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Model Detail

arcee-ai logo

Arcee AI: Spotlight

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Provider: Arcee-aiCategory: multimodal
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Overview

Arcee AI: Spotlight is a multimodal model released by Arcee-ai. And supports text+image->text inputs.

Pricing & Throughput

Arcee AI: Spotlight is priced at $0.18/M input tokens and $0.18/M output tokens. Operationally the model offers a 131K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. At this input rate the model sits in the commodity tier and is suitable for high-volume workloads where per-call cost dominates the decision.

Technical

The published knowledge cutoff is 2025-03-31, so newer events will not be reflected in zero-shot answers without retrieval.

Use Cases

Arcee AI: Spotlight is best fit for mixed text-and-image reasoning tasks such as document understanding, and high-volume batch jobs where per-call cost dominates the budget. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.

Download History
Pricing
Input ($/M tokens)
$0.18
Output ($/M tokens)
$0.18
Context Window
131K
Model Info
Modalitytext+image->text
Knowledge Cutoff2025-03-31
Recent newsView all news →
Related News
arxivneutral43d ago

Spotlights and Blindspots: Evaluating Machine-Generated Text Detection

arXiv:2604.16607v2 Announce Type: replace-cross Abstract: With the rise of generative language models, machine-generated text detection has become a critical challenge. A wide variety of models is available, but inconsistent datasets, evaluation metrics, and assessment strategies obscure comparisons

arxiv45d ago

Spotlights and Blindspots: Evaluation Machine-Generated Text Detection

arXiv:2604.16607v1 Announce Type: new Abstract: With the rise of generative language models, machine-generated text detection has become a critical challenge. A wide variety of models is available, but inconsistent datasets, evaluation metrics, and assessment strategies obscure comparisons of model

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