AI Models

Compare the leading AI models across Global, China and Japan — specs, heat scores, API console access and official links, all in one place.

Showing 1–51 of 79 modelsTotal 79 models
Claude Opus 5
100
Anthropic’s flagship Claude model built for complex reasoning, AI Agents, software development, and enterprise knowledge workflows.
GPT-5.6 Luna
99
An efficient GPT-5.6 series model optimized for speed, cost efficiency, and intelligent performance across large-scale AI applications.
GPT-5.5
99
OpenAI flagship model, a multimodal AI natively supporting text, images, and audio.
GPT-5.5 Pro
99
I’ve been using GPT-5.5 Pro with a few colleagues for the past several weeks, mostly on the kinds of jobs where regular chatbots tend to fall apart: long documents, messy research questions, code debugging, and tasks that need more than one or two steps of reasoning.
Claude Opus 4.8
98
Claude Opus 4.8 is Anthropic's most powerful Opus-series model, featuring multimodal input, reasoning, and a 1M-token context window, excelling in complex reasoning and coding.
GPT-5.6 Luna Pro
97
OpenAI’s next-generation efficient AI model, balancing speed, cost, and intelligence for chat, coding, and automation tasks.
DeepSeek R2
96
Open-source specialized reasoning model, with MATH benchmark test scores comparable to GPT-4o, released under the MIT open-source license.
Gemini 3.6 Flash
96
Claude Opus 4.7
96
Fast-mode variant of [Opus 4.7](/anthropic/claude-opus-4.7) - identical capabilities with higher output speed at premium 6x pricing.
DeepSeek V4 Pro 0813
96
DeepSeek V4 Pro 0813 feels more like a workhorse model to me. For casual chat or light editing, I wouldn’t bother. Its value shows up when I’m digging through code, chasing bugs, or handling tightly connected tasks.
Gemini 3.1 Pro
95
Google DeepMind’s latest Gemini Pro model delivers advanced reasoning, multimodal understanding, coding support, and enterprise AI capabilities for professional applications.
GPT-5.6 Sol Pro
95
The highest-performance model in the GPT-5.6 family, built for advanced reasoning, complex tasks, and long-running professional workflows.
Claude Sonnet 5
95
High‑performance agentic model for coding, tool use, and reasoning—secure, cost‑effective, and available across all plans.
Gemini 3.7 Flash
95
Just three weeks after the last update, Google has released another new model. Gemini 3.7 Flash is more than a minor refresh. Its coding, Agent, and automation capabilities have all improved noticeably, while API pricing is cut in half through the end of 2026. It may not be the most powerful model available, but for developers, the value proposition is hard to ignore.
GPT-5.6 Sol
94
OpenAI’s flagship reasoning model within the GPT-5.6 family, designed for advanced problem-solving, professional workflows, and high-complexity AI applications.
Grok 4.6
94
Elon Musk has a habit of overselling things, so most Grok announcements are worth taking with a grain of salt. But with Grok 4.6, the numbers are much harder to dismiss.
Gemini 3.5 Flash
93
Gemini 3.5 Flash delivers near-Pro intelligence at Flash-tier cost and speed: Pro-level coding proficiency, parallel agentic execution, all at the same price point as a Flash model.
Claude Fable 5
93
Claude Fable 5 is Anthropic's Mythos-class model for autonomous knowledge work and coding, with multimodal input and reasoning support.
Grok 4.5
93
xAI’s latest flagship model built for coding, AI Agents, and knowledge work with powerful reasoning and problem-solving capabilities.
GPT-5.6 Terra Pro
91
an advanced AI reasoning model from OpenAI’s GPT-5.6 family, designed to deliver a strong balance between intelligence, performance, and cost efficiency.
Llama 4 Scout
91
Meta open-source LLM allowing commercial use, local execution, and fine-tuning.
Qwen3-235B
90
Alibaba MoE model achieving high-quality reasoning at low cost with 22B active parameters.
DeepSeek V4 Pro(Legacy)
90
DeepSeek’s flagship MoE model designed for complex reasoning, advanced coding, AI Agents, and long-context professional workflows.
Qwen3.8 2.4T A95B
90
What stands out to me isn’t how well it answers a single question—it’s whether it can keep a complex task going. In my own experience, hitting a wall usually isn’t about missing the basics. It’s about finding something that can pick up where you left off and move forward.
GPT-5.6 Terra
89
A balanced GPT-5.6 series model designed to deliver strong intelligence, efficient performance, and cost-effective AI solutions for everyday and enterprise applications.
Muse Spark 1.2
89
Muse Spark 1.2 landed just a month after version 1.1. This release is more focused. Meta is putting more weight behind code generation, software engineering, and its new terminal-based agent, Muse Code.
Qwen3.8 Max
88
Alibaba released Qwen3.8-Max on August 3. It has 2.4 trillion total parameters, activates around 95 billion parameters per inference step, and supports a 1 million token context window. The pitch is not just “better coding.” The model is supposed to handle the full process: break down requirements, write code, debug, iterate, and eventually deliver a working project.
Muse Spark 1.1
88
Meta’s multimodal reasoning model optimized for AI Agents, coding, tool use, and complex task automation.
Grok 4.3
88
xAI’s flagship AI reasoning model designed for complex problem solving, multimodal understanding, tool use, and advanced AI Agent workflows.
DeepSeek V4 Flash 0731
87
DeepSeek’s advanced AI model optimized for coding, AI Agents, tool calling, complex reasoning, and large-scale AI applications with million-token context support.
Qwen3.7 Max
87
China's strongest AI of 2026, deep reasoning + autonomous execution, from conversation to getting things done.
Mistral Large 2
84
French AI lab Mistral flagship model popular for EU regulatory compliance and privacy-conscious users.
ERNIE 5.1
84
Baidu’s latest flagship foundation model with enhanced reasoning, AI Agent capabilities, knowledge understanding, and content creation for enterprise and developer applications.
Qwen3.6 Flash
81
Alibaba’s Qwen3.6 Flash has been getting a fair amount of attention among developers. After using it for a few days, my impression is pretty straightforward: it is not trying to beat the Plus model on raw capability.
Qwen3.7 Plus
81
Text + image input, text output. Upgraded vision-language capabilities, with full agentic strength in coding and tool use retained.
Nano Banana 2
80
Google's latest image model delivers pro-grade quality at blazing speed, excels at complex generation and iterative editing, and combines deep understanding with high cost-effectiveness.
Qwen3.7 Flash
79
Alibaba’s Qwen3.7-Flash is a high-performance lightweight AI model optimized for multimodal understanding, AI Agents, coding, and fast, cost-efficient reasoning.
MiMo-V2.5-Pro
79
MiMo-V2.5-Pro is a flagship MoE model specialized in long-term agent tasks and complex coding. It stably executes over 1,000 tool calls, reduces token consumption by 40–60% vs. competitors, and is open-sourced under MIT license.
Nano Banana Pro
79
Google's most powerful image model, featuring precise text rendering, multi-image fusion, and 4K output, built for professional design.
Gemini 3.1 Flash Lite
77
Google's lightweight multimodal model, supporting text, image, audio, video, and PDF. Delivers low latency and high throughput for large-scale agentic workloads.
Gemini 3.5 Flash Lite
74
Google’s lightweight multimodal AI model optimized for high-volume tasks, AI Agent workflows, and cost-efficient AI applications.
Nemotron 3 Ultra
74
NVIDIA Nemotron 3 Ultra is an open reasoning model from NVIDIA, with 550B total parameters (55B active), a 1M-token context window, and excels at multi-step reasoning and agent orchestration.
Doubao Pro
72
ByteDance flagship model with Japanese-Chinese-English trilingual support for enterprise APIs.
Kimi K3
72
Moonshot AI’s flagship model featuring long-context understanding, multimodal capabilities, advanced reasoning, and AI Agent task execution.
Mistral Medium 3.5
71
Mistral AI’s latest Medium model delivers advanced reasoning, coding capabilities, multimodal understanding, and AI Agent support for professional and enterprise applications.
Nano Banana 2 Lite
69
Google's fastest, most cost-efficient image generation model — 4-second output, low cost, built for high-concurrency development and scaled visual applications.
GLM 5.3
68
Just two months after GLM-5.2 landed in June, Zhipu AI released GLM-5.3 on August 14. The interesting part is what didn’t change. GLM-5.3 keeps the same base model and the same MoE architecture with about 743 billion parameters. Most of the gains come from scaling up post-training instead.
GLM 5.2
65
Z.ai's large-scale reasoning model with 1M context, excels at coding and complex automation, supports high-intensity reasoning, and handles full development workflows in a single task.
Kimi K2.7 Code
64
MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts...
LongCat 2.0
64
Meituan’s next-generation open-source AI model optimized for long-context understanding, coding, and intelligent Agent task execution.
Grok Build 0.1
61
an AI application development tool launched by xAI, designed to help developers and businesses quickly create intelligent applications powered by Grok models.

