Best AI Models for OpenClaw Agents in 2026

OpenClaw has quickly become one of the most popular AI agent frameworks available — automating tasks, managing workflows, and staying online 24/7. But once you’ve got it running, the next question is inevitable: which model should I actually use?

There’s no single right answer. The smartest approach is a tiered strategy: premium models for critical tasks, capable mid-range models as daily drivers, and cheap models to handle routine work in bulk. This guide breaks down specific model recommendations for each tier — with pricing, context windows, and what each model does best.

The Tiered Model Strategy

Picking one model for everything is like using a sledgehammer to hang a picture frame. Complex reasoning tasks need frontier-level intelligence, but simple file organization doesn’t — and running a premium model on every request will burn through your budget fast.

The most effective OpenClaw setups use three tiers:

• Tier 1 (Power): The heavy hitters for critical tasks — complex reasoning, code review, high-stakes decisions
• Tier 2 (Daily Driver): Cover most real work — code generation, content writing, multi-step agent workflows
• Tier 3 (Budget): Handle simple tasks at minimal cost — file organization, basic Q&A, routine automation

Here’s what we recommend for each tier.

Why Prompt Caching Matters for OpenClaw

OpenClaw agents maintain long system prompts, persistent memory files, and extensive conversation histories — often sending tens of thousands of tokens with every request. Without caching, you pay full input price for these repeated tokens every single time.

Prompt caching solves this. When a model supports it, the provider stores previously seen input prefixes and serves them at a steep discount on subsequent requests. For an always-on OpenClaw agent, the savings are substantial:

• System prompts and skill files — loaded on every turn, cached automatically after the first request
• Conversation history — only the newest messages incur full input cost; everything before the cache boundary is discounted
• Memory and context files — MEMORY.md, RULES.md, and other workspace files that rarely change between turns

On Novita AI, most recommended models support prompt caching with 50–90% input cost reduction on cached tokens. The cache pricing for each model is listed alongside standard pricing in the tiers below.

Tier 1: Power Models — When It Has to Be Right

Some tasks demand the strongest reasoning available. When accuracy is non-negotiable or a single mistake is costly, these are the models to reach for.

Claude Sonnet 4.6 & Claude Opus 4.6

Anthropic’s Claude models are widely regarded as the gold standard for complex reasoning and nuanced instruction following. Sonnet offers a strong balance of speed and intelligence for most advanced tasks, while Opus is the ultimate option for work where precision matters above all else.

GPT-5.4

OpenAI’s most capable model for professional work. GPT-5.4 is a flagship reasoning mode, with standard processing for context lengths under 270K tokens. It excels at complex multi-step reasoning, code generation, and tasks that require deep analytical thinking — making it a natural fit for high-stakes agent workflows where precision justifies the premium cost.

Gemini 3 Flash Preview

Google’s Gemini 3 Flash provides frontier-level capability with fast response times, making it a solid choice when you need both speed and depth for demanding tasks.

💡When to use Tier 1:

• Complex multi-file code refactoring
• High-stakes decision analysis
• Tasks where a single error is costly
• Review and validation of critical outputs

⚖️The trade-off: These models deliver exceptional quality, but they come at a premium. For an always-on OpenClaw agent processing hundreds of requests daily, running Tier 1 on every task quickly becomes expensive. That’s where the next two tiers come in — covering the vast majority of your agent’s workload at a fraction of the cost.

Tier 2: Daily Drivers — Most Tasks, Best Value

This is where your agent spends most of its thinking time. These models balance cost and capability for the work that actually matters — and they’re good enough that you’ll rarely need to escalate to Tier 1.

Kimi K2.5

Moonshot AI’s Kimi K2.5 has become a standout choice for agentic workloads. Built on a MoE (Mixture-of-Experts) architecture, it’s specifically optimized for tool use, multi-step planning, and code generation — the exact capabilities OpenClaw agents rely on most.

What sets K2.5 apart is its agentic performance. It ranks among the top models on coding benchmarks and its tool-calling accuracy rivals much more expensive models. The 262K context window is generous enough for complex workflows involving multiple documents or long conversation histories.

• Context window: 262K tokens
• Pricing: $0.60/M input · $3.00/M output · $0.10/M cached input
• Strengths: Top-tier agentic capability for its price, excellent code generation and tool use, strong multi-step reasoning.
• Best for: The go-to daily driver — code writing, multi-step agent workflows, research tasks, and anything requiring tool calls.

GLM-5

Z.ai’s flagship model represents a significant step up from the GLM-4 series. GLM-5 competes with frontier models on reasoning and coding tasks while maintaining competitive pricing. It features enhanced capabilities in mathematical reasoning, code generation, and structured output — making it particularly well-suited for agent workflows that need reliable tool use.

• Context window: 202K tokens
• Pricing: $1.00/M input · $3.20/M output · $0.20/M cached input
• Strengths: Strong reasoning, very effective at structured output and function calling, competitive benchmark performance against models at 2-3× its price.
• Best for: Complex agent tasks — code analysis, multi-step problem solving, report generation, and workflows with heavy tool use.

Qwen3.5-397B-A17B

The largest model in Alibaba’s Qwen 3.5 series, built on a MoE architecture that activates only a fraction of its total parameters per forward pass. This means you get large-model intelligence at a fraction of the expected cost. With a 262K context window, it handles extended agent sessions and multi-document workflows without context degradation.

• Context window: 262K tokens
• Pricing: $0.60/M input · $3.60/M output
• Strengths: Near-frontier reasoning and coding performance, excellent long-context handling, efficient MoE inference.
• Best for: Tasks that need maximum capability at mid-range pricing — complex code generation, analytical reasoning, and long-context research tasks.

