activated per token), supports up to 128K context length, and excels across reasoning, code generation, language, and multimodal tasks. On standard benchmarks, it rivals or exceeds proprietary models—including GPT‑4o and Claude 3.5—as a high-performance, cost-efficient alternative.
Claude 3 Opus is Anthropic’s flagship Claude 3 model, released March 4, 2024. It offers top-tier performance for deep reasoning, complex code, advanced math, and multimodal understanding—including charts and documents—supported by a 200K‑token context window (extendable to 1 million in select enterprise cases). It consistently outperforms GPT‑4 and Gemini Ultra on benchmark tests like MMLU, HumanEval, HellaSwag, and more.
Claude 3 Opus is Anthropic’s flagship Claude 3 model, released March 4, 2024. It offers top-tier performance for deep reasoning, complex code, advanced math, and multimodal understanding—including charts and documents—supported by a 200K‑token context window (extendable to 1 million in select enterprise cases). It consistently outperforms GPT‑4 and Gemini Ultra on benchmark tests like MMLU, HumanEval, HellaSwag, and more.
Claude 3 Opus is Anthropic’s flagship Claude 3 model, released March 4, 2024. It offers top-tier performance for deep reasoning, complex code, advanced math, and multimodal understanding—including charts and documents—supported by a 200K‑token context window (extendable to 1 million in select enterprise cases). It consistently outperforms GPT‑4 and Gemini Ultra on benchmark tests like MMLU, HumanEval, HellaSwag, and more.
Grok 3 is xAI’s newest flagship AI chatbot, released on February 17, 2025, running on the massive Colossus supercluster (~200,000 GPUs). It offers elite-level reasoning, chain-of-thought transparency (“Think” mode), advanced “Big Brain” deeper reasoning, multimodal support (text, images), and integrated real-time DeepSearch—positioning it as a top-tier competitor to GPT‑4o, Gemini, Claude, and DeepSeek V3 on benchmarks.
Grok 3 is xAI’s newest flagship AI chatbot, released on February 17, 2025, running on the massive Colossus supercluster (~200,000 GPUs). It offers elite-level reasoning, chain-of-thought transparency (“Think” mode), advanced “Big Brain” deeper reasoning, multimodal support (text, images), and integrated real-time DeepSearch—positioning it as a top-tier competitor to GPT‑4o, Gemini, Claude, and DeepSeek V3 on benchmarks.
Grok 3 is xAI’s newest flagship AI chatbot, released on February 17, 2025, running on the massive Colossus supercluster (~200,000 GPUs). It offers elite-level reasoning, chain-of-thought transparency (“Think” mode), advanced “Big Brain” deeper reasoning, multimodal support (text, images), and integrated real-time DeepSearch—positioning it as a top-tier competitor to GPT‑4o, Gemini, Claude, and DeepSeek V3 on benchmarks.
Llama 4 Scout is Meta’s compact and high-performance entry in the Llama 4 family, released April 5, 2025. Built on a mixture-of-experts (MoE) architecture with 17B active parameters (109B total) and a staggering 10‑million-token context window, it delivers top-tier speed and long-context reasoning while fitting on a single Nvidia H100 GPU. It outperforms models like Google's Gemma 3, Gemini 2.0 Flash‑Lite, and Mistral 3.1 across benchmarks.
Llama 4 Scout is Meta’s compact and high-performance entry in the Llama 4 family, released April 5, 2025. Built on a mixture-of-experts (MoE) architecture with 17B active parameters (109B total) and a staggering 10‑million-token context window, it delivers top-tier speed and long-context reasoning while fitting on a single Nvidia H100 GPU. It outperforms models like Google's Gemma 3, Gemini 2.0 Flash‑Lite, and Mistral 3.1 across benchmarks.
Llama 4 Scout is Meta’s compact and high-performance entry in the Llama 4 family, released April 5, 2025. Built on a mixture-of-experts (MoE) architecture with 17B active parameters (109B total) and a staggering 10‑million-token context window, it delivers top-tier speed and long-context reasoning while fitting on a single Nvidia H100 GPU. It outperforms models like Google's Gemma 3, Gemini 2.0 Flash‑Lite, and Mistral 3.1 across benchmarks.
Llama 3.2 Vision is Meta’s first open-source multimodal Llama model series, released on September 25, 2024. Available in 11 B and 90 B parameter sizes, it merges advanced image understanding with a massive 128 K‑token text context. Optimized for vision reasoning, captioning, document QA, and visual math tasks, it outperforms many closed-source multimodal models.
Llama 3.2 Vision is Meta’s first open-source multimodal Llama model series, released on September 25, 2024. Available in 11 B and 90 B parameter sizes, it merges advanced image understanding with a massive 128 K‑token text context. Optimized for vision reasoning, captioning, document QA, and visual math tasks, it outperforms many closed-source multimodal models.
