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Compare GPU and LLM inference API pricing between Lambda Labs and Wafer. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Lambda Labs Price | Wafer Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A10 24GB VRAM • Lambda Labs | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 SXM 80GB VRAM • Lambda Labs | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
B200 192GB VRAM • | ||||
GH200 96GB VRAM • Lambda Labs | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 SXM 80GB VRAM • Lambda Labs | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
RTX A6000 48GB VRAM • Lambda Labs | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
Tesla V100 32GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
Tesla V100 32GB VRAM • | ||||
A10 24GB VRAM • Lambda Labs | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 SXM 80GB VRAM • Lambda Labs | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
B200 192GB VRAM • | ||||
GH200 96GB VRAM • Lambda Labs | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 SXM 80GB VRAM • Lambda Labs | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
RTX A6000 48GB VRAM • Lambda Labs | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
Tesla V100 32GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
Tesla V100 32GB VRAM • | ||||
Explore how these providers compare to other popular GPU cloud services
Compare Lambda Labs with another leading provider
Compare Lambda Labs with another leading provider
Compare Lambda Labs with another leading provider
Compare Lambda Labs with another leading provider
Compare Lambda Labs with another leading provider
Compare Lambda Labs with another leading provider
Pay-as-you-go API access to hosted open-source models including GLM, Kimi, Qwen, and DeepSeek with no infrastructure management
Custom-tuned inference deployments with performance guarantees, provisioned in under 24 hours
Agents profile inference bottlenecks and tune across serving engines (vLLM, SGLang, TensorRT-LLM), custom kernels (CUDA, HIP, Triton, NKI), quantization (FP8/FP4), and decode strategies
Workloads run on NVIDIA B200/B300, AMD MI350X/MI355X, and AWS Trainium depending on the model and traffic shape
Standard chat completions endpoint at pass.wafer.ai/v1 with Bearer token authentication
Cached input tokens are billed at reduced rates on supported models
Prepaid credits with separate input and output token rates per model and no subscription
Reduced rates for cached input tokens on supported models
Custom pricing for dedicated deployments with tuned performance targets, arranged with the sales team
Sign up at app.wafer.ai and load credits for pay-as-you-go usage
Create a key in the console and pass it as a Bearer token
Call the OpenAI-compatible endpoint at pass.wafer.ai/v1 with a model from the serverless catalog
Documentation at docs.wafer.ai, email support (hi@wafer.ai), and scheduled onboarding calls for enterprise