Best AI Tools for AI Multimodal Reasoning

Claude Fable 5 is Anthropic's Mythos-class model released on June 9, 2026, focused on creative writing, worldbuilding, and narrative depth. It was suspended from distribution on June 12, 2026, under US export controls, making it a limited-availability release.

Claude Opus 5 is Anthropic's flagship model, released 24 July 2026 with a 1M-token context window and five selectable effort levels (low, medium, high, xhigh, max). Effort is the main control: output token spend runs roughly 8x from low to max, and Artificial Analysis measures a 407-Elo spread in task quality across that range, so the same model behaves like several different price and capability tiers. API pricing is $5 per million input tokens and $25 per million output, with cache writes at $6.25 and cache hits at $0.50. It leads the Intelligence Index at 60.7 and tops the Coding Agent Index, scoring 89 percent on Terminal-Bench v2.1 at max effort and 53 percent on Humanity's Last Exam.

DeepSeek is the architect of the 'DeepSeek movement,' a fundamental shift in AI development that prioritizes extreme efficiency over raw compute. Founded by High-Flyer Quant, they proved that architectural innovations like Multi-head Latent Attention (MLA) and DeepSeekMoE could match the performance of $100B models like GPT-4o and Claude 3.5 while costing 95% less to train and run. Their ecosystem includes the flagship DeepSeek-V3, the reasoning-heavy DeepSeek-R1, and the state-of-the-art DeepSeek-VL2 for high-fidelity OCR and vision tasks. DeepSeek is committed to the open-source community, regularly releasing model weights and technical papers that have democratized frontier-level AI for developers globally.

Kimi k1.5 is a multimodal large language model from Moonshot AI, specifically engineered for high-fidelity technical reasoning and long-context processing. It is a key player in the 'DeepSeek movement,' matching the reasoning performance of frontier models like GPT-5.2 Codex and Claude 4.5 while remaining significantly more cost-effective. It features a massive 2 million token context window and joint text-vision reasoning, making it ideal for complex coding, mathematical proofs, and large-scale document analysis. The model is built using advanced Reinforcement Learning (RL) to achieve deep 'Chain-of-Thought' capabilities.

Qwen 2.5-VL is Alibaba's state-of-the-art open-weight multimodal model, designed to bridge the gap between open source and proprietary vision-language models. It features advanced 'NaViVi' (Native Dynamic Resolution) architecture, allowing it to process images of any resolution and videos of any length with extreme precision. It excels at complex visual reasoning, document understanding (OCR), and real-time video analysis, matching or exceeding GPT-4o in many multimodal benchmarks while remaining fully open for the community to build upon.

Llama 3.2 Vision is Meta's first open-weight multimodal model family, bringing high-fidelity image reasoning to the Llama ecosystem. It integrates vision and text into a unified transformer architecture, enabling it to understand images, charts, and diagrams with the same ease as text. Available in 11B and 90B versions, it is designed for efficiency and edge deployment, making it the industry standard for developers building open multimodal applications that require deep reasoning and broad community support.

Pixtral Large is Mistral AI's flagship 124B parameter multimodal model, designed to compete directly with GPT-4o and Claude 3.5 Sonnet. Built on the Mistral Large 2 foundation, it features a native vision encoder that allows it to reason across text and images with extreme precision. It excels at complex diagram understanding, mathematical reasoning with visual context, and high-fidelity image captioning. Pixtral Large is released under the Mistral Research License, allowing developers to explore frontier-level vision-language capabilities with open weights.

InternVL 2.5 is a world-class open-source multimodal large language model (MLLM) that consistently tops the leaderboards for open-weight vision reasoning. It features a powerful 78B parameter architecture with a specialized vision-language alignment that excels at OCR, document understanding, and complex visual Q&A. It is designed to bridge the gap between open models and GPT-4V, offering exceptional performance across a wide range of multimodal benchmarks while remaining fully open for community development.

Gemini 3.5 Flash is a mid-tier multimodal model announced at Google I/O on May 19, 2026. It delivers strong reasoning, coding, and long-context performance at lower latency and cost than Ultra-tier models, with native support for text, images, audio, and video inputs.

Gemini Omni is a single Google model announced at I/O 2026 that can generate and reason across text, images, video, and audio from unified prompts. It is designed to reduce the need for separate modality-specific models by handling generation and understanding in one architecture.

