Best AI Reasoning Models in Germany - Page 3
View:
Compare the Top AI Reasoning Models in Germany as of August 2026 - Page 3
Sort By:
-
1
QwQ-32B
Alibaba
QwQ-32B is an advanced reasoning model developed by Alibaba Cloud's Qwen team, designed to enhance AI's problem-solving capabilities. With 32 billion parameters, it achieves performance comparable to state-of-the-art models like DeepSeek's R1, which has 671 billion parameters. This efficiency is achieved through optimized parameter utilization, allowing QwQ-32B to perform complex tasks such as mathematical reasoning, coding, and general problem-solving with fewer resources. The model supports a context length of up to 32,000 tokens, enabling it to process extensive input data effectively. QwQ-32B is accessible via Alibaba's chatbot service, Qwen Chat, and is open sourced under the Apache 2.0 license, promoting collaboration and further development within the AI community.Starting Price: Free -
2
Mistral Large 2
Mistral AI
Mistral AI has launched the Mistral Large 2, an advanced AI model designed to excel in code generation, multilingual capabilities, and complex reasoning tasks. The model features a 128k context window, supporting dozens of languages including English, French, Spanish, and Arabic, as well as over 80 programming languages. Mistral Large 2 is tailored for high-throughput single-node inference, making it ideal for large-context applications. Its improved performance on benchmarks like MMLU and its enhanced code generation and reasoning abilities ensure accuracy and efficiency. The model also incorporates better function calling and retrieval, supporting complex business applications.Starting Price: Free -
3
EXAONE Deep
LG
EXAONE Deep is a series of reasoning-enhanced language models developed by LG AI Research, featuring parameter sizes of 2.4 billion, 7.8 billion, and 32 billion. These models demonstrate superior capabilities in various reasoning tasks, including math and coding benchmarks. Notably, EXAONE Deep 2.4B outperforms other models of comparable size, EXAONE Deep 7.8B surpasses both open-weight models of similar scale and the proprietary reasoning model OpenAI o1-mini, and EXAONE Deep 32B shows competitive performance against leading open-weight models. The repository provides comprehensive documentation covering performance evaluations, quickstart guides for using EXAONE Deep models with Transformers, explanations of quantized EXAONE Deep weights in AWQ and GGUF formats, and instructions for running EXAONE Deep models locally using frameworks like llama.cpp and Ollama.Starting Price: Free -
4
Llama 4 Behemoth
Meta
Llama 4 Behemoth is Meta's most powerful AI model to date, featuring a massive 288 billion active parameters. It excels in multimodal tasks, outperforming previous models like GPT-4.5 and Gemini 2.0 Pro across multiple STEM-focused benchmarks such as MATH-500 and GPQA Diamond. As the teacher model for the Llama 4 series, Behemoth sets the foundation for models like Llama 4 Maverick and Llama 4 Scout. While still in training, Llama 4 Behemoth demonstrates unmatched intelligence, pushing the boundaries of AI in fields like math, multilinguality, and image understanding.Starting Price: Free -
5
Llama 4 Maverick
Meta
Llama 4 Maverick is one of the most advanced multimodal AI models from Meta, featuring 17 billion active parameters and 128 experts. It surpasses its competitors like GPT-4o and Gemini 2.0 Flash in a broad range of benchmarks, especially in tasks related to coding, reasoning, and multilingual capabilities. Llama 4 Maverick combines image and text understanding, enabling it to deliver industry-leading results in image-grounding tasks and precise, high-quality output. With its efficient performance at a reduced parameter size, Maverick offers exceptional value, especially in general assistant and chat applications.Starting Price: Free -
6
Llama 4 Scout
Meta
Llama 4 Scout is a powerful 17 billion active parameter multimodal AI model that excels in both text and image processing. With an industry-leading context length of 10 million tokens, it outperforms its predecessors, including Llama 3, in tasks such as multi-document summarization and parsing large codebases. Llama 4 Scout is designed to handle complex reasoning tasks while maintaining high efficiency, making it perfect for use cases requiring long-context comprehension and image grounding. It offers cutting-edge performance in image-related tasks and is particularly well-suited for applications requiring both text and visual understanding.Starting Price: Free -
7
GPT-4.1 mini
OpenAI
GPT-4.1 mini is a compact version of OpenAI’s powerful GPT-4.1 model, designed to provide high performance while significantly reducing latency and cost. With a smaller size and optimized architecture, GPT-4.1 mini still delivers impressive results in tasks such as coding, instruction following, and long-context processing. It supports up to 1 million tokens of context, making it an efficient solution for applications that require fast responses without sacrificing accuracy or depth.Starting Price: $0.40 per 1M tokens (input) -
8
GPT-4.1 nano
OpenAI