Llama 3.2 Vision is Meta’s first open-source multimodal Llama model series, released on September 25, 2024. Available in 11 B and 90 B parameter sizes, it merges advanced image understanding with a massive 128 K‑token text context. Optimized for vision reasoning, captioning, document QA, and visual math tasks, it outperforms many closed-source multimodal models.
DeepSeek R1 Zero is an open-source large language model introduced in January 2025 by DeepSeek AI. It is a reinforcement learning–only version of DeepSeek R1, trained without supervised fine-tuning. With 671B total parameters (37B active) and a 128K-token context window, it demonstrates strong chain-of-thought reasoning, self-verification, and reflection.
DeepSeek R1 Zero is an open-source large language model introduced in January 2025 by DeepSeek AI. It is a reinforcement learning–only version of DeepSeek R1, trained without supervised fine-tuning. With 671B total parameters (37B active) and a 128K-token context window, it demonstrates strong chain-of-thought reasoning, self-verification, and reflection.
DeepSeek R1 Zero is an open-source large language model introduced in January 2025 by DeepSeek AI. It is a reinforcement learning–only version of DeepSeek R1, trained without supervised fine-tuning. With 671B total parameters (37B active) and a 128K-token context window, it demonstrates strong chain-of-thought reasoning, self-verification, and reflection.
DeepSeek R1 Lite Preview is the lightweight preview of DeepSeek’s flagship reasoning model, released on November 20, 2024. It’s designed for advanced chain-of-thought reasoning in math, coding, and logic, showcasing transparent, multi-round reasoning. It achieves performance on par—or exceeding—OpenAI’s o1-preview on benchmarks like AIME and MATH, using test-time compute scaling.
DeepSeek R1 Lite Preview is the lightweight preview of DeepSeek’s flagship reasoning model, released on November 20, 2024. It’s designed for advanced chain-of-thought reasoning in math, coding, and logic, showcasing transparent, multi-round reasoning. It achieves performance on par—or exceeding—OpenAI’s o1-preview on benchmarks like AIME and MATH, using test-time compute scaling.
DeepSeek R1 Lite Preview is the lightweight preview of DeepSeek’s flagship reasoning model, released on November 20, 2024. It’s designed for advanced chain-of-thought reasoning in math, coding, and logic, showcasing transparent, multi-round reasoning. It achieves performance on par—or exceeding—OpenAI’s o1-preview on benchmarks like AIME and MATH, using test-time compute scaling.
DeepSeek R1 0528 is the May 28, 2025 update to DeepSeek’s flagship reasoning model. It brings significantly enhanced benchmark performance, deeper chain-of-thought reasoning (now using ~23K tokens per problem), reduced hallucinations, and support for JSON output, function calling, multi-round chat, and context caching.
DeepSeek R1 0528 is the May 28, 2025 update to DeepSeek’s flagship reasoning model. It brings significantly enhanced benchmark performance, deeper chain-of-thought reasoning (now using ~23K tokens per problem), reduced hallucinations, and support for JSON output, function calling, multi-round chat, and context caching.
DeepSeek R1 0528 is the May 28, 2025 update to DeepSeek’s flagship reasoning model. It brings significantly enhanced benchmark performance, deeper chain-of-thought reasoning (now using ~23K tokens per problem), reduced hallucinations, and support for JSON output, function calling, multi-round chat, and context caching.
DeepSeek R1 0528 – Qwen3 ‑ 8B is an 8 B-parameter dense model distilled from DeepSeek‑R1‑0528 using Qwen3‑8B as its base. Released in May 2025, it transfers high-depth chain-of-thought reasoning into a compact architecture while achieving benchmark-leading results close to much larger models.
DeepSeek R1 0528 – Qwen3 ‑ 8B is an 8 B-parameter dense model distilled from DeepSeek‑R1‑0528 using Qwen3‑8B as its base. Released in May 2025, it transfers high-depth chain-of-thought reasoning into a compact architecture while achieving benchmark-leading results close to much larger models.
DeepSeek R1 0528 – Qwen3 ‑ 8B is an 8 B-parameter dense model distilled from DeepSeek‑R1‑0528 using Qwen3‑8B as its base. Released in May 2025, it transfers high-depth chain-of-thought reasoning into a compact architecture while achieving benchmark-leading results close to much larger models.
This page was researched and written by the ATB Editorial Team. Our team researches each AI tool by reviewing its official website, testing features, exploring real use cases, and considering user feedback. Every page is fact-checked and regularly updated to ensure the information stays accurate, neutral, and useful for our readers.
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