DeepSeek V4-Pro is a high-performance language model from DeepSeek. The model itself was released on April 24, 2026, and permanent pricing was announced on May 31, 2026. It offers strong reasoning and coding performance at a competitive price point, with open weights available for local deployment.

StepFun Step 3.7 Flash is a 198-billion-parameter mixture-of-experts vision-language model released on May 28-29, 2026. It supports text, image, and video understanding with a focus on efficient inference and strong multimodal reasoning.

OpenAI's most advanced model to date, featuring a 2M context window and specialized training for complex multi-step reasoning. It excels at architectural planning, deep research, and autonomous code generation.

Google's most powerful multimodal model, capable of processing hours of video, thousands of lines of code, or massive document sets in a single prompt. Features native audio/video understanding.

Nemotron 3 Nano Omni is NVIDIA's compact-but-capable multimodal stack for agentic workflows: one family of endpoints that accept text, images, audio, or video (depending on route) and return text answers, useful as the 'perception and reasoning' layer for assistants that must read screens, documents, calls, or clips without chaining four different specialist models. Optimized for efficiency at scale; exposed on fal.ai as separate text, vision, audio, and video reasoning endpoints built on the same foundation.

Qwen-VL-Max is a high-performance vision-language model from Alibaba, capable of understanding images, charts, and documents, and answering questions about them. It is available through the Qwen API and Tongyi Qianwen apps.

Anthropic's frontier Opus-tier model announced on April 16, 2026, with substantial gains on the hardest coding tasks, higher-resolution vision input, a new xhigh effort level, file-system-based memory recall across sessions, and the Task Budgets public beta. Available across the Anthropic API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry.

Anthropic's Mythos-class model announced on June 9, 2026, shares the same capabilities as Claude Fable 5 without the safety classifiers. It is offered only in limited availability to approved customers through Anthropic's Project Glasswing program.

DeepSeek V4-Flash is the efficient sibling of V4-Pro, offering a 1M-token context window and configurable thinking modes at a fraction of the API cost. It is optimized for high-throughput chat, classification, bulk extraction, and agentic coding workloads, with a July 2026 update that boosted agent and coding benchmarks.

DeepSeek R1 is a 671B-parameter open-weight reasoning model that matches o1-class performance on math, code, and logic benchmarks through reinforcement learning on verifiable tasks. It exposes chain-of-thought reasoning and is available as MIT-licensed local weights and via API, with the R1-0528 update in May 2025 further improving math and code reasoning.

DeepSeek V3.2 is a 128K-context mixture-of-experts model that unified thinking and non-thinking modes in the V3 line and introduced DeepSeek Sparse Attention. It served as the December 2025 flagship before V4 and remains available for self-hosting and as a historical comparison point.

GLM-5V-Turbo is a vision-language variant of the GLM-5 family, built for multimodal coding, visual reasoning, and image-plus-text agent workflows. It offers a 200K context window and 128K maximum output.

GLM-4.6V is a 2025 vision-language model in the GLM family, offering visual reasoning, tool calling, and frontend code replication. It supports a 128K context window and a 32K maximum output.

GLM-OCR is a specialized GLM model for extracting structured Markdown from PDFs and images. It supports a 65K context window and is optimized for layout-aware document parsing rather than open-ended chat.

GLM-4V-Flash is a free-tier vision model in the GLM family, offering zero-cost image understanding and document snapshot analysis with a 16K context window.

Gemini 1.5 Pro is a mid-2024 multimodal model that handles text, images, audio, and video with a 1M-token context window (extendable to 2M in limited preview). It powers complex document analysis, code understanding, and video QA in Google AI Studio and the Gemini API.

Gemini 1.5 Flash is a lightweight, speed-optimized variant of Gemini 1.5 Pro. It keeps the same 1M-token context window and multimodal input support while offering much lower latency and cost, making it ideal for high-volume agents and summarization.

Gemini 2.0 Flash is a late-2024 general-purpose model optimized for agentic workflows, native tool use, and fast multimodal output. It supports text, image, audio, and video input and is the default model for many Gemini API applications.

Gemini 2.5 Pro is an early-2025 flagship model focused on complex reasoning, advanced coding, and detailed multimodal understanding. It builds on Gemini 2.0 with improved instruction following and is positioned for high-stakes enterprise and research tasks.

Gemma 3 is an open-weights family of multimodal models from Google, ranging from 1B to 27B parameters. It supports text and image input, a 128K context window, and is released under a permissive license for research and commercial use.

