Anthropic: Claude Haiku 4.5
by anthropic
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
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Benchmarking Anthropic: Claude Haiku 4.5
Coding Performance
Coding benchmarks and performance metrics for development tasks
Coding Benchmarks
| Benchmark | Score |
|---|---|
| AA Coding Index | 29.6% |
| LiveCodeBench | 51.1% |
| SciCode | 34.4% |
| TerminalBench Hard | 27.3% |
| LCR | 43.7% |
| IFBench | 42.0% |
Speed & Efficiency
| Metric | Value |
|---|---|
| Output Speed | 116 tok/s |
Performance metrics from Artificial Analysis
OpenClaw Benchmarks
PinchBench measures how Anthropic: Claude Haiku 4.5 performs on real OpenClaw agent tasks: multi-step execution, tool use, recovery, latency, and cost.
Average score
#25 of 50 official models
Average time
45 runs · per OpenClaw task
Average cost
Per benchmark run
Category breakdown
Best verified PinchBench v2 run by OpenClaw task family.
Top task results
Highest-scoring benchmark tasks from the same submission.
Autonomous task execution
Anthropic: Claude Haiku 4.5 shows emerging average success across OpenClaw-style benchmark runs, useful for recurring research, browser, and file-based automations.
Tool use and recovery
PinchBench tasks stress multi-step planning, tool calls, and judge-verified completion rather than single prompt coding snippets.
Agent workflow fit
Its deliberate average runtime and premium run cost help set expectations for long-running KiloClaw agents and production workflows.
Agentic benchmarks from the PinchBench Leaderboard
Real-World Usage
Real-world usage statistics from the Kilo Code community
Weekly Token Usage
Mode Rankings (Last Week)
Where this model ranks for each built-in mode
Code
Write, modify, and refactor code
Ask
Get answers and explanations
Debug
Diagnose and fix software issues
Orchestrator
Coordinate tasks across multiple modes
Real-world metrics from the Kilo Code Leaderboard
Pricing
Cost per 1 million tokens
Example Cost
Analyzing a 10,000 line codebase (≈40k input tokens, 10k output tokens) costs approximately $0.0900
Coding Capabilities
Features and parameters relevant to coding tasks
Coding Features
Pricing details from OpenRouter
Technical Details
Architecture and implementation specifications
- Model ID
- anthropic/claude-haiku-4.5
- Artificial Analysis Slug
- claude-4-5-haiku
- Created
- October 15, 2025
- Tokenizer
- Claude
- Input Modalities
- text, image, file
- Context Window
- 200,000 tokens
- Max Completion Tokens
- 64,000 tokens
- Input Price
- $1.00 per 1M tokens
- Output Price
- $5.00 per 1M tokens
- Cache Read Price
- $0.10 per 1M tokens
- Cache Write Price
- $1.25 per 1M tokens
- Content Moderation
- Enabled
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