Runcrate vs Together AI: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Runcrate and Together AI. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
Runcrate is a GPU cloud founded in 2024 offering on-demand instances with per-second billing and no minimum commitment — the meter stops the moment you stop the instance. The platform aggregates GPU capacity across eight global regions spanning North America, Europe, and Asia, covering 14 GPU models from RTX A6000 and A100 through H100 and RTX PRO 6000. Full root access via SSH, Docker support, and custom images are included on every instance. An OpenAI-compatible inference API serves open-source models billed per token, and reserved or dedicated capacity is available for teams with monthly volume commitments.
- Per-second billing — no minimum commitment
- OpenAI-compatible inference API
- 14 GPU models including H100 and RTX PRO 6000
- 8 global regions across NA, EU, and Asia
- Full root SSH access with Docker and custom images
- Reserved and dedicated capacity available
- No enterprise SLAs or uptime guarantees
- Smaller provider — limited scale vs hyperscalers
- No managed platform or containers
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Together AI is a full-stack AI platform combining a high-throughput inference API (200+ open-source models), dedicated GPU clusters (H100 SXM, A100), and a managed fine-tuning service. Together MoE optimization cuts costs on large mixture-of-experts models. Function calling and JSON mode across all major models. Fine-tuning: LoRA and full fine-tune for Llama, Mistral, and Qwen. GPU cloud: H100 SXM and A100 clusters for large-scale training. Check api.together.ai/models for current per-token rates.
- 200+ open-source models — wide inference API catalog
- Llama 4 Scout — competitive frontier-open pricing
- Together MoE optimization reduces cost on large MoE models
- Managed fine-tuning: LoRA and full fine-tune for Llama, Mistral, Qwen
- Function calling and JSON mode across all major models
- GPU cloud + inference API from one vendor
- GPU cloud side less polished than pure-play providers like CoreWeave
- Inference API latency trails Fireworks and Cerebras on speed benchmarks
- Enterprise SLAs require custom contracts — not self-serve
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Key differences
Runcrate
GPU cloud with per-second billing and an OpenAI-compatible inference API
Together AI
Full-stack AI platform — 200+ models, GPU cloud, fine-tuning, and Together MoE optimization