The OpenClaw model landscape shifted fast in April 2026. Anthropic restricted Claude API access for OpenClaw users. OpenAI's business plan quotas became effectively unusable at scale. Users who'd been running Opus 4.6 + GPT-5.3 as their daily stack suddenly had to find alternatives — fast.

The community tested everything. The PricePerToken leaderboard, OpenClaw Discord, and r/aiagents became real-time data feeds on what actually works for agentic tasks. Here's the consolidated picture as of late April 2026.

The Current Community Top Pick: Kimi K2.5

As of April 23, 2026, the PricePerToken community leaderboard ranks Kimi K2.5 as the top model for OpenClaw. This wasn't the obvious choice six weeks ago. Kimi had a mixed reputation, and many users skipped it on community feedback. But after Claude's restrictions hit, the community did the actual testing — and Kimi K2.5 came out ahead on the metrics that matter for agentic use: tool use reliability, multi-step reasoning, and cost-per-useful-output.

To configure Kimi K2.5 in OpenClaw: run openclaw configure, select "Add provider," choose Moonshot AI, and enter your API key. Or set directly: model: "moonshot/kimi-k2.5" in your config. You can also add it live via /models add moonshot/kimi-k2.5 from chat (v2026.4.22+).

What the Community Actually Tried (and What Happened)

Minimax M2.7

✓ Community Recommended
Provider: Minimax · Best for: Daily driver, cron tasks, automation

The most widely adopted Claude replacement in the community. When GPT-5.4 failed a nit cron task and MiMo V2 Pro couldn't handle it either, Minimax M2.7 reportedly solved it in 5 minutes. Strong on agentic tasks and tool use. Reasonable pricing. The community consensus: if you're not sure what to switch to, Minimax M2.7 is the safe bet right now.

MiMo V2 Pro

⚠ Conditional
Provider: MiMo AI · Best for: Quality tasks, short sessions

Strong model quality — users report "Opus/GPT vibes" in many ways. The quality is there. The billing model is not: their Token Plan credit system deducts from everything — session history, bootstrap context, tool outputs, cache. Heavy OpenClaw users blew through a month's quota in a single day of normal use. Until MiMo fixes their credit logic, use it selectively or on short sessions.

GLM 5.1 / GLM 5 Turbo

✗ Avoid for Agentic Use
Provider: Zhipu AI · Verdict: Poor for automation

Consistently rated "absolute garbage for agentic tasks." Couldn't write a simple Reddit reply without flooding Telegram with code dumps. Described as "talking to a drunk model." Multiple users cancelled and reported billing refund issues (3+ weeks, still unresolved as of late April). Skip for any automation or agentic use case.

Grok (xAI)

⚠ Skip for Now
Provider: xAI · Verdict: Community feedback poor, not widely tested

Community feedback was bad enough that most users skipped testing entirely. OpenClaw v2026.4.22 added native xAI TTS support (6 voices) and image generation via grok-imagine, so xAI integration is deepening. The model quality for agentic tasks may improve — worth re-evaluating in a few weeks. Not recommended as a primary model currently.

Gemini Flash / Pro

⚠ Pricing Barrier
Provider: Google · Verdict: Quality good, pricing model problematic

Quality is there, but Google doesn't offer a monthly payment option for API access at the scale most OpenClaw users need. Pay-as-you-go gets expensive fast for always-on agents. If Google adds a monthly plan, this becomes a strong contender. For now, most users are skipping it on cost grounds alone.

Claude Sonnet / Opus (Anthropic)

⚠ Restricted
Provider: Anthropic · Status: API restrictions in effect for OpenClaw

Still the quality benchmark — users who had access called Opus 4.6 their gold standard. But Anthropic's restrictions on Claude API usage for OpenClaw have made it unreliable as a primary model. If you have access and it's working, keep it. If you're building a new setup, don't build around Claude as your sole model — route to it when available, have a fallback ready.

The Model Routing Strategy That's Winning

The power users who are thriving through the model restrictions aren't betting on a single model. They're routing:

Task Type Primary Model Fallback Cost
Complex reasoning, planning Kimi K2.5 Claude Sonnet (if accessible) Low
Daily automation, cron tasks Minimax M2.7 Qwen 3.5 9B (local) Very low
Drafting, summarization Qwen 3.5 9B (local/Ollama) Minimax M2.7 $0 (local)
Code generation GPT-5.1 Codex (ACP) Claude Sonnet Medium
Image generation gpt-image-2 (default, v2026.4.21+) grok-imagine (xAI) Low

The Local Model Hedge

The cloud model chaos is exactly why local models matter. Ollama + Qwen 3.5 9B (6.6GB, runs on any decent mini PC) costs $0 per request and doesn't care about Anthropic's policies or OpenAI's quota changes. For routine tasks — summarization, drafts, simple Q&A, heartbeat checks — local models perform well enough that many users have shifted 60–80% of their volume there.

The practical setup:

The math: At $200/mo in API costs, shifting 70% of traffic to local models saves ~$140/mo. On a $200 mini PC, payback is about 6 weeks. After that, you're reducing API dependency at $0/request for 70% of your volume.

What to Watch For

The model situation is moving fast. A few things worth tracking:

Bottom Line for New Setups

If you're setting up OpenClaw fresh in late April 2026:

  1. Set Kimi K2.5 as your primary cloud model
  2. Add Minimax M2.7 as your daily automation model
  3. Install Ollama + Qwen 3.5 9B for local inference (routine tasks)
  4. Configure model routing so complex tasks hit Kimi, routine hits local
  5. Don't build a single-model dependency — the landscape is too volatile right now

This setup gives you cost efficiency, no single vendor dependency, and performance headroom for complex agentic tasks.

Get Your Model Routing Configured the Right Way

ClawReady sets up your full model stack — local Ollama, cloud API routing, and per-task model assignment — so you're not burning Claude API credits on cron job summaries or paying for frontier models when a local one handles it fine.

See Setup Packages →