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Collections/Roleplay

Best AI Models for Roleplay (RP) and Creative Writing

Model rankings updated April 2026 based on real usage data.

Discover the top AI models for roleplay (RP), character chat and creative writing, ranked by real usage data on OpenRouter. These LLMs excel at maintaining consistent personas, rich dialogue and immersive storytelling across long-context sessions.

Whether you're using Janitor AI, SillyTavern or another frontend, or building your own character chatbot or interactive fiction engine, OpenRouter gives you access to the best roleplay models through a single API.

LLM Leaderboard for Roleplay Models

1.
Deepseek V3.2
by deepseek
391B
39.3%
2.
Grok 4.1 Fast
by x-ai
64.5B
6.5%
3.
gpt-oss-120b
by openai
56.4B
5.7%
4.
Gemini 2.5 Flash Lite
by google
50.8B
5.1%
5.
GLM 4.5 Air
by z-ai
50.2B
5.1%
6.
Gemini 3 Flash Preview
by google
35B
3.5%
7.
GLM 5
by z-ai
20.9B
2.1%
8.
Qwen3 235B A22B
by qwen
19.2B
1.9%
9.
Gemini 2.5 Pro
by google
18.3B
1.8%
10.
Others
by unknown
288B
29.0%

Top Roleplay Models on OpenRouter

Based on top weekly usage data from millions of users accessing AI models for roleplay through OpenRouter.

Favicon for xiaomi

Xiaomi: MiMo-V2-Pro

1.8T tokens

MiMo-V2-Pro is Xiaomi's flagship foundation model, featuring over 1T total parameters and a 1M context length, deeply optimized for agentic scenarios. It is highly adaptable to general agent frameworks like OpenClaw. It ranks among the global top tier in the standard PinchBench and ClawBench benchmarks, with perceived performance approaching that of Opus 4.6. MiMo-V2-Pro is designed to serve as the brain of agent systems, orchestrating complex workflows, driving production engineering tasks, and delivering results reliably.

by xiaomi1.05M context$1/M input tokens$3/M output tokens
Favicon for deepseek

DeepSeek: DeepSeek V3.2

1.29T tokens

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism that reduces training and inference cost while preserving quality in long-context scenarios. A scalable reinforcement learning post-training framework further improves reasoning, with reported performance in the GPT-5 class, and the model has demonstrated gold-medal results on the 2025 IMO and IOI. V3.2 also uses a large-scale agentic task synthesis pipeline to better integrate reasoning into tool-use settings, boosting compliance and generalization in interactive environments.

Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

by deepseek164K context$0.26/M input tokens$0.38/M output tokens
Favicon for minimax

MiniMax: MiniMax M2.7

1.29T tokens

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments.

Trained for production-grade performance, M2.7 handles workflows such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. It delivers strong results on benchmarks including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while achieving a 1495 ELO on GDPval-AA, setting a new standard for multi-agent systems operating in real-world digital workflows.

by minimax205K context$0.30/M input tokens$1.20/M output tokens
Favicon for anthropic

Anthropic: Claude Sonnet 4.6

1.14T tokens

Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work. It excels at iterative development, complex codebase navigation, end-to-end project management with memory, polished document creation, and confident computer use for web QA and workflow automation.

by anthropic1M context$3/M input tokens$15/M output tokens
Favicon for anthropic

Anthropic: Claude Opus 4.6

1.12T tokens

Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective for large codebases, complex refactors, and multi-step debugging that unfolds over time. The model shows deeper contextual understanding, stronger problem decomposition, and greater reliability on hard engineering tasks than prior generations.

Beyond coding, Opus 4.6 excels at sustained knowledge work. It produces near-production-ready documents, plans, and analyses in a single pass, and maintains coherence across very long outputs and extended sessions. This makes it a strong default for tasks that require persistence, judgment, and follow-through, such as technical design, migration planning, and end-to-end project execution.

For users upgrading from earlier Opus versions, see our official migration guide here

by anthropic1M context$5/M input tokens$25/M output tokens
Favicon for google

Google: Gemini 3 Flash Preview

1.05T tokens

Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance. It delivers near Pro level reasoning and tool use performance with substantially lower latency than larger Gemini variants, making it well suited for interactive development, long running agent loops, and collaborative coding tasks. Compared to Gemini 2.5 Flash, it provides broad quality improvements across reasoning, multimodal understanding, and reliability.

The model supports a 1M token context window and multimodal inputs including text, images, audio, video, and PDFs, with text output. It includes configurable reasoning via thinking levels (minimal, low, medium, high), structured output, tool use, and automatic context caching. Gemini 3 Flash Preview is optimized for users who want strong reasoning and agentic behavior without the cost or latency of full scale frontier models.

by google1.05M context$0.50/M input tokens$3/M output tokens$1/M audio tokens
Favicon for x-ai

xAI: Grok 4.1 Fast

713B tokens

Grok 4.1 Fast is xAI's best agentic tool calling model that shines in real-world use cases like customer support and deep research. 2M context window.

Reasoning can be enabled/disabled using the reasoning enabled parameter in the API. Learn more in our docs

by x-ai2M context$0.20/M input tokens$0.50/M output tokens
Favicon for moonshotai

MoonshotAI: Kimi K2.5

667B tokens

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed visual and text tokens, it delivers strong performance in general reasoning, visual coding, and agentic tool-calling.

by moonshotai262K context$0.3827/M input tokens$1.72/M output tokens
Favicon for z-ai

Z.ai: GLM 5 Turbo

563B tokens

GLM-5 Turbo is a new model from Z.ai designed for fast inference and strong performance in agent-driven environments such as OpenClaw scenarios. It is deeply optimized for real-world agent workflows involving long execution chains, with improved complex instruction decomposition, tool use, scheduled and persistent execution, and overall stability across extended tasks.

by z-ai203K context$1.20/M input tokens$4/M output tokens
Favicon for openai

OpenAI: GPT-4o-mini

560B tokens

GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs.

As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.

GPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences common leaderboards.

Check out the launch announcement to learn more.

#multimodal

by openai128K context$0.15/M input tokens$0.60/M output tokens