Which AI Model Should You
Connect to OpenClaw? —
The Kimi K2.5 Era Explained
"I use Kimi the most — the price-to-performance ratio is just unbeatable." One line from a Twitter thread. Here's the data and strategy behind it, fully updated for March 2026.
When I posted about OpenClaw on Twitter, a flood of questions came back. "Is Kimi K2.5 free?" "Claude API tokens drain so fast." "I'm on Gemini Pro — should I switch to Claude?" Every question was really asking the same thing: which AI model is the most rational choice for running OpenClaw in 2026?
The landscape shifted significantly on January 27, 2026, when Moonshot AI released Kimi K2.5. Since then, the way the OpenClaw community thinks about model selection has changed. This post breaks down why — with actual pricing data, benchmarks, and a practical routing strategy that most serious users are now running.
Stop thinking you need to pick one model and commit to it.
Task-based routing — using the right model for each job — is the winning strategy in 2026.
I. Why Kimi K2.5 Changed Everything
January 27, 2026 — The Day the Economics Shifted
Moonshot AI (Chinese AI startup, backed by Alibaba) released Kimi K2.5 on January 27, 2026. Three things made it immediately significant.
First: price. $0.60 per million input tokens. $2.50 per million output tokens. That is roughly one-fifth the cost of Claude Sonnet 4.6 ($3/$15) and 4–17x cheaper than GPT-5.4 depending on the tier. Alongside DeepSeek V4, it is now the cheapest frontier-class model on the market.
Second: Agent Swarm. Kimi K2.5's defining feature is the ability to coordinate up to 100 specialized sub-agents executing in parallel on a single task — a capability no other frontier model has shipped at this scale. Moonshot AI's own measurements show 4.5x faster task completion versus sequential single-agent execution. For a tool like OpenClaw, which is built around agent orchestration, this is a natural fit.
Third: context window. 256K tokens natively — larger than Claude's 200K and double GPT-5.2's 128K. In practice, this means analyzing large codebases or long documents in a single session without chunking.
II. The Four Main Options Compared
March 2026 — What Each Model Actually Is
1T parameter MoE (32B active). Agent Swarm with up to 100 parallel sub-agents. 256K context. SWE-Bench 76.8%, AIME 96.1%. Automatic 75% cache discount on repeated context. Best for high-volume automation and parallel agentic workflows.
SWE-Bench 79.6%, OSWorld 72.5%. Strongest on complex code review, legacy codebase comprehension, multi-file refactoring, and nuanced reasoning. Note: Claude Pro/Max OAuth for third-party tools was officially blocked by Anthropic in January 2026.
OpenAI explicitly allows Codex OAuth in external tools like OpenClaw. Connect GPT-5.4 Codex to OpenClaw for a flat $20/month with no surprise API bills. Strongest for terminal-based agentic coding workflows and CLI operations.
2M token context window — the largest available. Excellent for document summarization and data analysis at scale. Trails Claude and Kimi on agent tasks and coding benchmarks. Free API tier makes it a valid starting point for beginners with no budget.
III. Benchmark Reality Check
March 2026 — What the Numbers Actually Show
| Benchmark | Kimi K2.5 | Claude Opus 4.6 | Claude Sonnet 4.6 | GPT-5.2 |
|---|---|---|---|---|
| SWE-Bench Verified (coding) | 76.8% | 80.9% | 79.6% | 80.0% |
| LiveCodeBench | 85.0% | 82.2% | — | — |
| AIME 2025 (math reasoning) | 96.1% | 92.8% | — | — |
| HLE w/ Tools (agentic) | 50.2% | 43.2% | — | 41.7% |
| BrowseComp (agent search) | 60.2% | — | — | — |
| Context Window | 256K | 200K | 200K | 128K |
The pattern is clear: Claude leads on SWE-Bench coding accuracy. Kimi K2.5 leads on math reasoning and tool-augmented agentic tasks. Neither wins everything. This is precisely why task-based routing beats single-model commitment for anyone serious about both cost and quality.
