Claude Haiku 5.5 is a proprietary multimodal language model from Anthropic and the smallest member of the Claude 5.5 family, released on October 7, 2026 after Claude Opus 5.5 and Claude Sonnet 5.5. It accepts text and image input and returns text, with a 1M token context window and up to 128K output tokens per request. It is the first Haiku-class model with an adjustable effort parameter: adaptive thinking is on by default and the model decides how much to reason, steered by effort levels from low to max with medium as the default. Its training data cutoff is June 2026. Pricing starts at $0.10 per million input tokens and $0.50 per million output tokens for prompts up to 100K tokens, which Anthropic reports is about 90% lower than Claude Haiku 4.5 for requests in that range.
Anthropic positions Haiku 5.5 for high-volume, latency-sensitive work such as classification, extraction, routing, summarization, and subagent tasks, and describes it as its fastest model to date at standard speed. On visual and agentic evaluations reported at launch, it scores 46.4% on Chartography, a chart reading benchmark, compared with 6.4% for Haiku 4.5 and 61.6% for Sonnet 5.5, and 72.4% on the offline subset of OSWorld 2.1, a screenshot driven computer use benchmark, compared with 15.7% for Haiku 4.5. It uses the same tokenizer as Claude Opus 4.7 and later models, so the same text counts as roughly 30% more tokens than on Haiku 4.5.
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Vision Evals is Roboflow's ground-truth benchmark: every model runs the same real-world samples across six vision tasks, and answers are scored against ground truth.
Evals updated October 8, 2026Pricing updated October 8, 2026
Claude Haiku 5.5 averages 77.2% across the six Vision Evals tasks, ranking #20 of 61 models overall.
Its weakest relative showing is Identification, ranking #36 of 61 at 83.3%.
At $0.0005 per sample it is the 10th cheapest of the 61 benchmarked models, and its average inference time of 13.2s per sample makes it the 40th fastest.
Field medians: Object Detection 54.3%, Counting 62.6%, Identification 84.4%, OCR 89.4%, Data Extraction 84.5%, Reasoning 57.6%.
| Task | Score | Field (0 to 100) | Rank | Cost / sample | Speed |
|---|---|---|---|---|---|
| Object Detection (low) | 65.8% ±0.6, Mean of 3 runs, range 65.1 to 66.2 | #12 of 61 | $0.0006 | 8.34s | |
| Object Detection (high) | 68.2% ±1.0, Mean of 3 runs, range 67.2 to 69.2 | #12 of 29 | $0.0010 | 10.33s | |
| Counting (low) | 68.9% ±4.7, Mean of 3 runs, range 64.9 to 74.3 | #19 of 61 | $0.0003 | 18.88s | |
| Counting (high) | 73.0% ±1.3, Mean of 3 runs, range 71.6 to 74.3 | #15 of 29 | $0.0004 | 16.49s | |
| Identification (low) | 83.3% ±3.1, Mean of 3 runs, range 81.3 to 87.5 | #36 of 61 | $0.0002 | 14.70s | |
| Identification (high) | 86.5% ±1.6, Mean of 3 runs, range 84.4 to 87.5 | #18 of 29 | $0.0003 | 11.62s | |
| OCR (low) | 90.1% ±1.1, Mean of 3 runs, range 88.8 to 91.0 | #29 of 61 | $0.0006 | 9.73s | |
| OCR (high) | 88.0% ±1.3, Mean of 3 runs, range 87.0 to 89.6 | #24 of 29 | $0.0009 | 15.14s | |
| Data Extraction (low) | 85.9% ±1.5, Mean of 3 runs, range 84.5 to 87.6 | #23 of 61 | $0.0002 | 14.71s | |
| Data Extraction (high) | 87.3% ±0.5, Mean of 3 runs, range 86.6 to 87.6 | #15 of 29 | $0.0002 | 15.43s | |
| Reasoning (low) | 68.9% ±2.0, Mean of 3 runs, range 66.9 to 70.9 | #18 of 61 | $0.0004 | 18.15s | |
| Reasoning (high) | 74.8% ±2.6, Mean of 3 runs, range 72.2 to 77.5 | #13 of 48 | $0.0006 | 10.18s |
Overall benchmark score against estimated cost per sample, on a log scale. Upper-left is the sweet spot: high quality at low cost.
60 models on the current benchmark · scores and efficiency pooled across all six tasks at low effort · Claude Haiku 5.5 highlighted
Claude Haiku 5.5 scores are the mean of 3 runs per task at both low and high effort · Methodology
View all Vision Evals →Claude Haiku 5.5 costs $0.100 per 1M input tokens and $0.500 per 1M output tokens.
Pricing updated Oct 8, 2026
Other versions in the same family as Claude Haiku 5.5.
Claude Haiku 5.5 is proprietary: the weights are not distributed, and the Claude Haiku 5.5 license is the vendor's commercial terms of service that you accept when you call the API.
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Yes. Claude Haiku 5.5 accepts image input and handles OCR, data extraction, object counting, identification, visual reasoning, and object detection. On Roboflow's Vision Evals its strongest task is Object Detection at 65.8% (#12 of 61 at low effort).
Yes. its transcriptions match the ground truth 90.1% on average (#29 of 61 at low effort) on Vision Evals OCR. Pulling specific fields out of documents (data extraction) scores 85.9%.
It's serviceable. On Vision Evals, Claude Haiku 5.5 scores 65.8% mAP@50 on object detection (#12 of 61 at low effort) and 68.9% judge-graded accuracy on object counting.
On our benchmark's task mix, Claude Haiku 5.5 averages $0.0005 per sample at $0.10 per 1M input and $0.50 per 1M output tokens (#10 of 61 on cost), with an average speed of 13.2s per sample across the benchmark. Actual cost depends on your images and prompts.
On the overall Vision Evals ranking, Claude Haiku 5.5 sits #20 of 61 at 77.2%, just behind GPT-6 Luna (77.2%) and just ahead of Gemini 3 Flash (74.9%). See the full side-by-side: Claude Haiku 5.5 vs GPT-6 Luna.