Best OpenClaw Models After Anthropic's Billing Change

Anthropic’s billing change removed the assumption that a Claude consumer subscription could serve as a predictable OpenClaw budget. The practical response is not to abandon Claude. It is to use explicit API billing, task-based routing, and spending limits.

For most users, start by testing GPT-5.6 Luna as the default route, DeepSeek V4 Flash for low-risk background work, and either GPT-5.6 Sol or Claude Sonnet 5 for difficult coding and reasoning. Gemini 3.8 Flash is a useful alternative when speed, multimodal inputs, or Google infrastructure matter.

The live chart, pricing table, and calculator above are generated from pricing.json; they replace the stale rate tables previously embedded in this article. Check the Anthropic pricing page, OpenAI pricing page, Google AI pricing page, and DeepSeek pricing page before deploying.

What the billing change means

OpenClaw is a third-party agent harness, so users should treat model traffic as API usage unless a provider explicitly documents another supported arrangement. A consumer plan may still be valuable in the provider’s own app, but it is not a safe proxy for autonomous-agent spend.

That changes the buying questions:

1. Which model passes your coding and tool-use evaluations?
2. Which steps can run on a cheaper route?
3. What happens when an agent loops or retries?
4. Can you cap usage by task, agent, and day?

The relevant metric is cost per successful task, not the cheapest input-token rate.

Best models by OpenClaw job

OpenClaw job	First model to test	Why	Main risk to measure
General agent default	GPT-5.6 Luna	Balanced OpenAI route for mixed work	Quality on the hardest coding tasks
Complex coding and reasoning	Claude Sonnet 5 or GPT-5.6 Sol	Premium escalation options	Output length, retries, and total task cost
Fast multimodal work	Gemini 3.8 Flash	Speed-oriented Google route	Preview status and production limits
Background summaries and extraction	DeepSeek V4 Flash	Low-cost route for bounded steps	Reliability, safety, and provider fit
Claude-dependent workflow	Claude Sonnet 5 via API key	Keeps Claude behavior with explicit billing	Higher spend if used for every step

Do not choose from a benchmark leaderboard alone. Run representative repository edits, shell-tool calls, retrieval tasks, and failure-recovery cases. Score correctness, tool-call success, latency, retries, and human cleanup.

When to keep Claude

Keep Claude when it materially improves the work you care about. A direct Anthropic API key gives you clearer attribution and budgeting than relying on consumer-login behavior. It also makes routing and usage monitoring easier.

Claude Sonnet 5 belongs in the stack when difficult code changes, long-context analysis, or careful instruction following reduce rework. It does not need to handle cheap classification, summarization, or routing steps merely because it is your strongest model.

See the ChatGPT vs Claude pricing comparison for a broader product and API comparison.

When to switch or route

GPT-5.6 Luna is the sensible general starting point for teams already using OpenAI tooling. Escalate to GPT-5.6 Sol when the default model fails an evaluation or when the task value supports a premium route.

DeepSeek V4 Flash can lower average spend on bounded background work. Give it structured inputs, narrow permissions, deterministic output schemas, and an escalation path. Avoid assigning high-impact changes solely because the token rate is attractive.

Gemini 3.8 Flash deserves a test when screenshots, mixed media, or Google Cloud integration are central. Its preview status in the current dataset means availability and production terms should be verified before committing.

Recommended routing setup

A practical OpenClaw stack has three tiers:

• Budget tier: summaries, extraction, classification, and low-risk preprocessing.
• Default tier: routine code edits, research, and tool use that passed your evaluations.
• Escalation tier: hard debugging, architecture decisions, failed attempts, and high-value output.

Set maximum turns, token budgets, and tool permissions per task. Log the selected model, retries, tokens, tool failures, and final acceptance. A cheaper model that loops can cost more than a premium model that succeeds once.

Use the token cost calculator with your measured input/output mix, then compare the result with the maintained AI API pricing comparison.

Bottom line

Anthropic’s policy change made explicit API billing and multi-model routing the safer OpenClaw default. Keep Claude where it wins your evaluations, but do not pay frontier rates for every agent step.

Start with a balanced default, add a tightly controlled budget route, and reserve premium models for failures or genuinely difficult work. Re-run the evaluation whenever models, prices, or provider terms change.