Current as of March 2026. Haiku 4.5 is the model I use for the boring parts of an agent pipeline — log parsing, triage, routing, anything that runs at volume and doesn’t need deep reasoning. Fast, cheap enough for high-frequency calls, and better at following tool schemas than most models at this price.
Specs
| Provider | Anthropic |
| Input cost | $1.00 / M tokens |
| Output cost | $5.00 / M tokens |
| Context window | 200K tokens |
| Max output | 64K tokens |
| Parameters | N/A |
| Features | function_calling, vision, reasoning |
What it’s good at
Context Window
200K tokens means you can drop entire repositories or large log files into a single prompt. No RAG pipeline needed for most tasks, which simplifies your architecture.
Tool Calling Reliability
For a budget model, it follows function schemas better than expected. Arguments match the schema, JSON blocks close cleanly — that’s the baseline you need for any agent tool to work.
Vision Integration
It processes UI screenshots and diagrams without needing Sonnet-tier pricing. Useful for automated testing pipelines or document analysis where you’re running hundreds of images through.
Where it falls short
Price vs. Alternatives
$1/M input is reasonable, but GPT-4o-mini is $0.15/M for similar use cases. If you’re purely cost-driven and Anthropic’s instruction following isn’t a requirement, that gap is hard to ignore.
Deep Logic Gaps
Multi-step architectural reasoning is where it falls apart. Give it a complex feature to implement from scratch and it’ll miss edge cases, produce incorrect assumptions, or just lose the thread partway through.
Best use cases with OpenClaw
- High-Volume Log Parsing — 200K context and low latency for scanning large log files to find specific patterns. This is its sweet spot.
- Initial PR Triage — Boilerplate code review, syntax checks, labeling issues. Fast enough to run on every commit without breaking your budget.
Not ideal for
- Greenfield Feature Development — It misses subtle edge cases in complex business logic. You’ll spend more time fixing bugs than you saved in API costs.
- Extreme Budget Constraints — If cost is the top priority above all else, GPT-4o-mini and Gemini 1.5 Flash undercut Haiku on price with comparable output quality for simple tasks.
Run it through Haimaker
Skip juggling API keys. One Haimaker key gives you access to every model on the platform. Tell OpenClaw:
Add Haimaker as a custom provider to my OpenClaw config. Use these details:
- Provider name: haimaker
- Base URL: https://api.haimaker.ai/v1
- API key: [PASTE YOUR HAIMAKER API KEY HERE]
- API type: openai-completions
Add the auto-router model:
- haimaker/auto (reasoning: false, context: 128000, max tokens: 32000)
Create an alias "auto" for easy switching. Apply the config when done.
Or skip model selection entirely — Haimaker’s auto-router picks the best model for each task so you don’t have to.
OpenClaw setup
Set your API key and you’re done.
export ANTHROPIC_API_KEY="your-key-here"
That’s it. OpenClaw picks up Anthropic models automatically.
How it compares
- vs GPT-4o-mini — GPT-4o-mini is about 6x cheaper on input and has a 128K context window. For simple tasks, it often works fine. Haiku 4.5 wins on instruction following — worth it if your agent is prone to breaking on schema violations.
- vs Gemini 1.5 Flash — Gemini offers a 1M context window and lower pricing. I find Haiku more concise and consistent on system prompt adherence, but Gemini is competitive if the giant context window matters to your use case.
Bottom line
The right pick for high-volume, lower-complexity tasks where you want Anthropic’s tool-calling reliability without Sonnet pricing. If your primary goal is raw cost minimization and the task is simple, look at GPT-4o-mini first.
TRY CLAUDE HAIKU 4.5 ON HAIMAKER
For setup instructions, see our API key guide. For all available models, see the complete models guide.