GPT-4.1 nano is the smallest and most efficient version of OpenAI's GPT-4.1 model, optimized for low-latency, cost-effective AI processing. Despite its compact size, GPT-4.1 nano delivers strong performance with a 1 million token context window, making it ideal for applications like classification, autocompletion, and smaller-scale tasks that require fast responses. It provides a highly efficient solution for businesses and developers who need an AI model that balances speed, cost, and performance.Starting Price: $0.10 per 1M tokens (input) -
9
Qwen3
Alibaba
Qwen3, the latest iteration of the Qwen family of large language models, introduces groundbreaking features that enhance performance across coding, math, and general capabilities. With models like the Qwen3-235B-A22B and Qwen3-30B-A3B, Qwen3 achieves impressive results compared to top-tier models, thanks to its hybrid thinking modes that allow users to control the balance between deep reasoning and quick responses. The platform supports 119 languages and dialects, making it an ideal choice for global applications. Its pre-training process, which uses 36 trillion tokens, enables robust performance, and advanced reinforcement learning (RL) techniques continue to refine its capabilities. Available on platforms like Hugging Face and ModelScope, Qwen3 offers a powerful tool for developers and researchers working in diverse fields.Starting Price: Free -
10
DeepSeek V3.1
DeepSeek
DeepSeek V3.1 is a groundbreaking open-weight large language model featuring a massive 685-billion parameters and an extended 128,000‑token context window, enabling it to process documents equivalent to 400-page books in a single prompt. It delivers integrated capabilities for chat, reasoning, and code generation within a unified hybrid architecture, seamlessly blending these functions into one coherent model. V3.1 supports a variety of tensor formats to give developers flexibility in optimizing performance across different hardware. Early benchmark results show robust performance, including a 71.6% score on the Aider coding benchmark, putting it on par with or ahead of systems like Claude Opus 4 and doing so at a far lower cost. Made available under an open source license on Hugging Face with minimal fanfare, DeepSeek V3.1 is poised to reshape access to high-performance AI, challenging traditional proprietary models.Starting Price: Free -
11
GLM-4.6
Zhipu AI
GLM-4.6 advances upon its predecessor with stronger reasoning, coding, and agentic capabilities: it demonstrates clear improvements in inferential performance, supports tool use during inference, and more effectively integrates into agent frameworks. In benchmark tests spanning reasoning, coding, and agents, GLM-4.6 outperforms GLM-4.5 and shows competitive strength against models such as DeepSeek-V3.2-Exp and Claude Sonnet 4, though it still trails Claude Sonnet 4.5 in pure coding performance. In real-world tests using an extended “CC-Bench” suite across front-end development, tool building, data analysis, and algorithmic tasks, GLM-4.6 beats GLM-4.5 and approaches parity with Claude Sonnet 4, winning ~48.6% of head-to-head comparisons, while also achieving ~15% better token efficiency. GLM-4.6 is available via the Z.ai API, and developers can integrate it as an LLM backend or agent core using the platform’s API.Starting Price: Free -
12
DeepSeek-V3.2-Exp
DeepSeek
Introducing DeepSeek-V3.2-Exp, our latest experimental model built on V3.1-Terminus, debuting DeepSeek Sparse Attention (DSA) for faster and more efficient inference and training on long contexts. DSA enables fine-grained sparse attention with minimal loss in output quality, boosting performance for long-context tasks while reducing compute costs. Benchmarks indicate that V3.2-Exp performs on par with V3.1-Terminus despite these efficiency gains. The model is now live across app, web, and API. Alongside this, the DeepSeek API prices have been cut by over 50% immediately to make access more affordable. For a transitional period, users can still access V3.1-Terminus via a temporary API endpoint until October 15, 2025. DeepSeek welcomes feedback on DSA via its feedback portal. In conjunction with the release, DeepSeek-V3.2-Exp has been open-sourced: the model weights and supporting technology (including key GPU kernels in TileLang and CUDA) are available on Hugging Face.Starting Price: Free -
13
DeepSeek-V3.2
DeepSeek
DeepSeek-V3.2 is a next-generation open large language model designed for efficient reasoning, complex problem solving, and advanced agentic behavior. It introduces DeepSeek Sparse Attention (DSA), a long-context attention mechanism that dramatically reduces computation while preserving performance. The model is trained with a scalable reinforcement learning framework, allowing it to achieve results competitive with GPT-5 and even surpass it in its Speciale variant. DeepSeek-V3.2 also includes a large-scale agent task synthesis pipeline that generates structured reasoning and tool-use demonstrations for post-training. The model features an updated chat template with new tool-calling logic and the optional developer role for agent workflows. With gold-medal performance in the IMO and IOI 2025 competitions, DeepSeek-V3.2 demonstrates elite reasoning capabilities for both research and applied AI scenarios.Starting Price: Free -
