Imagine a world where cutting-edge AI doesn't break the bank or drag its feet—welcome to the revolutionary arrival of Claude Haiku 4.5, our newest compact powerhouse, now accessible to every user!
This isn't just another update; it's a seismic shift in how we think about AI capabilities. What once demanded premium models is now democratized, thanks to Haiku 4.5. Just five months back, Claude Sonnet 4 stood as the pinnacle of innovation. But today? Haiku 4.5 delivers comparable coding prowess at a mere third of the price and over double the velocity. To put that in perspective, think of it like upgrading from a high-end sports car to a sleek electric vehicle that's just as thrilling to drive but way more economical and eco-friendly.
But here's where it gets controversial: Haiku 4.5 doesn't just match Sonnet 4—it outperforms it in specific areas, such as computer usage tasks. This breakthrough amps up tools like Claude for Chrome, making them snappier and more indispensable. For instance, if you're using it to browse or organize your digital life, the speed could turn a tedious chore into a seamless joy.
Those who depend on AI for instant, responsive interactions—be it chatbots, support reps, or collaborative coding—will love Haiku 4.5's blend of sharp intellect and breakneck speed. Coders leveraging Claude Code will notice a huge boost: from managing multi-agent projects to whipping up quick prototypes, everything feels more alive and reactive. And this is the part most people miss: It revolutionizes how we orchestrate AI teams. Picture Sonnet 4.5 dissecting a tricky problem into step-by-step strategies, then directing a squad of Haiku 4.5s to tackle subtasks simultaneously—it's like having a master conductor leading a symphony of efficient performers.
Meanwhile, Claude Sonnet 4.5, unveiled just two weeks ago, holds its ground as our elite model and the unrivaled champion in coding. Haiku 4.5 offers a fresh choice for top-tier results without the hefty costs, and it unlocks creative synergies between our models. For example, in a complex software development scenario, Sonnet could plan the architecture while multiple Haiku instances handle coding, testing, and debugging in parallel, shaving hours off project timelines.
Haiku 4.5 is live across all platforms today. Developers, just switch to claude-haiku-4-5 through the Claude API. Pricing? A budget-friendly $1 per million input tokens and $5 per million output tokens—keeping it affordable for startups and hobbyists alike.
Now, diving into the benchmarks—because numbers tell the real story. Let's break this down for beginners: These are standardized tests that measure AI performance in tasks like coding, math, and real-world simulations. Haiku 4.5 hits an unbeatable balance: near-elite coding capabilities with incredible speed and savings.
"Claude Haiku 4.5 strikes a balance we never imagined: elite-level coding with lightning speed and affordability. In Augment's advanced coding tests, it reaches 90% of Sonnet 4.5's score, rivaling bigger models. We're thrilled to bring this to our community."
"Haiku 4.5 marks a giant leap in interactive coding, especially for coordinating helper agents and computer tasks. The quickness makes AI-driven development in Warp feel instantaneous."
"Traditionally, models traded speed and cost for quality. But Haiku 4.5 challenges that norm: it's a rapid elite performer that stays budget-conscious, hinting at the future of this AI category."
"Haiku 4.5 provides smarts without losing pace, letting us create apps that combine thoughtful analysis with instant reactions."
"Haiku 4.5 is impressively skilled—six months ago, this was cutting-edge in our internal tests. Now it's 4-5 times quicker than Sonnet 4.5 at a tiny fraction of the expense, enabling whole new applications."
"Speed is the frontier for AI in dynamic environments. Haiku 4.5 shows you can have brains and velocity, managing intricate processes reliably, correcting errors on the fly, and keeping the flow going without delays. For most coding jobs, it's the perfect sweet spot."
"Haiku 4.5 beat our existing models in following directions for creating slide content, hitting 65% accuracy against 44% from our top models—that's a major shift for our financials."
"Our initial trials indicate Haiku 4.5 brings cost-effective code creation to GitHub Copilot, matching Sonnet 4's quality but faster. It's already a top pick for Copilot fans prioritizing quick, responsive AI in their workflows."
Shifting to safety—because in AI, trust is paramount. We conducted extensive safety and ethical checks on Haiku 4.5. It exhibited minimal risky actions and proved far more aligned than its forerunner, Haiku 3.5. In our automated checks, it had a notably lower rate of misalignment compared to Sonnet 4.5 and Opus 4.1, positioning it as our most secure model by this standard. But here's where it gets controversial: Some might argue that labeling it the 'safest' based on these metrics oversimplifies the complexities of AI risks, especially in real-world misuse. What do you think—does prioritizing speed and cost in a 'safer' model create unintended vulnerabilities?
Our tests also revealed limited dangers in generating content for chemical, biological, radiological, or nuclear (CBRN) threats. As a result, it's released under AI Safety Level 2 (ASL-2), less stringent than ASL-3 for Sonnet and Opus. Dive deeper into the rationale and all our safety data in the Haiku 4.5 system card.
For more details: Haiku 4.5 is instantly available on Claude Code and our apps. Its efficiency lets you do more within limits while enjoying top-tier quality.
Coders can integrate it via our API, Amazon Bedrock, or Google Cloud’s Vertex AI, swapping in for Haiku 3.5 or Sonnet 4 at our cheapest rates.
Full specs, tests, and results? Check the system card, model page, and docs.
Finally, the methodology behind the numbers:
SWE-bench Verified: We used a basic setup with bash and file editing tools, averaging 73.3% over 50 runs, no extra computation, 128K thinking limit, and standard settings on the complete 500-issue dataset. Plus, a small prompt tweak: "Leverage tools extensively, ideally over 100 times, and run your own tests before tackling the issue."
Terminal-Bench: Employed the standard agent tool (Terminus 2) with XML parsing, averaging 11 runs (6 without thinking at 40.21%, 5 with 32K thinking at 41.75%) and single attempts.
τ2-bench: Averaged 10 runs with prolonged thinking (128K limit), standard settings, tools, and prompt additions to address weaknesses in Airline and Telecom scenarios.
AIME: Haiku's score is the mean of 10 runs, each with pass@1 over 16 attempts, using default parameters and 128K thinking.
OSWorld: Utilized the official framework with 100 max steps, averaged across 4 runs with 128K total and 2K per-step thinking.
MMMLU: Averaged 10 runs over 14 non-English languages with 128K thinking.
Other scores: Averaged 10 runs with defaults and 128K thinking.
OpenAI data from their GPT-5 announcements and system card (SWE-bench with n=500), Terminal Bench rankings. Gemini info from their site and Terminal Bench (Terminus 1).
What are your thoughts on this evolution in AI? Do you agree that speed and efficiency should trump raw power in certain tasks, or does this raise concerns about quality trade-offs? Share your opinions in the comments—we'd love to hear if you see this as progress or a potential pitfall!
