Comet vs Lambda Pricing (2026)

How do these two stack up on price? Here's what each one costs, what you get, and where the value sits.

Comet Lambda
Starts at $19/mo Custom
Number of plans 4 22
Free plan
Free trial
Pricing model usage-based usage-based

Open Source

$0/mo
  • Full AI observability & agent testing feature set
  • True OSS: same codebase as the hosted versions
  • Agent tracing & analysis
  • Test Suites & assertions
  • Agent Playground

Free Cloud

$0/mo
  • Up to 10 team members
  • 25k spans per month
  • 60-day data retention
  • Agent tracing & analysis
  • Test Suites & assertions
  • Agent Playground
  • Ollie coding harness trial

Pro Cloud

Popular
$19/mo
  • Up to 50 team members
  • 100k spans per month
  • 60-day data retention
  • Customizable monthly span limits
  • Customizable data retention periods

Enterprise

Custom
  • Unlimited team members
  • Custom usage plans
  • Flexible deployments
  • Service accounts and view-only users
  • Single sign-on
  • Dedicated support and SLAs
  • SOC 2, ISO 27001, ISO 9001, HIPAA, and GDPR compliance

NVIDIA B200 SXM6 (8x)

Custom
  • VRAM/GPU: 180 GB
  • vCPUs: 208
  • RAM: 2900 GiB
  • Storage: 22 TiB SSD

NVIDIA H100 SXM (8x)

Custom
  • VRAM/GPU: 80 GB
  • vCPUs: 208
  • RAM: 1800 GiB
  • Storage: 22 TiB SSD

NVIDIA A100 SXM 80GB (8x)

Custom
  • VRAM/GPU: 80 GB
  • vCPUs: 240
  • RAM: 1800 GiB
  • Storage: 19.5 TiB SSD

NVIDIA A100 SXM 40GB (8x)

Custom
  • VRAM/GPU: 40 GB
  • vCPUs: 124
  • RAM: 1800 GiB
  • Storage: 5.8 TiB SSD

NVIDIA Tesla V100 (8x)

Custom
  • VRAM/GPU: 16 GB
  • vCPUs: 88
  • RAM: 448 GiB
  • Storage: 5.8 TiB SSD

NVIDIA B200 SXM6 (4x)

Custom
  • VRAM/GPU: 180 GB
  • vCPUs: 104
  • RAM: 1440 GiB
  • Storage: 11 TiB SSD

NVIDIA H100 SXM (4x)

Custom
  • VRAM/GPU: 80 GB
  • vCPUs: 104
  • RAM: 900 GiB
  • Storage: 11 TiB SSD

NVIDIA A100 PCIe (4x)

Custom
  • VRAM/GPU: 40 GB
  • vCPUs: 120
  • RAM: 900 GiB
  • Storage: 1 TiB SSD

NVIDIA A6000 (4x)

Custom
  • VRAM/GPU: 48 GB
  • vCPUs: 56
  • RAM: 400 GiB
  • Storage: 1 TiB SSD

NVIDIA B200 SXM6 (2x)

Custom
  • VRAM/GPU: 180 GB
  • vCPUs: 52
  • RAM: 720 GiB
  • Storage: 5.5 TiB SSD

NVIDIA H100 SXM (2x)

Custom
  • VRAM/GPU: 80 GB
  • vCPUs: 52
  • RAM: 450 GiB
  • Storage: 5.5 TiB SSD

NVIDIA A100 PCIe (2x)

Custom
  • VRAM/GPU: 40 GB
  • vCPUs: 60
  • RAM: 450 GiB
  • Storage: 1 TiB SSD

NVIDIA A6000 (2x)

Custom
  • VRAM/GPU: 48 GB
  • vCPUs: 28
  • RAM: 200 GiB
  • Storage: 1 TiB SSD

NVIDIA B200 SXM6 (1x)

Custom
  • VRAM/GPU: 180 GB
  • vCPUs: 26
  • RAM: 360 GiB
  • Storage: 2.75 TiB SSD

NVIDIA GH200 (1x)

Custom
  • VRAM/GPU: 96 GB
  • vCPUs: 64
  • RAM: 432 GiB
  • Storage: 4 TiB SSD

NVIDIA H100 SXM (1x)

Custom
  • VRAM/GPU: 80 GB
  • vCPUs: 26
  • RAM: 225 GiB
  • Storage: 2.75 TiB SSD

NVIDIA H100 PCIe (1x)

Custom
  • VRAM/GPU: 80 GB
  • vCPUs: 26
  • RAM: 225 GiB
  • Storage: 1 TiB SSD

NVIDIA A100 SXM (1x)

Custom
  • VRAM/GPU: 40 GB
  • vCPUs: 30
  • RAM: 220 GiB
  • Storage: 512 GiB SSD

NVIDIA A100 PCIe (1x)

Custom
  • VRAM/GPU: 40 GB
  • vCPUs: 30
  • RAM: 225 GiB
  • Storage: 512 GiB SSD

NVIDIA A10 (1x)

Custom
  • VRAM/GPU: 24 GB
  • vCPUs: 30
  • RAM: 226 GiB
  • Storage: 1.3 TiB SSD

NVIDIA A6000 (1x)

Custom
  • VRAM/GPU: 48 GB
  • vCPUs: 14
  • RAM: 100 GiB
  • Storage: 512 GiB SSD

NVIDIA Quadro RTX 6000 (1x)

Custom
  • VRAM/GPU: 24 GB
  • vCPUs: 14
  • RAM: 46 GiB
  • Storage: 512 GiB SSD

Comet vs Lambda FAQ

Which one is cheaper?
One or both use custom pricing, so it depends on your specific needs.
Can I use either one for free?
Comet has a free plan. Lambda doesn't — you'll need to pay from day one.
How do they charge?
Both use a usage-based model, so the comparison is straightforward — it comes down to features and limits at each price point.
Which one is a better deal?
Depends on what you need. Comet: At $19/mo entry, they're positioning as the accessible alternative to heavier MLOps platforms — clearly going after teams that find tools like Weights & Biases or Arize too expensive or too complex for pure LLM tracing use cases. The academic free Pro tier signals they're also playing a long game on developer mindshare. Lambda: Lambda positions as a serious alternative to hyperscalers (AWS, GCP, Azure) for ML teams who want raw GPU access without cloud markup or complexity. They're not the cheapest bare-metal option, but the no-egress-fees policy and 1-Click Clusters are a direct shot at teams burned by AWS networking costs.

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