Together AI Batch API
What ChatGPT, Claude, Gemini & Grok actually say · August 2026
The verdict
Together AI Batch API appears in 1 AI-ranked category — best position #5 for batch inference api for large-scale llm processing.
Positioning brief — for the Together AI Batch API team
Why the models put Together AI Batch API at #5 for batch inference api for large-scale llm processing
- broad open model catalog Gemini · Grok“Broad open model catalog”
- 50% cost discount Gemini“50% cost discount”
- massive token enqueue capacity Gemini“a massive 30-billion token enqueue capacity”
- OpenAI-compatible API simplifies switching Grok“OpenAI-compatible API simplifies switching”
What the models credit OpenAI Batch API (#1) with — and don’t credit Together AI Batch API
- frontier-model quality GPT · Claude · Grok“frontier-model quality”
- mature JSONL workflow GPT · Claude · Gemini“mature JSONL workflow”
- separate rate limit pools GPT · Gemini“separate rate limit pools that do not compete with synchronous TPM/RPM limits”
What would move the rank — the models’ fix lines, unified
- no access to proprietary frontier models Gemini“no access to proprietary frontier models like GPT-4o or Claude 3.5 Sonnet”
- higher per-token cost Grok“Higher per-token cost than deepest self-hosted or cheapest managed specialists”
- not the absolute cheapest or fastest Grok“not the absolute cheapest or fastest raw throughput”
Restructured from verbatim model output · nothing invented · every quote machine-verified
Best-in-class serverless batching for open-weight models with a 50% cost discount, 50,000 requests per batch limit, and a massive 30-billion token enqueue capacity.
Grok Broad open model catalog, native batch support, fine-tuning + dedicated options; good balance of managed ease and cost for open models (~$0.88/M); OpenAI-compatible API simplifies switching.
Where Together AI Batch API falls short, per the models
- Gemini Restricted to open-source or fine-tuned weights with no access to proprietary frontier models like GPT-4o or Claude 3.5 Sonnet.
- Grok Higher per-token cost than deepest self-hosted or cheapest managed specialists; not the absolute cheapest or fastest raw throughput.
Top alternatives per the models: OpenAI Batch API · Anthropic Message Batches API · vLLM · Google Gemini Batch API
Watch Together AI Batch API
Boards re-poll weekly and the models change their minds. One short email only when Together AI Batch API's standing moves — a rank change, a rival overtaking, or new reasoning from the models. Nothing otherwise.
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Together AI Batch API ranks #5 for best batch inference api for large-scale llm processing by AI-model consensus. Put the badge in your README, docs or site — it updates automatically as the models re-rank.
[](https://modelsagree.com/best/best-batch-inference-api-for-large-scale-llm-processing?utm_source=badge&utm_medium=embed&utm_campaign=badge-together-ai-batch-api)<a href="https://modelsagree.com/best/best-batch-inference-api-for-large-scale-llm-processing?utm_source=badge&utm_medium=embed&utm_campaign=badge-together-ai-batch-api"><img src="https://modelsagree.com/badge/together-ai-batch-api.svg" alt="Together AI Batch API — ranked #5 for Best batch inference API for large-scale LLM processing by AI models on ModelsAgree" height="28"></a>Rankings are computed from what the models answer, re-polled on demand · raw reasoning shown verbatim · methodology