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Claude Haiku 5.5 vs Gemini 3.5 Flash

Compare Claude Haiku 5.5 and Gemini 3.5 Flash side-by-side. See how these vision models stack up in Image Captioning, OCR, Classification, Object Detection, and Open Prompt.

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AnthropicClaude Haiku 5.5
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GoogleGemini 3.5 Flash
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Models in this comparison

Claude Haiku 5.5 vs Gemini 3.5 Flash on Vision Evals

Gemini 3.5 Flash scores higher on all five Vision Evals tasks.

The widest gap is Identification, where Gemini 3.5 Flash leads 99.0% to 83.3%.

Overall, Claude Haiku 5.5 averages 69.6% (#22 of 63) against 81.8% (#4 of 63) for Gemini 3.5 Flash.

Claude Haiku 5.5 is both cheaper ($0.0006 vs $0.012 per sample) and faster (11.0s vs 11.5s per sample).

Claude Haiku 5.5Gemini 3.5 Flash

Claude Haiku 5.5 vs Gemini 3.5 Flash Comparison Table

Evals updated October 13, 2026Pricing updated October 19, 2026

PropertyClaude Haiku 5.5Gemini 3.5 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateOct 2026May 2026
Context Window1.0M1.0M
ParametersundisclosedUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$0.100$1.50
Output $/1M$0.500$9.00
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
69.6%
81.8%
Avg cost / sample$0.0006$0.012
Avg speed / sample11.01s11.52s
By task
Object Detection (low)
65.8%
±0.6, Mean of 3 runs, range 65.1 to 66.2
$0.0006
70.6%
±2.0, Mean of 3 runs, range 68.7 to 72.6
$0.016
Object Detection (high)
68.2%
±1.0, Mean of 3 runs, range 67.2 to 69.2
$0.0010
69.8%
±1.8, Mean of 3 runs, range 67.5 to 71.1
$0.021
Counting (low)
68.9%
±4.7, Mean of 3 runs, range 64.9 to 74.3
$0.0003
80.6%
±0.7, Mean of 3 runs, range 79.7 to 81.1
$0.0075
Counting (high)
73.0%
±1.3, Mean of 3 runs, range 71.6 to 74.3
$0.0004
82.4%
±0.0, Mean of 3 runs, range 82.4 to 82.4
$0.017
Identification (low)
83.3%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0002
99.0%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0040
Identification (high)
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0003
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0068
OCR (low)
61.2%
$0.0006
76.7%
$0.013
by category
Single value
44.8%
Transcription
93.0%
Structured JSON
82.2%
Text localization
32.0%
Single value
71.7%
Transcription
90.0%
Structured JSON
86.8%
Text localization
56.2%
OCR (high)
65.3%
$0.0010
75.5%
$0.031
by category
Single value
46.5%
Transcription
94.7%
Structured JSON
85.3%
Text localization
45.8%
Single value
69.6%
Transcription
85.4%
Structured JSON
88.1%
Text localization
53.3%
Reasoning (low)
68.9%
±2.0, Mean of 3 runs, range 66.9 to 70.9
$0.0004
82.1%
±2.0, Mean of 3 runs, range 80.1 to 84.1
$0.0082
Reasoning (high)
74.8%
±2.6, Mean of 3 runs, range 72.2 to 77.5
$0.0006
81.0%
±1.7, Mean of 3 runs, range 79.5 to 82.8
$0.018

Claude Haiku 5.5 vs Gemini 3.5 Flash: Overview

Claude Haiku 5.5

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.

Gemini 3.5 Flash

Gemini 3.5 Flash is a multimodal language model developed by Google DeepMind and released at Google I/O 2026. It is built on the Gemini 3 Flash reasoning foundation and introduces configurable thinking levels (minimal, low, medium, and high) that allow developers to tune the depth of internal reasoning before a response is generated. The model accepts text, image, video, audio, and PDF inputs and produces text output, with a 1 million token context window and up to 65,000 output tokens per request. It is natively multimodal, processing visual inputs alongside text to support tasks such as image captioning, classification, optical character recognition, object detection, and visual grounding, where the model references specific regions within an image or video frame.

Its vision capabilities extend to interpreting UI screenshots, diagrams, charts, and real-world scenes, as well as understanding video and live frame sequences for activity and scene recognition. The model supports combined tool use, including Google Search, URL context, code execution, and custom functions, within a single request, and it uses reasoning context from previous turns when thought signatures are present in the conversation history, enabling persistent multi-turn reasoning chains. Gemini 3.5 Flash carries a knowledge cutoff of January 2026 and is available via the Gemini API, Google AI Studio, Google Antigravity, and the Gemini Enterprise Agent Platform.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.5 Flash performed better. It scores higher on all five vision tasks and averages 81.8% (#4 of 63) against 69.6% (#22 of 63) for Claude Haiku 5.5. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

No. On the Vision Evals Identification benchmark at low effort, Gemini 3.5 Flash leads with 99.0% against 83.3%. This is the widest gap between the two models across the benchmark's tasks.

Claude Haiku 5.5 is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0006 per sample against $0.012. Claude Haiku 5.5 is priced at $0.10 per 1M input tokens and $0.50 per 1M output; Gemini 3.5 Flash is priced at $1.50 per 1M input tokens and $9.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Claude Haiku 5.5 is faster. Across Roboflow's Vision Evals it averaged 11.0s per inference against 11.5s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.

Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.