14
DeepSeek-V3.2-Speciale
DeepSeek
DeepSeek-V3.2-Speciale is a high-compute variant of the DeepSeek-V3.2 model, created specifically for deep reasoning and advanced problem-solving tasks. It builds on DeepSeek Sparse Attention (DSA), a custom long-context attention mechanism that reduces computational overhead while preserving high performance. Through a large-scale reinforcement learning framework and extensive post-training compute, the Speciale variant surpasses GPT-5 on reasoning benchmarks and matches the capabilities of Gemini-3.0-Pro. The model achieved gold-medal performance in the International Mathematical Olympiad (IMO) 2025 and International Olympiad in Informatics (IOI) 2025. DeepSeek-V3.2-Speciale does not support tool-calling, making it purely optimized for uninterrupted reasoning and analytical accuracy. Released under the MIT license, it provides researchers and developers an open, state-of-the-art model focused entirely on high-precision reasoning.Starting Price: Free -
15
Ministral 3
Mistral AI
Mistral 3 is the latest generation of open-weight AI models from Mistral AI, offering a full family of models, from small, edge-optimized versions to a flagship, large-scale multimodal model. The lineup includes three compact “Ministral 3” models (3B, 8B, and 14B parameters) designed for efficiency and deployment on constrained hardware (even laptops, drones, or edge devices), plus the powerful “Mistral Large 3,” a sparse mixture-of-experts model with 675 billion total parameters (41 billion active). The models support multimodal and multilingual tasks, not only text, but also image understanding, and have demonstrated best-in-class performance on general prompts, multilingual conversations, and multimodal inputs. The base and instruction-fine-tuned versions are released under the Apache 2.0 license, enabling broad customization and integration in enterprise and open source projects.Starting Price: Free -
16
GLM-4.6V
Zhipu AI
GLM-4.6V is a state-of-the-art open source multimodal vision-language model from the Z.ai (GLM-V) family designed for reasoning, perception, and action. It ships in two variants: a full-scale version (106B parameters) for cloud or high-performance clusters, and a lightweight “Flash” variant (9B) optimized for local deployment or low-latency use. GLM-4.6V supports a native context window of up to 128K tokens during training, enabling it to process very long documents or multimodal inputs. Crucially, it integrates native Function Calling, meaning the model can take images, screenshots, documents, or other visual media as input directly (without manual text conversion), reason about them, and trigger tool calls, bridging “visual perception” with “executable action.” This enables a wide spectrum of capabilities; interleaved image-and-text content generation (for example, combining document understanding with text summarization or generation of image-annotated responses).Starting Price: Free -
17
GLM-4.1V
Zhipu AI
GLM-4.1V is a vision-language model, providing a powerful, compact multimodal model designed for reasoning and perception across images, text, and documents. The 9-billion-parameter variant (GLM-4.1V-9B-Thinking) is built on the GLM-4-9B foundation and enhanced through a specialized training paradigm using Reinforcement Learning with Curriculum Sampling (RLCS). It supports a 64k-token context window and accepts high-resolution inputs (up to 4K images, any aspect ratio), enabling it to handle complex tasks such as optical character recognition, image captioning, chart and document parsing, video and scene understanding, GUI-agent workflows (e.g., interpreting screenshots, recognizing UI elements), and general vision-language reasoning. In benchmark evaluations at the 10 B-parameter scale, GLM-4.1V-9B-Thinking achieved top performance on 23 of 28 tasks.Starting Price: Free -
18
GLM-4.5V-Flash
Zhipu AI
GLM-4.5V-Flash is an open source vision-language model, designed to bring strong multimodal capabilities into a lightweight, deployable package. It supports image, video, document, and GUI inputs, enabling tasks such as scene understanding, chart and document parsing, screen reading, and multi-image analysis. Compared to larger models in the series, GLM-4.5V-Flash offers a compact footprint while retaining core VLM capabilities like visual reasoning, video understanding, GUI task handling, and complex document parsing. It can serve in “GUI agent” workflows, meaning it can interpret screenshots or desktop captures, recognize icons or UI elements, and assist with automated desktop or web-based tasks. Although it forgoes some of the largest-model performance gains, GLM-4.5V-Flash remains versatile for real-world multimodal tasks where efficiency, lower resource usage, and broad modality support are prioritized.Starting Price: Free -
19
GLM-4.5V
Zhipu AI
