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Claude Haiku 5.5 vs Gemini 3.8 Flash

Compare Claude Haiku 5.5 and Gemini 3.8 Flash side-by-side.

Compare Claude Haiku 5.5 vs Gemini 3.8 Flash live

Run the same image across every model that supports a task and compare their outputs side-by-side.

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

Models in this comparison

Claude Haiku 5.5 vs Gemini 3.8 Flash on Vision Evals

Gemini 3.8 Flash scores higher on 5 of the six Vision Evals tasks.

The widest gap is Identification, where Gemini 3.8 Flash leads 97.9% to 83.3%.

Overall, Claude Haiku 5.5 averages 77.2% (#20 of 61) against 85.1% (#6 of 61) for Gemini 3.8 Flash.

Claude Haiku 5.5 is cheaper ($0.0005 vs $0.0033 per sample), while Gemini 3.8 Flash is faster (11.6s vs 13.2s per sample).

Claude Haiku 5.5Gemini 3.8 Flash

Claude Haiku 5.5 vs Gemini 3.8 Flash Comparison Table

Evals updated October 8, 2026Pricing updated October 8, 2026

PropertyClaude Haiku 5.5Gemini 3.8 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateOct 2026Sep 2026
Context Window1.0M1.0M
ParametersundisclosedUnknown
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$0.100$0.750
Output $/1M$0.500$3.75
Vision Tasks
CaptioningSupportedDemo
Chart Question AnsweringSupportedSupported
ClassificationSupportedDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionSupportedDemo
OCRSupportedDemo
Vision LanguageSupportedSupported
Visual Question AnsweringSupportedDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
Overall
77.2%
85.1%
Avg cost / sample$0.0005$0.0033
Avg speed / sample13.23s11.65s
By task
Object Detection (low)
65.8%
±0.6, Mean of 3 runs, range 65.1 to 66.2
$0.0006
68.1%
±0.8, Mean of 3 runs, range 67.3 to 69.0
$0.0041
Object Detection (high)
68.2%
±1.0, Mean of 3 runs, range 67.2 to 69.2
$0.0010
74.8%
±1.1, Mean of 3 runs, range 73.4 to 75.6
$0.021
Counting (low)
68.9%
±4.7, Mean of 3 runs, range 64.9 to 74.3
$0.0003
78.8%
±2.7, Mean of 3 runs, range 75.7 to 81.1
$0.0036
Counting (high)
73.0%
±1.3, Mean of 3 runs, range 71.6 to 74.3
$0.0004
79.3%
±1.4, Mean of 3 runs, range 78.4 to 81.1
$0.024
Identification (low)
83.3%
±3.1, Mean of 3 runs, range 81.3 to 87.5
$0.0002
97.9%
±1.6, Mean of 3 runs, range 96.9 to 100.0
$0.0014
Identification (high)
86.5%
±1.6, Mean of 3 runs, range 84.4 to 87.5
$0.0003
96.9%
±0.0, Mean of 3 runs, range 96.9 to 96.9
$0.0034
OCR (low)
90.1%
±1.1, Mean of 3 runs, range 88.8 to 91.0
$0.0006
87.3%
±0.8, Mean of 3 runs, range 86.5 to 88.2
$0.0024
OCR (high)
88.0%
±1.3, Mean of 3 runs, range 87.0 to 89.6
$0.0009
88.8%
±0.7, Mean of 3 runs, range 88.0 to 89.4
$0.064
Data Extraction (low)
85.9%
±1.5, Mean of 3 runs, range 84.5 to 87.6
$0.0002
97.3%
±0.5, Mean of 3 runs, range 96.9 to 97.9
$0.0018
Data Extraction (high)
87.3%
±0.5, Mean of 3 runs, range 86.6 to 87.6
$0.0002
94.8%
±1.0, Mean of 3 runs, range 93.8 to 95.9
$0.0089
Reasoning (low)
68.9%
±2.0, Mean of 3 runs, range 66.9 to 70.9
$0.0004
81.2%
±0.3, Mean of 3 runs, range 80.8 to 81.5
$0.0034
Reasoning (high)
74.8%
±2.6, Mean of 3 runs, range 72.2 to 77.5
$0.0006
84.5%
±1.0, Mean of 3 runs, range 83.4 to 85.4
$0.021

Claude Haiku 5.5 vs Gemini 3.8 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 3.8 Flash

Gemini 3.8 Flash is a natively multimodal reasoning model in Google's Gemini 3 series, positioned as the speed and cost oriented Flash tier while targeting long-horizon software engineering, autonomous agents, and enterprise workflows. It accepts text, images, video, audio, and PDF documents in a single request and returns text, with an input limit of 1,048,576 tokens and an output limit of 65,536 tokens. Thinking is configurable at low, medium, and high levels, and the model supports function calling, code execution, structured outputs, context caching, search and Maps grounding, file search, and computer use in preview. Image generation, audio generation, and the Live API are not supported.

On vision oriented evaluations the model reports 86.2% on CharXiv Reasoning for chart and figure synthesis and 87.8% on LVBench for long video understanding in agentic mode, alongside 90.8% on Terminal-Bench 2.1 and 61.6% on SWE-Bench Pro for coding. Following Gemini API conventions, it can localize objects by emitting bounding boxes as [ymin, xmin, ymax, xmax] integers normalized to a 0 to 1000 range, which supports prompt driven detection and grounding in addition to captioning, document parsing, and visual question answering. The knowledge cutoff is March 2026, though coverage in some domains reflects the January 2025 cutoff shared across the Gemini 3 family.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.8 Flash performed better. It scores higher on 5 of the six vision tasks and averages 85.1% (#6 of 61) against 77.2% (#20 of 61) 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 3.8 Flash leads with 97.9% 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 $0.0005 per sample against $0.0033. Claude Haiku 5.5 is priced at $0.10 per 1M input tokens and $0.50 per 1M output; Gemini 3.8 Flash is priced at $0.75 per 1M input tokens and $3.75 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Gemini 3.8 Flash is faster. Across Roboflow's Vision Evals it averaged 11.6s per inference against 13.2s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.