Best Model for OpenClaw — April 2026 Community Rankings
PricePerToken's OpenClaw model leaderboard updated today. As of April 22, 2026, community votes rank the top models for OpenClaw agentic workflows as:
- Kimi K2.5 (Moonshot AI) — $0.44/M input, $2.00/M output — 678 net votes
- GLM 4.7 (Z-AI) — $0.39/M input — strong #2
- Claude Opus 4.6 (Anthropic) — #3, still competitive but losing ground
This is a notable shift from six months ago when Claude dominated community recommendations for OpenClaw setups.
Why the Rankings Changed
Two things happened in quick succession that reshuffled the leaderboard:
1. Anthropic Tightened Usage Rules
Anthropic's changes to how Claude subscriptions handle third-party harnesses (including OpenClaw's CLI integration) pushed users toward direct API access — which gets expensive fast for always-on agent setups. The community discussion is blunt: "Claude is dead. OpenAI made business plan quotas unusable. So I went shopping."
2. Chinese Models Got Competitive
Kimi K2.5, GLM 4.7, and Minimax 2.7 have all improved significantly. For agentic tasks — tool use, multi-step planning, long-context reliability — the community is finding them "not as smart as Opus, but enough." At $0.39–$0.44/M input vs. Claude's pricing, the value math is compelling.
The Minimax 2.7 Story
The most interesting community signal this cycle isn't the top of the rankings — it's Minimax 2.7 as a practical fallback. One widely-upvoted user comment:
"When MiMo and GPT failed to handle my cron task and Minimax M2.7 solved it in 5 minutes. And the quota on Minimax is impossible to exhaust... How are they this generous? Tested browser automations. It's not as smart as Opus, but for automation tasks, light coding work, and being a personal agent — it's enough."
The "impossible to exhaust quota" claim is unusual and worth verifying for your own use case — but if it holds, it makes Minimax 2.7 a compelling default for high-volume OpenClaw heartbeat workloads where you're burning tokens on routine tasks.
What to Avoid Right Now
From community feedback this week:
- GLM 5.1 / 5 Turbo — multiple reports of poor agentic performance, "drunk model" behavior, credit billing problems with no refunds after 3+ weeks
- MiMo V2 Pro — credit system burns quota extremely fast in OpenClaw (session history, bootstrap content, tool outputs all deduct); one user exhausted a month's quota in a day filling two session contexts
- Grok — community feedback consistently negative for OpenClaw agentic use cases
The Practical Model Stack (April 2026)
For a balanced OpenClaw setup right now, the community consensus points toward:
| Task Type | Recommended Model | Why |
|---|---|---|
| Heavy reasoning, complex tasks | Claude Opus 4.6 or Kimi K2.5 | Still the ceiling for hard problems |
| Routine automation, cron tasks | Minimax 2.7 | Generous quota, good enough for repetitive work |
| Cost-sensitive always-on | GLM 4.7 or Kimi K2.5 | Cheapest at quality threshold |
| Local / zero API cost | Qwen 2.5 7B (Ollama) | Free, CPU-only, good for lightweight tasks |
Setting Up a Fallback Chain
OpenClaw's model fallback system lets you define a primary + fallback chain so routine tasks hit cheaper models automatically:
# openclaw.json
{
"agents": {
"defaults": {
"model": {
"primary": "moonshotai/kimi-k2.5",
"fallbacks": [
"minimax/minimax-2.7",
"ollama/qwen2.5:7b"
]
}
}
}
}This lets you run Kimi K2.5 for primary interactions, fall back to Minimax for high-volume cron work, and use local Ollama as a free tier for the most routine tasks — all without manual switching.
Need help configuring your model stack for your actual workload? That's part of every ClawReady setup.