💡What Tier 2 is good for:

• Code generation and debugging
• Content creation and editing
• Multi-step agent workflows
• Research and analysis tasks
• Tool use and function calling

Tier 3: Budget Models — Simple Tasks, Minimal Cost

These models handle high-volume, low-complexity work. They’re surprisingly capable for straightforward tasks and keep your token bill under control.

DeepSeek V3.2

DeepSeek’s latest general-purpose model, built on a MoE architecture that delivers strong performance across coding, math, and general reasoning at rock-bottom pricing. Its efficient design means you get quality output without premium costs.

• Context window: 163K tokens
• Pricing: $0.269/M input · $0.40/M output · $0.13/M cached input
• Strengths: Excellent cost-to-performance ratio, solid coding ability, fast inference speed.
• Best for: Routine agent tasks, data extraction, text formatting, and general Q&A.

GLM-4.7 Flash

Zhipu AI’s speed-optimized model, designed for high-throughput scenarios where response latency matters more than peak reasoning depth. It supports both Chinese and English well, making it a strong choice for multilingual agent setups.

• Context window: 200K tokens
• Pricing: $0.07/M input · $0.40/M output · $0.01/M cached input
• Strengths: One of the cheapest models available with a 200K context window. Very fast response times. Strong at structured output and instruction following.
• Best for: High-volume, low-complexity tasks — summarization, classification, data formatting, and notification workflows.

MiniMax M2.5

MiniMax’s M2.5 is a capable all-rounder that punches above its price point. It handles document analysis and extended conversations well, with a long context window that supports multi-turn workflows without degradation.

• Context window: 204K tokens
• Pricing: $0.30/M input · $1.20/M output · $0.03/M cached input
• Strengths: Reliable long-context performance, good at following complex instructions, strong multilingual support.
• Best for: Tasks that need slightly more capability than the cheapest models — document summarization, multi-turn conversations, and content drafting.

💡What Tier 3 is good for:

• File management and organization
• Simple question answering
• Data formatting and extraction
• Routine notifications and summaries

Run Your Model Stack on Novita AI

All the Tier 2 and Tier 3 models recommended above — Kimi K2.5, GLM-5, Qwen3.5-397B-A17B, DeepSeek V3.2, GLM-4.7 Flash, and MiniMax M2.5 — are available on Novita AI through a single API key.

Why this matters for OpenClaw users:

• OpenAI/Anthropic-compatible API format — plug directly into OpenClaw’s model configuration without custom adapters
• One API key, multiple models — switch between tiers without managing separate accounts
• Prompt caching across most models — significantly reduces input costs and speeds up responses for long-context agent sessions
• Pay-per-token — no subscriptions or minimum commitments

You can also try these models interactively on the Novita AI Playground — a web-based environment to experiment with prompts, explore parameters visually, and get instant feedback before deploying in OpenClaw.

For a step-by-step guide on how to integrate models like Kimi K2.5 into your OpenClaw agents — including Telegram bot setup and advanced configuration — check out our detailed tutorial: Use Kimi K2.5 in OpenClaw (Clawdbot): Quick Setup for Telegram Agents with Novita.

NovitaClaw: Deploy OpenClaw in One Command

Want your OpenClaw agent running 24/7 in the cloud without managing any infrastructure? NovitaClaw gets you there in one command.

NovitaClaw is a deployment tool built on Novita Agent Sandbox that provisions a fully configured OpenClaw instance from your terminal. Three steps, any platform:

sudo pip3 install novitaclaw

export NOVITA_API_KEY=sk_your_api_key

novitaclaw launch

pip install novitaclaw

$env:NOVITA_API_KEY = "sk_your_api_key"

novitaclaw launch

That’s it. In under a minute, you get:

• A 24/7 OpenClaw agent — no session limits, no manual restarts. Your agent stays online as long as you need it.
• Pre-configured with Novita models — your tiered model stack is ready out of the box. Switch models anytime through the Web UI settings.
• Multi-channel support — connect Telegram, Discord, and other messaging platforms so your agent is reachable wherever you are.
• Auto-recovery — if the agent crashes, it restarts automatically and restores the last working configuration. No data loss, no manual intervention.
• Built-in Web Terminal and File Manager — access your agent’s environment directly from the browser for debugging and file management.

The underlying sandbox runs on 2 vCPU and 4 GB RAM — sized for real production workloads, not demos. Every model on the Novita platform is supported, and you can bring your own third-party API keys for models like Claude or Gemini if you need Tier 1 access.

A Note on OpenRouter Usage Data

For those curious about what the broader community runs: OpenClaw is currently the #1 ranked app on OpenRouter by daily usage, processing 12.6 trillion tokens across 348 models as of March 2026.

The top models by token volume include Step 3.5 Flash (2.2T), MiniMax M2.5 (1.3T), Kimi K2.5 (962B), Claude Sonnet 4.6 (805B), and GLM 5 Turbo (579B). It’s worth noting that some models near the top may have elevated usage due to promotional events or free-tier availability, so raw token volume doesn’t always reflect model quality directly. The tiered strategy recommended in this article is based on a combination of usage patterns, model capabilities, and real-world community feedback.

Conclusion

The most effective OpenClaw setups don’t rely on a single model — they layer three tiers. Power models like Claude handle the moments that demand peak accuracy. Daily drivers like Kimi K2.5 and GLM-5 do the real thinking at reasonable cost. And budget models like DeepSeek V3.2 and GLM-4.7 Flash absorb the high-volume routine work.

With Novita AI, you can access all the Tier 2 and Tier 3 recommendations through a single API. And with NovitaClaw, you can deploy the entire stack in one command — no infrastructure required.

Novita AI is an AI & agent cloud platform helping developers and startups build, deploy, and scale models and agentic applications with high performance, reliability, and cost efficiency.

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