{"slug":"baseten","name":"Baseten","domain":"baseten.co","verdict":"As of 2026-07-18, ChatGPT, Claude, Gemini, Grok collectively rank Baseten #2 of 8 for gpu serverless platforms for ai inference (one of 6 leaderboards it appears on). Source: https://modelsagree.com/product/baseten (modelsagree.com, CC BY 4.0).","best_rank":2,"categories":6,"brief":{"category":"best-gpu-serverless-platforms-for-ai-inference","title":"Best GPU serverless platforms for AI inference","rank":2,"of":8,"top":"Modal","day":"2026-07-18","why":[{"t":"Production-scale model serving","m":["ChatGPT","Gemini","Claude","Grok"],"q":"Best-in-class for production-scale LLMs and complex generative models"},{"t":"Truss custom model packaging","m":["ChatGPT","Gemini","Claude","Grok"],"q":"Truss for custom model packaging"},{"t":"Optimized inference runtimes","m":["ChatGPT","Gemini","Claude"],"q":"TensorRT-LLM/vLLM-optimized runtimes out of the box"},{"t":"Strong autoscaling and observability","m":["ChatGPT","Gemini","Claude","Grok"],"q":"strong autoscaling and observability"}],"gap":[{"t":"Python-first developer experience","m":["Claude","Gemini","Grok"],"q":"Best Python-first developer experience"},{"t":"Reliable per-second scaling to zero","m":["Claude","Grok"],"q":"reliable per-second scaling to zero"},{"t":"Flexibility and iteration speed","m":["ChatGPT","Gemini"],"q":"flexibility and iteration speed alongside production performance"}],"fix":[{"t":"Higher opaque production pricing","m":["ChatGPT","Claude","Grok"],"q":"Premium, relatively opaque pricing"},{"t":"Heavy for experiments and solo developers","m":["ChatGPT","Claude"],"q":"the platform is heavier than a solo developer or experimenter needs"},{"t":"Narrow focus on model serving","m":["Gemini"],"q":"keeping its focus narrow to model serving"}]},"entries":[{"slug":"best-gpu-serverless-platforms-for-ai-inference","title":"Best GPU serverless platforms for AI inference","rank":2,"of":8,"score":14,"appearances":4,"modelRanks":{"ChatGPT":2,"Claude":3,"Gemini":2,"Grok":3},"reason":"Strongest production-focused near-tie with Modal, combining Truss packaging, optimized inference engines, multi-cloud capacity, model-weight caching, configurable autoscaling, observability, and safe deployment promotion.","reasons":[{"model":"ChatGPT","reason":"Strongest production-focused near-tie with Modal, combining Truss packaging, optimized inference engines, multi-cloud capacity, model-weight caching, configurable autoscaling, observability, and safe deployment promotion."},{"model":"Gemini","reason":"Best-in-class for production-scale LLMs and complex generative models, featuring native integration with Truss for containerization, highly optimized inference runtimes, and robust autoscaling under high-traffic SLAs."},{"model":"Claude","reason":"Strongest production-grade option — Truss packaging (open source), TensorRT-LLM/vLLM-optimized runtimes out of the box, genuinely fast cold starts, strong autoscaling and observability, and self-hosted/BYO-cloud deployment for enterprises; it targets teams running custom models at real traffic volume rather than hobby projects."},{"model":"Grok","reason":"Strong production focus with Truss for custom model packaging, autoscaling/observability, compliance features, and good multi-GPU support; balances control and managed serving well for enterprise-ish typical users."}],"fixes":[{"model":"ChatGPT","fix":"Premium, relatively opaque pricing makes it less attractive for cost-sensitive experiments and small workloads."},{"model":"Claude","fix":"Priced and designed for production workloads — per-minute GPU rates run higher than RunPod, and the platform is heavier than a solo developer or experimenter needs."},{"model":"Gemini","fix":"Lacks a versatile developer-first workflow for general, non-ML batch tasks or raw Python pipelines, keeping its focus narrow to model serving."},{"model":"Grok","fix":"Higher cost and per-minute elements in some configs; less emphasis on raw cheapest commodity GPUs."