GLM-4.5V builds on the GLM-4.5-Air foundation, using a Mixture-of-Experts (MoE) architecture with 106 billion total parameters and 12 billion activation parameters. It achieves state-of-the-art performance among open-source VLMs of similar scale across 42 public benchmarks, excelling in image, video, document, and GUI-based tasks. It supports a broad range of multimodal capabilities, including image reasoning (scene understanding, spatial recognition, multi-image analysis), video understanding (segmentation, event recognition), complex chart and long-document parsing, GUI-agent workflows (screen reading, icon recognition, desktop automation), and precise visual grounding (e.g., locating objects and returning bounding boxes). GLM-4.5V also introduces a “Thinking Mode” switch, allowing users to choose between fast responses or deeper reasoning when needed.Starting Price: Free -
20
GLM-4.7
Zhipu AI
GLM-4.7 is an advanced large language model designed to significantly elevate coding, reasoning, and agentic task performance. It delivers major improvements over GLM-4.6 in multilingual coding, terminal-based tasks, and real-world software engineering benchmarks such as SWE-bench and Terminal Bench. GLM-4.7 supports “thinking before acting,” enabling more stable, accurate, and controllable behavior in complex coding and agent workflows. The model also introduces strong gains in UI and frontend generation, producing cleaner webpages, better layouts, and more polished slides. Enhanced tool-using capabilities allow GLM-4.7 to perform more effectively in web browsing, automation, and agent benchmarks. Its reasoning and mathematical performance has improved substantially, showing strong results on advanced evaluation suites. GLM-4.7 is available via Z.ai, API platforms, coding agents, and local deployment for flexible adoption.Starting Price: Free -
21
Qwen3.5
Alibaba
Qwen3.5 is a next-generation open-weight multimodal large language model designed to power native vision-language agents. The flagship release, Qwen3.5-397B-A17B, combines a hybrid linear attention architecture with sparse mixture-of-experts, activating only 17 billion parameters per forward pass out of 397 billion total to maximize efficiency. It delivers strong benchmark performance across reasoning, coding, multilingual understanding, visual reasoning, and agent-based tasks. The model expands language support from 119 to 201 languages and dialects while introducing a 1M-token context window in its hosted version, Qwen3.5-Plus. Built for multimodal tasks, it processes text, images, and video with advanced spatial reasoning and tool integration. Qwen3.5 also incorporates scalable reinforcement learning environments to improve general agent capabilities. Designed for developers and enterprises, it enables efficient, tool-augmented, multimodal AI workflows.Starting Price: Free -
22
Mistral Small 4
Mistral AI
Mistral Small 4 is an advanced open-source AI model developed by Mistral AI that combines reasoning, coding, and multimodal capabilities into a single system. It unifies the strengths of previous models such as Magistral for reasoning, Pixtral for multimodal processing, and Devstral for agentic coding tasks. The model can handle both text and image inputs, allowing it to perform tasks ranging from conversational chat to visual analysis and document understanding. Built with a mixture-of-experts architecture, Mistral Small 4 delivers efficient performance while scaling to complex workloads. It also features a configurable reasoning parameter that allows users to switch between fast responses and deeper analytical outputs. With a large context window and optimized inference performance, the model supports long-form interactions and complex workflows.Starting Price: Free -
23
MiMo-V2-Pro
Xiaomi Technology
Xiaomi MiMo-V2-Pro is a flagship AI foundation model designed to power real-world agentic workflows and complex task execution. It is built to function as the core intelligence behind agent systems, enabling orchestration of multi-step processes and production-level tasks. The model demonstrates strong capabilities in coding, tool usage, and search-based tasks, performing competitively on global benchmarks. With its large-scale architecture and extended context window, it can handle long and complex interactions efficiently. MiMo-V2-Pro is optimized for practical applications, delivering reliable performance across development, automation, and enterprise workflows.Starting Price: $1/million tokens -
24
Trinity-Large-Thinking
Arcee AI
Trinity Large Thinking is a frontier open source reasoning model developed by Arcee AI, designed specifically for complex, multi-step problem solving and autonomous agent workflows that require long-horizon planning and tool use. Built on a sparse Mixture-of-Experts architecture with roughly 400 billion total parameters but only about 13 billion active per token, the model achieves high efficiency while maintaining strong reasoning performance across tasks such as mathematical problem solving, code generation, and multi-step analysis. It introduces extended chain-of-thought reasoning capabilities, allowing the model to generate intermediate “thinking traces” before producing final answers, which improves accuracy and reliability in complex scenarios. Trinity Large Thinking supports a very large context window of up to 262K tokens, enabling it to process long documents, maintain state across extended interactions, and operate effectively in continuous agent loops.Starting Price: Free -
25
Qwen3.6-35B-A3B
Alibaba