Grok 4.3 is xAI's general-purpose frontier model released in April 2026. It pairs strong reasoning and coding with a 1-million-token context window, making it practical for analyzing long documents and large codebases in a single pass.

Grok 4.20 is a beta model from xAI released in February 2026. It features a 2-million-token context window and multi-agent architecture, targeting complex reasoning and long-horizon workflows that benefit from coordinated sub-agents.

Hybrid Mamba-Transformer MoE reasoning model released March 2025, built on Hunyuan TurboS with 52 billion active parameters and a 256K context window. It focuses compute on reinforcement-learning post-training and scores strongly on math, coding, and graduate-level reasoning tasks.

Open-weight reasoning variant of Hunyuan 2.0 with a 131K context window, designed for complex problem-solving, math, and long-context reasoning workflows.

Kimi K2.5 is Moonshot AI's open-weight multimodal model released January 27, 2026. It supports text, image, and video input, thinking and non-thinking modes, and a 256K context window, with strong performance on agent, coding, and vision tasks. Moonshot announced the kimi-k2.5 API will be retired on August 31, 2026, so production workloads should plan a migration path to K2.6 or K3.

Kimi K2.6 is Moonshot AI's open-weight multimodal model released April 21, 2026. It supports text, image, and video input, thinking and non-thinking modes, and a 256K context window, with improved long-context coding stability and agent-task performance.

Llama 4 Maverick is Meta's flagship open-weight model, released in April 2025 as part of the Llama 4 family. It uses a Mixture-of-Experts architecture with 17B active parameters and around 400B total parameters, natively understands text and images, and supports a 1M-token context window.

Llama 4 Scout is Meta's efficient Llama 4 variant, released in April 2025. It is a Mixture-of-Experts model with 17B active parameters and 109B total parameters across 16 experts, natively multimodal for text and images, and supports an industry-leading 10M-token context window.

A 675B-parameter sparse mixture-of-experts model with 41B active parameters and a 262K context window, released under Apache 2.0. It handles text and vision tasks, supports strong multilingual performance, and is designed for both research and enterprise deployment.

A 119B-parameter MoE model with 6B active parameters and a 256K context window, released under Apache 2.0. It unifies instruct, reasoning, multimodal, and agentic coding capabilities in a single efficient model with configurable reasoning effort.

A general-purpose document parsing model that overcomes traditional OCR limitations by understanding complex page layouts. It extracts structured text, tables as Markdown or LaTeX, bounding boxes, and semantic classes from unstructured PDFs and images.

A 4B-parameter multimodal, multilingual small language model designed as a robust content-safety moderator. It supports standard taxonomy safety classification and custom-policy enforcement with reasoning traces for text and image inputs.

NVIDIA's open foundation model for humanoid robot reasoning and control, combining an Eagle-based vision-language backbone with a diffusion transformer (DiT) action head for language-conditioned manipulation across diverse embodiments.

Microsoft announced a family of MAI-branded models at Build 2026, including MAI-Thinking-1 for reasoning, MAI-Image-2.5 for image generation and editing, MAI-Voice-2 for expressive text-to-speech, MAI-Transcribe-1.5 for speech-to-text, MAI-Code-1-Flash for coding in GitHub Copilot, and Scout as a workplace personal agent. They integrate tightly with Microsoft 365, Azure, and GitHub.

Muse Spark 1.1 is Meta Superintelligence Labs' multimodal reasoning model, released 9 July 2026. It has a 1M-token context window, accepts text, images, video and PDFs, and is built for agentic work: tool use, computer use, coding, and multi-agent orchestration. It is free to use in the Meta AI app and at meta.ai in Thinking mode, and available to developers through the new Meta Model API at $1.25 per million input tokens and $4.25 per million output, with $20 in starting credits. Unlike the Llama family it succeeds in practice, Muse Spark is closed-weight.

Inkling is the first open-weights model from Thinking Machines Lab, released 15 July 2026 under Apache 2.0. It is a 975B-parameter mixture of experts with 41B active per token, trained from scratch on 45 trillion tokens of text, images, audio and video, with a context window up to 1M tokens. The architecture uses 256 routed experts plus 2 shared experts per layer with 6 routed experts active per token, a sigmoid router, and interleaved sliding-window and global attention at a 5:1 ratio. It accepts text, image and audio input natively and returns text. Weights are on Hugging Face in both the original format and an NVFP4 checkpoint for Blackwell hardware. A distilled Inkling-Small followed on 31 July.