}],"updated":"2026-07-18","rank_history":{"days":["2026-07-17","2026-07-18"],"ranks":[3,2]},"api":"https://modelsagree.com/api/v1/best/best-gpu-serverless-platforms-for-ai-inference.json"},{"slug":"best-serverless-gpu-cloud-for-bursty-inference","title":"Best serverless GPU cloud for bursty inference","rank":3,"of":6,"score":9,"appearances":3,"modelRanks":{"ChatGPT":3,"Claude":3,"Gemini":3},"reason":"Strongest production-focused managed option for custom models, combining Truss packaging, optimized inference runtimes, multi-cloud capacity, weight caching, request parking, observability, autoscaling, and safe deployment promotion workflows.","reasons":[{"model":"ChatGPT","reason":"Strongest production-focused managed option for custom models, combining Truss packaging, optimized inference runtimes, multi-cloud capacity, weight caching, request parking, observability, autoscaling, and safe deployment promotion workflows."},{"model":"Claude","reason":"Strongest production-grade option — Truss packaging plus a TensorRT-LLM-optimized inference stack, fast autoscaling with scale-to-zero, solid SLAs, and the best story for teams that need low p99s and enterprise compliance on custom model deployments rather than a hacker-friendly sandbox."},{"model":"Gemini","reason":"Enterprise-grade deployment and observability built on the open-source Truss framework, utilizing pre-warmed networks to optimize cold-start performance for production model serving."}],"fixes":[{"model":"ChatGPT","fix":"Premium pricing and minute-based replica billing—including startup time—make it a weaker value for tiny, highly intermittent workloads."},{"model":"Claude","fix":"Enterprise pricing and posture — overkill and costly for solo developers or side projects, and less flexible for arbitrary non-inference GPU jobs than Modal or RunPod."},{"model":"Gemini","fix":"Designed exclusively for model serving endpoints, rendering it unsuitable for arbitrary batch jobs, parallel maps, or general Python execution."}],"updated":"2026-07-17","api":"https://modelsagree.com/api/v1/best/best-serverless-gpu-cloud-for-bursty-inference.json"},{"slug":"best-serverless-gpu-platform","title":"Best serverless GPU platform","rank":3,"of":8,"score":8,"appearances":4,"modelRanks":{"ChatGPT":5,"Claude":3,"Gemini":3,"Grok":5},"reason":"The production-inference specialist — Truss packaging, TensorRT-LLM/engine-level optimizations baked in, strong autoscaling and observability, and SOC 2/HIPAA posture that makes it the safe choice for latency-sensitive customer-facing inference at scale.","reasons":[{"model":"Claude","reason":"The production-inference specialist — Truss packaging, TensorRT-LLM/engine-level optimizations baked in, strong autoscaling and observability, and SOC 2/HIPAA posture that makes it the safe choice for latency-sensitive customer-facing inference at scale."},{"model":"Gemini","reason":"Superior enterprise-grade MLOps features built around the open-source Truss framework, offering robust observability, native version control, and seamless canary rollouts out of the box for production inference."},{"model":"ChatGPT","reason":"Strongest specialist for polished production inference: Truss packaging, optimized runtimes, fast scale-to-zero, observability, rolling deployments, multi-cloud scheduling, compliance, and serious engineering support."},{"model":"Grok","reason":"Truss framework simplifies packaging/deploying PyTorch/TF/HF models to production APIs with clean UI, configurable scaling, and good GPU options—practical for teams moving models to low-latency inference."}],"fixes":[{"model":"ChatGPT","fix":"Its inference-focused, per-minute dedicated compute is costlier and less flexible for experimentation, arbitrary batch work, or budget-sensitive users."},{"model":"Claude","fix":"Inference-focused and pricier — it's not the tool for ad-hoc batch jobs, training runs, or general GPU scripting, where Modal or RunPod flex better."},{"model":"Gemini","fix":"Strictly tailored for real-time model inference, making it unsuitable for training, fine-tuning, or generic Python batch workloads."},{"model":"Grok","fix":"Per-minute billing and higher costs for platform features (not the cheapest for high-volume raw compute or non-model-serving tasks)."}],"updated":"2026-07-15","rank_history":{"days":["2026-07-13","2026-07-15"],"ranks":[3,5]},"api":"https://modelsagree.com/api/v1/best/best-serverless-gpu-platform.json"},{"slug":"best-gpu-cloud-for-inference","title":"Best GPU cloud for inference","rank":4,"of":9,"score":7,"appearances":2,"modelRanks":{"Claude":2,"Gemini":3},"reason":"Purpose-built inference platform with production-grade autoscaling, optimized serving (TensorRT-LLM, speculative decoding) baked in via Truss, multi-cloud capacity pooling, and real SLAs — the strongest choice when inference latency and reliability are revenue-critical.","reasons":[{"model":"Claude","reason":"Purpose-built inference platform with production-grade autoscaling, optimized serving (TensorRT-LLM, speculative decoding) baked in via Truss, multi-cloud capacity pooling, and real SLAs — the strongest choice when inference latency and reliability are revenue-critical."