Claude Haiku 4.5: Near-Frontier Coding at 1/3 Cost and 2x+ Speed

Anthropic launched Claude Haiku 4.5, a small model delivering near-frontier coding performance at one-third the cost and over twice the speed of Sonnet 4, with strengths in computer use. It targets real-time, low-latency applications and can be orchestrated with Sonnet 4.5 for multi-agent workflows, and is available now via the Claude API, Bedrock, Vertex AI, and Anthropic apps at $1/$5 per million input/output tokens. Safety tests classify it as ASL-2 with lower misalignment rates than previous models, supported by detailed benchmarks and a system card.

Key Points

Near-frontier coding performance at one-third the cost and more than twice the speed of Claude Sonnet 4; exceeds Sonnet 4 on certain computer-use tasks.
Designed for low-latency, real-time use cases (chat, support, pair programming) and responsive multi-agent coding in Claude Code.
Works in tandem with Sonnet 4.5 for planning and sub-agent orchestration, enabling parallel task execution.
Available now via Claude API (model: claude-haiku-4-5), Anthropic apps, Amazon Bedrock, and Google Cloud Vertex AI; priced at $1/$5 per million input/output tokens.
Safety: lower misalignment rates than prior models and even Sonnet 4.5/Opus 4.1; released under ASL-2 with detailed system card and benchmark methodology.

Sentiment

The overall sentiment of the discussion is mixed to cautiously positive. While several commenters highlight significant advantages and clear use cases for Haiku 4.5, particularly in cost-efficiency and multi-agent systems, others raise valid concerns about its competitiveness against the broader market of small LLMs and its utility for certain user segments.

In Agreement

The pricing ($1/M input, $5/M output) is considered good when compared to Claude Sonnet 4.5, suggesting it will gain traction if its claimed quality holds true.
The potential for caching to reduce input costs to as low as 10 cents per million tokens is highlighted as 'massive,' possibly surpassing many cheaper open-source models with less effective caching.
A significant use case involves multi-agent orchestration, where a primary model like Sonnet 4.5 can delegate specific, context-rich tasks to multiple cheaper Haiku 4.5 sub-agents, thereby saving context window space and increasing token throughput.
Small models are generally favored by coders for 'vibe/agentic coding' as seen in LLM rankings, reinforcing Haiku 4.5's strategic positioning for such applications and specialized tool calls.

Opposed

While Haiku 4.5's pricing is good relative to Sonnet 4.5, there are other smaller/faster LLMs available in the industry at even lower costs for agentic coding, which is a significant factor at scale.
Skepticism exists regarding the practical use case for these 'tiny models,' particularly for users primarily interacting through a Claude subscription, questioning whether the benefits of speed and API pricing relief are truly applicable or needed in that context.