Baseten vs Modal vs Together AI vs vLLM
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
Baseten
Production model serving that hit $600M ARR in 2026.
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Modal
Serverless GPU compute for AI workloads
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Together AI
High-performance inference for open-weights LLMs
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VLL vLLM High-throughput LLM inference and serving engine with an OpenAI-compat... Visit | |
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| RECATOOLS Score | 7.4 / 10 | 7.8 / 10 | 8 / 10 | 8.5 / 10 |
| Capability | — | |||
| Value for money | — | |||
| Ease of use | — | |||
| ASEAN readiness | — | |||
| API quality | — | |||
| Pricing | Paid | Usage_based | Usage_based | Free |
| Free tier | — | Starter: $0 a month plus usage, with $30 of free compute every month and 3 seats | Not offered as a plan — one model (Ternary Bonsai 27B) is listed at $0.00 per 1M tokens | Everything — Apache-2.0 code on GitHub and PyPI, official container images and docs; the project is hosted by the PyTorch Foundation and has no hosted or paid product of its own |
| Paid from | — | Pay per second — GPUs from $0.000164/sec (T4), Team plan $250/month plus usage | Per 1M tokens by model — e.g. DeepSeek V4 Flash 0731 $0.14 in / $0.28 out | — |
| Has API | ✓ | ✓ | ✓ | ✓ |
| Open source | ✗ | ✗ | ✗ | ✓ |
| Free to use | ✗ | ✓ | ✗ | ✓ |
| Users | — | — | — | — |
| Founded | — | 2021 | 2022 | — |
| Maker | — | — | — | — |
| Verdict | This is infrastructure for teams that have models and engineers to run them, not a point-and-click app. Truss, Baseten's open-source framework, turns a Hugging Face or custom model into an autoscaling HTTPS endpoint and... |
Modal is a serverless compute platform built for AI and data workloads: you define functions in Python, decorate them, and Modal handles containerization, scheduling, GPUs, and autoscaling. Its strengths are developer ex... |
Together AI is a developer-focused cloud for running, fine-tuning, and training open-source models (Llama, DeepSeek, Qwen, Flux, and many more) with an OpenAI-compatible API, competitive pricing, and strong inference per... |
vLLM is for serving large language models at production throughput on hardware you control. Its PagedAttention algorithm manages the KV cache like paged virtual memory. Continuous batching keeps the GPU busy across concu... |
| Full review → | Full review → | Full review → | Full review → |
Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.