},{"model":"Gemini","reason":"Production-ready serverless GPU hosting built around the open-source Truss packaging framework. Combines infrastructure-level customization (such as cold start optimization and multi-model routing) with serverless scaling and enterprise options like VPC deployments."}],"fixes":[{"model":"Claude","fix":"You pay a platform premium and it's inference-only — not for teams that also need training, batch, or arbitrary GPU compute on the same platform."},{"model":"Gemini","fix":"Billing is based on active compute time (per-minute) rather than per-token, making it significantly more expensive for continuous, high-throughput production traffic."}],"updated":"2026-07-15","rank_history":{"days":["2026-07-12","2026-07-13","2026-07-14","2026-07-15"],"ranks":[3,4,4,4]},"reasoning_shift":[{"model":"Claude","from":"2026-07-14","to":"2026-07-15","added":[{"t":"speculative decoding","q":"speculative decoding"},{"t":"baked in via Truss","q":"baked in via Truss"},{"t":"training, batch, or arbitrary GPU compute","q":"not for teams that also need training, batch, or arbitrary GPU compute on the same platform"}],"dropped":[{"t":"near-tie with CoreWeave","q":"near-tie with CoreWeave"},{"t":"overkill below meaningful production traffic","q":"overkill below meaningful production traffic"}]}],"api":"https://modelsagree.com/api/v1/best/best-gpu-cloud-for-inference.json"},{"slug":"best-model-serving-and-deployment-platform","title":"Best model serving and deployment platform","rank":4,"of":10,"score":4,"appearances":1,"modelRanks":{"ChatGPT":2},"reason":"Purpose-built production inference with Truss packaging, strong cold-start and autoscaling performance, optimized model serving, observability, and private-cloud deployment; it can outrank Modal when predictable low latency is the primary requirement","reasons":[{"model":"ChatGPT","reason":"Purpose-built production inference with Truss packaging, strong cold-start and autoscaling performance, optimized model serving, observability, and private-cloud deployment; it can outrank Modal when predictable low latency is the primary requirement"}],"fixes":[{"model":"ChatGPT","fix":"Premium economics and platform complexity are hard to justify for small, intermittent, or experimental workloads"}],"updated":"2026-07-15","rank_history":{"days":["2026-06-29","2026-06-30","2026-07-08","2026-07-09","2026-07-10","2026-07-14","2026-07-15"],"ranks":[2,1,1,2,1,3,3]},"reasoning_shift":[{"model":"ChatGPT","from":"2026-07-14","to":"2026-07-15","added":[{"t":"private-cloud deployment","q":"private-cloud deployment"},{"t":"predictable low latency","q":"it can outrank Modal when predictable low latency is the primary requirement"},{"t":"small intermittent experimental workloads","q":"platform complexity are hard to justify for small, intermittent, or experimental workloads"}],"dropped":[{"t":"scale-to-zero","q":"scale-to-zero"},{"t":"CI/CD and safe environment promotion","q":"CI/CD, safe environment promotion"},{"t":"multimodal and streaming workloads","q":"demanding LLM, multimodal, and streaming workloads"}]}],"api":"https://modelsagree.com/api/v1/best/best-model-serving-and-deployment-platform.json"},{"slug":"best-cd-pipeline-for-machine-learning","title":"Best CD pipeline for machine learning","rank":10,"of":12,"score":1,"appearances":1,"modelRanks":{"Gemini":5},"reason":"Delivers the fastest, turnkey serverless CD pipeline for LLMs and deep learning models via the Truss packaging framework, offering built-in staging-to-prod environment promotion.","reasons":[{"model":"Gemini","reason":"Delivers the fastest, turnkey serverless CD pipeline for LLMs and deep learning models via the Truss packaging framework, offering built-in staging-to-prod environment promotion."}],"fixes":[{"model":"Gemini","fix":"Requires adoption of the Truss framework and Baseten hosting, limiting container-level custom runtime modifications."}],"updated":"2026-07-15","api":"https://modelsagree.com/api/v1/best/best-cd-pipeline-for-machine-learning.json"}],"page":"https://modelsagree.com/product/baseten","check":"https://modelsagree.com/check?q=Baseten","updated":"2026-08-10T18:18:45.051Z","attribution":"modelsagree.com, CC BY 4.0"}