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Together AI boosts Batch Inference API with 3000x rate limit increase

By PulseAugur Editorial · [1 sources] ·

Together AI has significantly upgraded its Batch Inference API, introducing a more user-friendly interface and expanding model compatibility to include all serverless and private deployment models. The update dramatically increases rate limits by 3000x, from 10 million to 30 billion enqueued tokens per model per user, enabling much larger-scale data processing. These enhancements aim to make high-throughput workloads more cost-effective and accessible, with costs typically at 50% of their real-time API for most serverless models. AI

IMPACT Enables more cost-effective and scalable processing for large AI workloads like synthetic data generation and model evaluation.

RANK_REASON Product update to an existing API service.

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Together AI boosts Batch Inference API with 3000x rate limit increase

How we ranked this

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
Product update to an existing API service.
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, infra
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
110 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Together AI blog TIER_1 English(EN) ·

    Improved Batch Inference API: Enhanced UI, Expanded Model Support, and 3000× Rate Limit Increase

    Our new Batch Inference API makes large-scale AI workloads simpler, faster, and cheaper. With a streamlined UI, universal model support, and 3000× higher rate limits—now up to 30B tokens—you can process massive datasets at half the cost of real-time APIs.

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