Amazon CloudFront vs Baseten (2026): Pricing, Features & Verdict

A

Why choose Amazon CloudFront

• Has a free plan (Baseten does not)
• Higher Integration score (9/10 vs 6/10)
• Higher Cost score (6/10 vs 5/10)
• Better fit for small business (5/10 vs 2/10)

Why choose Baseten

• Higher Ease of Use score (6/10 vs 5/10)

A

Amazon CloudFront

Pros

• The network is very large, with more than 750 PoPs plus over 1,140 PoPs embedded inside ISP networks.
• Data transfer from AWS origins such as S3 and EC2 to CloudFront costs nothing, which lowers costs for workloads hosted on AWS.
• Flat-rate plans start at $15 a month with no overage charges, which makes bills predictable.
• It has strong compliance coverage, including PCI-DSS Level 1, HIPAA, SOC, ISO and FedRAMP Moderate.
• Two tiers of edge compute are available: CloudFront Functions at $0.10 per million invocations and Lambda@Edge for heavier code.

Cons

• G2 and Capterra reviewers report complex configuration and a steep learning curve for people new to AWS.
• Capterra-network reviewers rate customer support poorly, around 3.4 out of 5.
• Flat-rate plans lack some features, such as real-time logs, dedicated IP SSL and continuous deployment, and going over the allowance reduces performance.
• Dedicated IP SSL at $600 a month and Anycast Static IPs at $3,000 a month are expensive extras.
• Users on AWS re:Post and GitHub report cache invalidations that occasionally hang for hours or time out during deploys.

Baseten

Pros

• Broad compliance coverage: SOC 2 Type II, SOC 3, HIPAA with a BAA, GDPR and PCI DSS, plus BYOK encryption for model weights and payloads.
• Flexible deployment: the same stack runs on Baseten's multi-cloud pool, on single-tenant clusters, or in a self-hosted data plane inside your own VPC.
• Per-minute GPU billing and scale to zero (min replicas defaults to 0) mean idle dev deployments cost nothing.
• Wide range of GPUs, from T4 at about $0.63 an hour to B200 at about $9.98 an hour, with failover across 20+ cloud providers.
• Built-in logs, metrics and traces for every dedicated deployment, exportable to Datadog, Prometheus, Grafana and New Relic.

Cons

• Covers inference, training and sandboxes only, so databases, object storage and general app hosting need another provider.
• Dedicated replicas bill per minute while they run, including cold-start time and the default 15-minute scale-down delay, which can make bills hard to predict.
• Built for ML engineers. Reviewers say non-technical teams will struggle, and performance tuning still needs ML expertise.
• Very few independent reviews: G2 lists too few reviews to give buying insight.
• SLAs, reserved capacity and volume discounts are only available through negotiated contracts with sales.