Frequently Asked Questions

How many AI models are listed?

Aivoax continuously collects and updates information about different AI models.
The platform covers major international models such as GPT, Claude, Gemini and DeepSeek, as well as Chinese-developed models including Qwen, Ernie and Hunyuan.
Models are organized by category, including general-purpose language models, multimodal models and code-focused models, making it easier to find options based on different needs.
Since the AI industry changes quickly, we regularly review new releases and update information about existing models.

How are models ranked?

Aivoax organizes model information from different perspectives, including regions and usage scenarios.
Users can explore models based on global, Japan and China views, as well as different needs such as enterprise use, learning and developer workflows.
Rankings are provided as a reference for understanding current attention and popularity. They do not represent official performance rankings.
When choosing a model, factors such as use case, pricing, speed and available features should also be considered.

Where can I check a model's specs and API access?

Each model page includes key information such as model overview, context length, pricing details, open-source status, release information and official links.
For developers, we also provide API documentation links to help with evaluation and integration.
Because AI models are updated frequently, specifications may change over time. Please check official documentation before production use.

What is the heat score?

The Heat Score is a reference indicator used by Aivoax to show how much attention an AI model is receiving.
It is based on publicly available signals such as search trends, community discussions and user interest.
A higher score indicates greater current attention, but it does not necessarily mean the model has better performance.
Different models are suitable for different tasks, including coding, content creation and business applications.

What's the difference between a model and a tool?

An AI model is the underlying technology that provides AI capabilities, such as GPT, Claude and Qwen. Developers usually access these models through APIs.
An AI tool is a finished application built using one or more AI models, such as chat assistants, writing tools and image generation services.
In simple terms, models provide the core capability, while tools turn that capability into products that users can directly use. Aivoax organizes both separately for easier discovery.

What else is on a model's detail page?

Model detail pages include more than basic specifications. They also provide information about suitable use cases, key features, limitations and related models.
These details are designed to help users compare different options more efficiently.
There is no single AI model that works best for everyone. The right choice depends on your goals, budget and usage environment.