By the toolist.ai editors. Researched from public sources, not hands-on tested by toolist.ai. Updated November 3, 2026; prices checked November 3, 2026.

Claude Haiku 5.5: price, context window and benchmarks

Claude Haiku 5.5 is Anthropic's small, fast model for high-volume work such as classification, extraction, routing and subagents, at $0.10 per million input tokens and $0.50 per million output tokens, a tenth of Claude Haiku 4.5's price. Prompts over 100,000 tokens cost five times as much ($0.50 in, $2.50 out), and Artificial Analysis scores it 36 on its Intelligence Index at max effort.

Best for

Key facts

FactClaude Haiku 5.5Source
ProviderAnthropicClaude docs: Pricing
API model nameclaude-haiku-5-5Claude docs: Claude Haiku 5.5
ReleasedOctober 7, 2026Anthropic: Introducing Claude Haiku 5.5
Input price$0.10 per million tokensClaude docs: Pricing
Cached input price$0.01 per million tokensClaude docs: Pricing
Output price$0.50 per million tokensClaude docs: Pricing
Context window1,000,000 tokensClaude docs: Claude Haiku 5.5
Maximum output128,000 tokensClaude docs: Claude Haiku 5.5
Knowledge cutoffJune 2026Claude docs: Claude Haiku 5.5
Input and outputText and images in; text outClaude docs: Claude Haiku 5.5
ReasoningAdaptive thinking is on by default and can be turned off at high effort or below. Effort levels low to max; medium is the API defaultClaude docs: Effort
API and cloud platformsClaude API, Claude Platform on AWS, Amazon Bedrock, Google Cloud and Microsoft FoundryClaude docs: Claude Haiku 5.5
In the appsHaiku models are in the Claude apps on every plan, Free to Enterprise; the plan table names model families, not versionsClaude plans and pricing
Data retentionAvailable under zero data retention arrangements; it is not one of the models that require 30-day retentionClaude docs: API and data retention

Prompts over 100,000 tokens are billed at $0.50 in, $2.50 out and $0.05 for cache reads per million tokens for the whole request; the prompt length counts cache reads and writes. Cache writes cost $0.125 per million tokens (5-minute cache) or $0.20 (1-hour cache), or $0.625 and $1 for prompts over 100,000 tokens. The Batch API costs half.

What Claude Haiku 5.5 costs a month

Three typical workloads, priced at the standard API rates above. We calculated these; the provider does not publish them.

WorkloadTokens a monthCost a month
Support chatbot
100,000 replies, each 3,000 input and 400 output tokens, no caching
300M in, 40M out $50.00
Document Q&A
5,000 questions over the same 60,000-token document set (90% cache hits), 800 output tokens each
300M in, 4M out $7.70
Coding agent
200 tasks, each 1.5 million input tokens (90% cache hits) and 50,000 output tokens
300M in, 10M out $10.70

Reasoning models bill their thinking as output tokens, so heavy reasoning can raise the output count several times. Cache-write charges are not included.

Benchmarks

BenchmarkScoreSource
Artificial Analysis Intelligence Index
max effort
36.0 Claude Haiku 5.5 (max)
Intelligence Index at everyday effort
medium effort, the API default
25.0 Claude Haiku 5.5 (medium)
Terminal-Bench 4.0
max effort
33.0% Claude Haiku 5.5 vs Claude Sonnet 5.5
HLE-Diamond
max effort
30.0% Claude Haiku 5.5 vs Claude Sonnet 5.5
Terminal-Bench-Science 0.1
max effort
20.0% Claude Haiku 5.5 vs Claude Sonnet 5.5

Speed: about 168.2 output tokens a second (medium effort, Artificial Analysis; Claude Haiku 5.5 (medium)).

Benchmark and speed data marked as such come from Artificial Analysis.

What changed

Compared with Claude Haiku 4.5, input and output prices fall from $1 and $5 to $0.10 and $0.50 per million tokens for prompts up to 100,000 tokens ($0.50 and $2.50 above that), and cache reads from $0.10 to $0.01 up to 100,000 tokens. It is the first Haiku with an adjustable effort setting, and its updated tokenizer uses slightly more tokens per task; Anthropic says it costs around 75% less to run on average. (Anthropic: Introducing Claude Haiku 5.5)

Claude Haiku 5.5 compared

Other models

All prices side by side: AI model API price table. How we research: our method.

Sources