Qwen3.5-35B-A3B is part of the Qwen3.5 “Medium” model series, designed as a highly efficient, multimodal foundation model that balances strong reasoning ability with practical deployment requirements. It uses a Mixture-of-Experts (MoE) architecture with 35 billion total parameters but activates only about 3 billion per token, allowing it to deliver performance comparable to much larger models while significantly reducing computational cost. The model integrates a hybrid attention mechanism that combines linear attention with standard attention layers, enabling efficient long-context processing and improved scalability for complex tasks. As a native vision-language model, it can process both text and visual inputs, supporting use cases such as multimodal reasoning, coding, and agent-based workflows. It is designed to function as a general-purpose “AI agent,” capable of planning, tool use, and structured problem solving rather than just conversational responses.Starting Price: Free -
26
GPT-5.5 Pro
OpenAI
GPT-5.5 Pro is an advanced AI model designed to handle complex, real-world work with greater autonomy and efficiency. It understands user intent quickly and can execute multi-step tasks such as coding, research, data analysis, and document creation with minimal guidance. The model is built to plan, use tools, and refine its outputs until tasks are complete. It excels in knowledge work, software development, and analytical problem-solving. With strong reasoning and persistence, GPT-5.5 Pro can manage long-running workflows across tools and systems. It delivers high-quality results while maintaining speed and efficiency. Overall, it enables individuals and teams to complete demanding tasks faster and more accurately.Starting Price: $30 per 1M tokens (input) -
27
Sakana Fugu
Sakana AI
Sakana Fugu is an AI model and multi-agent AI system delivered through a single OpenAI-compatible API. The platform dynamically orchestrates a pool of powerful models to solve complex tasks without requiring users to manually choose models, assign roles, or design agent workflows. Fugu learns how to assemble and coordinate agents for coding, reasoning, research, cybersecurity, scientific analysis, and other quality-critical work. Users can choose between Fugu for balanced performance and latency or Fugu Ultra for harder, high-stakes tasks that need deeper expert coordination. The platform also allows users to control which models or providers can participate in the agent pool to support privacy, compliance, and organizational requirements. Sakana Fugu helps teams access collective AI intelligence through one endpoint while reducing single-vendor dependency and improving performance on complex multi-step workflows.Starting Price: $20/month -
28
Hy3
Tencent
Hy3 preview is Tencent Hy’s most intelligent model in the Hy series to date, built as a 295B-parameter Mixture-of-Experts model with 21B activated parameters, 3.8B MTP layer parameters, and support for up to a 256K token context window. As the first model trained on Tencent Hy’s rebuilt infrastructure, Hy3 preview is designed to improve real-world usability across complex reasoning, instruction following, context learning, coding, agent capabilities, and overall inference performance. It integrates both fast and slow thinking capabilities, allowing direct responses for simpler tasks and deeper reasoning for complex math, coding, and reasoning work. The model is built around well-rounded capabilities across long-context understanding, instruction following, tool use, and agent workflows, with evaluation focused not only on standard benchmarks but also on authentic business and development scenarios.Starting Price: Free -
29
GPT-5
OpenAI
GPT-5 is OpenAI’s most advanced AI model, delivering smarter, faster, and more useful responses across a wide range of topics including math, science, finance, and law. It features built-in thinking capabilities that allow it to provide expert-level answers and perform complex reasoning. GPT-5 can handle long context lengths and generate detailed outputs, making it ideal for coding, research, and creative writing. The model includes a ‘verbosity’ parameter for customizable response length and improved personality control. It integrates with business tools like Google Drive and SharePoint to provide context-aware answers while respecting security permissions. Available to everyone, GPT-5 empowers users to collaborate with an AI assistant that feels like a knowledgeable colleague.Starting Price: $1.25 per 1M tokens -
30
OpenAI o3
OpenAI
OpenAI o3 is an advanced AI model designed to enhance reasoning capabilities by breaking down complex instructions into smaller, more manageable steps. It offers significant improvements over previous AI iterations, excelling in coding tasks, competitive programming, and achieving high scores in mathematics and science benchmarks. Available for widespread use, OpenAI o3 supports advanced AI-driven problem-solving and decision-making processes. The model incorporates deliberative alignment techniques to ensure its responses align with established safety and ethical guidelines, making it a powerful tool for developers, researchers, and enterprises seeking sophisticated AI solutions.Starting Price: $2 per 1 million tokens