Best LLMs by Use Case 2026 | AI Model Rankings for Every Task

Real-time LLM leaderboards by use case. Find the best AI models for coding, science, legal, marketing, finance, health and more. Updated daily with transparent benchmarks.

MoonshotAI: Kimi K2.6

MoonshotAI: Kimi K2.6

by moonshotai

262.14K tokens

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture scales to hundreds of parallel sub-agents for autonomous task decomposition - delivering documents, websites, and spreadsheets in a single run without human oversight.

Position Medals
Anthropic: Claude Opus 4.7

Anthropic: Claude Opus 4.7

by Anthropic

1M tokens

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 complex, multi-step tasks and more reliable agentic execution across extended workflows. It is especially effective for asynchronous agent pipelines where tasks unfold over time - large codebases, multi-stage debugging, and end-to-end project orchestration. Beyond coding, Opus 4.7 brings improved knowledge work capabilities - from drafting documents and building presentations to analyzing data. It maintains coherence across very long outputs and extended sessions, making it a strong default for tasks that require persistence, judgment, and follow-through. For users upgrading from earlier Opus versions, see our [official migration guide here](https://openrouter.ai/docs/guides/evaluate-and-optimize/model-migrations/claude-4-7)

Position Medals
StepFun: Step 3.5 Flash

StepFun: Step 3.5 Flash

by stepfun

262.14K tokens

Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates only 11B of its 196B parameters per token. It is a reasoning model that is incredibly speed efficient even at long contexts.

Position Medals

4

DeepSeek: DeepSeek V4 Pro

DeepSeek: DeepSeek V4 Pro

by DeepSeek

1.05M tokens

5

Anthropic: Claude Sonnet 4.6

Anthropic: Claude Sonnet 4.6

by Anthropic

1M tokens

6

DeepSeek: DeepSeek V4 Flash

DeepSeek: DeepSeek V4 Flash

by DeepSeek

1.05M tokens

7

NVIDIA: Nemotron 3 Super (free)

NVIDIA: Nemotron 3 Super (free)

by nvidia

262.14K tokens