IV. Real Cost Comparison
Based on ~1M Tokens/Month — Typical Personal Use
| Option | Monthly Cost | Notes | Best For |
|---|---|---|---|
| Gemini Free API tier | $0 | Rate-limited. Weak on agents and coding | Beginners / testing |
| Kimi K2.5 API | $3–5 | Based on 1M input+output tokens. Cache hits reduce further | Cost-first users |
| ChatGPT Plus + Codex OAuth | $20 flat | No per-token billing. Rate limits apply at peak | Flat-rate preference |
| Claude Sonnet 4.6 API | $18–30 | Best coding and reasoning quality per dollar | Quality-first users |
| Claude Opus 4.6 API | $100–300+ | Maximum reasoning depth. Heavy agent use = large bills | Professionals / enterprise |
Until early 2026, many OpenClaw users connected their Claude Pro/Max subscription token directly, bypassing per-token billing. Anthropic officially blocked this in January 2026 via client fingerprinting. If you want to use Claude with OpenClaw, you must use an API key with pay-per-token billing. OpenAI explicitly allows Codex OAuth in external tools — that path remains fully supported.
V. The Routing Strategy Most Power Users Run
How to Get Frontier-Class Results for $20–30/Month
🔷 Kimi K2.5
Daily automation, file management, web research, high-volume batch tasks. Unbeatable cost-to-performance ratio for routine agentic work.
🟠 Claude Sonnet 4.6
Complex code review, debugging, multi-file refactoring, tasks where output quality is non-negotiable. Use sparingly; route here only when it matters.
🟢 ChatGPT Codex
Terminal-based coding agent sessions via OpenClaw. Flat $20/month subscription covers this entirely — no per-token exposure.
This three-model setup runs at roughly $20–30/month total for most personal users — while delivering meaningful quality differentiation across task types. The math is straightforward: Kimi handles the volume at near-zero cost, Claude handles the precision when stakes are high.
Kimi's API applies an automatic 75% discount on cache hits. For agentic workflows with repeated system prompts or long shared context — which is exactly what OpenClaw generates — real effective costs can drop to 25% of the listed price. A $0.60 input rate becomes effectively $0.15 on cached tokens.
VI. Direct Answers to the Most Common Questions
"Is Kimi K2.5 free?"
No — there's a free chat tier on kimi.ai, but API access is paid. That said, at $0.60/M input tokens, it's among the cheapest frontier-class models available. For context: 1 million input tokens is roughly 750,000 words of text.
"Claude API tokens drain so fast — what do I do?"
Claude Opus charges $25 per million output tokens. A heavy agentic session generating 100K output tokens costs $2.50 — and sessions can run long. Route 80% of your work to Kimi K2.5 and reserve Claude for tasks where the quality difference genuinely matters. Most users find the quality delta isn't worth the 5–8x price premium for routine tasks.
"I'm on Gemini Pro. Should I switch to Claude?"
Gemini Pro has clear limits on agent and coding performance. If you're hitting those limits, Kimi K2.5 is the better cost-first move. Claude Sonnet is the better quality-first move. Either way, the answer is yes — there's meaningful capability headroom above Gemini Pro for agentic use.
"ChatGPT Pro via Codex OAuth through KakaoTalk — is that still working?"
Yes — and it's one of the cleanest setups right now. OpenAI explicitly allows Codex OAuth in external tools. $20/month flat, no token billing, GPT-5.4 Codex quality. The Anthropic equivalent (Claude Pro OAuth) was blocked in January 2026, so Codex is now the recommended subscription path.
"Kimi is dominating OpenClaw — which one are you running?"
See below.
📋 22B Labs Current Setup — March 2026
- Default agent work (automation, file ops, search, batch tasks) → Kimi K2.5 API (~$3–5/month)
- Precision coding, complex reasoning, critical output → Claude Sonnet 4.6 API (usage-dependent)
- Terminal agent sessions, OpenClaw coding loops → ChatGPT Codex OAuth ($20/month flat)
- Offline / privacy-sensitive tasks → Ollama local models (free, Mac Mini 24GB)