Trigger when the user asks which model to use, wants to compare model costs, says "what's cheapest for this task", "should I use Opus or Sonnet", "can a smaller model handle this", or "/model-cost-compare". Estimates token cost across Opus 4.6, Sonnet 4.6, GLM-5.1, Minimax M2.7, and local Gemma 4, then recommends the cheapest model capable of the task.
Given a task description (and optionally a rough prompt / input size), estimate the cost of running it on each available model tier and recommend the cheapest one that can actually do the job.
Use these rough figures. They are not exact; confirm before quoting real numbers to the user.
| Model | Tier | Input ($/1M tok) | Output ($/1M tok) | Context | Strengths |
|---|---|---|---|---|---|
| Opus 4.6 (1M) | Frontier | ~$15 | ~$75 | 1M | Agentic, long-context, hard reasoning |
| Sonnet 4.6 | Mid | ~$3 |
| ~$15 |
| 400k |
| Everyday coding, agents, drafting |
| GLM-5.1 | Budget hosted | ~$0.60 | ~$2.20 | 256k | Cheap bulk work, decent reasoning |
| Minimax M2.7 | Budget hosted | ~$0.40 | ~$1.80 | 256k | Very cheap, OK for templated output |
| Gemma 4 (local) | On device | $0 marginal | $0 marginal | 32k | Free but slow, weak at multi-step logic |
Indicative pricing as of OpenClaw 2026.4.11. Check the provider docs before billing decisions.
cost = (input_tokens / 1_000_000) * input_price
+ (output_tokens / 1_000_000) * output_price
Multiply by volume. Show your arithmetic so the user can sanity-check.Recommended: <model> — <1-sentence reason>.Input: "Classify 10,000 customer support emails into 5 categories. Avg 400 input tokens, 20 output tokens."
Total tokens: 4M input, 200k output
| Model | Input cost | Output cost | Total | Capable? |
|-------------|-----------:|------------:|--------:|---------:|
| **Gemma 4** | $0.00 | $0.00 | $0.00 | yes |
| Minimax M2.7| $1.60 | $0.36 | $1.96 | yes |
| GLM-5.1 | $2.40 | $0.44 | $2.84 | yes |
| Sonnet 4.6 | $12.00 | $3.00 | $15.00 | yes |
| Opus 4.6 | $60.00 | $15.00 | $75.00 | overkill |
Recommended: Gemma 4 local — classification with a fixed 5-label schema is trivial for on-device models and costs nothing.
/model-cost-compare classify 10k support tickets into 5 buckets