Guide

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

Fast Grok coding model tuned for agentic engineering and iterative edits

Stronger Opus tier for advanced software work and high-stakes reasoning

Stronger Opus tier for advanced software work and high-stakes reasoning

Stronger Opus tier for advanced software work and high-stakes reasoning

Stronger Opus tier for advanced software work and high-stakes reasoning

Stronger Opus tier for advanced software work and high-stakes reasoning

Stronger Opus tier for advanced software work and high-stakes reasoning

Stronger Opus tier for advanced software work and high-stakes reasoning

Grok coding model for agentic engineering, edits, and codebase workflows

Stronger Opus tier for advanced software work and high-stakes reasoning

Image model for prompt-driven generation, editing, and visual design workflows

Efficient model for low-latency assistance, extraction, and routine automation

Efficient model for low-latency assistance, extraction, and routine automation

Stronger Opus tier for advanced software work and high-stakes reasoning

Low-latency speech generation with steerable prompts and expressive audio tags

Vision-language model for embodied reasoning: spatial understanding, task planning, and physical-world agentic robotics

Stronger Opus tier for advanced software work and high-stakes reasoning

Video model for prompt-guided generation, editing, and motion workflows

Video model for prompt-guided generation, editing, and motion workflows

Open Gemma instruction model for efficient chat and self-hosted deployments

MiniMax model for chat, coding, office work, and agentic tasks

Claude Opus 4.6 Fast from Venice AI - text, image input, 1,000,000 token context

Open Llama instruction model for multilingual chat, reasoning, and coding

Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration.

Fast-mode variant of [Opus 4.6](/anthropic/claude-opus-4.6) - identical capabilities with higher output speed at premium 6x pricing. Learn more in Anthropic's docs: https://platform.claude.com/docs/en/build-with-claude/fast-mode

GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on...

Strong GLM coding model for agentic engineering, terminals, and repository generation

Strong GLM coding model for agentic engineering, terminals, and repository generation

Flagship GLM model for hybrid reasoning, coding, and agentic engineering

Open Gemma instruction model for efficient chat and self-hosted deployments

Open Gemma instruction model for efficient chat and self-hosted deployments

Flagship GLM model for hybrid reasoning, coding, and agentic engineering

Strong GLM coding model for agentic engineering, terminals, and repository generation

Strong GLM coding model for agentic engineering, terminals, and repository generation

Video model for prompt-guided generation, editing, and motion workflows

Video model for prompt-guided generation, editing, and motion workflows

Earlier Qwen multimodal workhorse for million-token agent and document tasks

Qwen 3.6 Plus from Fireworks AI - text, image input, 262,144 token context

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

Higher-fidelity Grok Imagine image model for prompt-driven generation, editing, and visual design workflows

Google Gemma 4 31B Instruct from Venice AI - text, image, video input, 256,000 token context

Largest Gemma 4 instruction model for open, self-hosted chat and reasoning

Flagship GLM model for hybrid reasoning, coding, and agentic engineering

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...

Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...