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Baseten vs Wafer
Wafer uses AI agents to tune inference stacks and reports 2x or more over stock engines. Baseten has independently measured latency, a broader platform and compliance.
By The Subconscious Team · Updated
Baseten vs Wafer: key differences
Both companies sell speed on open weights, but the evidence differs. Wafer's agents profile a workload, try configurations across batching, decoding, quantization, kernels and hardware, and deploy the winner, then keep re-tuning. Wafer reports its Qwen 3.5 397B running 2.8x faster than stock SGLang and GLM 5.1 and DeepSeek V4 Pro each 2x faster than vLLM. Those are self-reported against untuned baselines, and Wafer's own downside advises comparing against tuned hosts before buying. Baseten is one of those tuned hosts, with a 0.49 second time to first token measured by Artificial Analysis in August 2026.
The business shape is different too. Wafer is a very young company with a small hosted catalog. Its serverless API bills per token and drops into Claude Code, Cline and OpenHands, and it runs on NVIDIA or AMD. Baseten offers about a dozen curated models, Truss for custom ones, HIPAA, data residency and a 99.99% SLA. An individual developer on an agent harness can get far on Wafer's serverless API. A company with an SLO and a compliance checklist has more assurance on Baseten.
What Baseten and Wafer do
Baseten
Baseten runs two products. Model APIs serve a curated set of about a dozen open models, including GLM 5.3, DeepSeek V4.1 Flash, DeepSeek V4 Pro 0813, Kimi K3 and gpt-oss 120B, over endpoints that speak both the OpenAI Chat Completions shape and the Anthropic Messages shape. That dual compatibility means an existing OpenAI or Claude SDK, or a coding agent, points at Baseten with a base URL change. Dedicated deployments take any model you package with the open-source Truss CLI and bill per GPU minute, with an H100 at about $6.50 an hour.
Example models: GLM 5.3, gpt-oss 120B
Full Baseten profileWafer
Wafer builds AI agents that act as GPU performance engineers, then sells inference on the stacks those agents tune. The company came out of Y Combinator's Summer 2025 batch as a "Cursor for CUDA" that turned slow PyTorch into custom kernels. Founders Emilio Andere and Steven Arellano are based in San Francisco. Wafer raised a $4M seed led by Fifty Years in April 2026 and a $40M Series A co-led by Marathon and Chemistry in September 2026 at a $220M post-money valuation, with AMD Ventures and Wing joining. Its agents profile a workload, generate candidate configs across batching, decoding, quantization, engines, kernels and hardware, measure each one and deploy the winner.
Example models: GLM-5.3, DeepSeek V4.1 Flash
Full Wafer profileShould you choose Baseten or Wafer?
Baseten
Choose Baseten for
- Production endpoints backed by a 99.99% SLA
- Independently measured low first-token latency
- Custom speech, embedding or fine-tuned models
Wafer
Choose Wafer for
- Fast open models inside Claude Code or Cline
- Dedicated deployments re-tuned as traffic changes
- Teams hedging GPU supply across NVIDIA and AMD
Baseten vs Wafer at a glance
| Attribute | Baseten | Wafer |
|---|---|---|
| Model access | Open weights, about a dozen curated | Open weights |
| Flagship models | GLM 5.3, DeepSeek V4.1 Flash, Kimi K3, gpt-oss 120B | GLM-5.3, DeepSeek V4.1 Flash |
| Speed | 0.49s TTFT, lowest measured | ~176 tok/s on GLM-5.3; 2–2.8x vs stock vLLM or SGLang (vendor) |
| Price | H100 about $6.50/hr dedicated | Per token, prepaid credits |
| Customization | Deploy any model with Truss | Agent-tuned dedicated deployments |
| Deployment | Model APIs, dedicated, self-host | Serverless, dedicated |
| Long context | Varies by model | Up to 1M (GLM-5.3, DeepSeek V4.1 Flash) |
Frequently asked questions
What is the difference between Baseten and Wafer?
Wafer uses AI agents to tune inference stacks and reports 2x or more over stock engines. Baseten has independently measured latency, a broader platform and compliance.
When should I choose Baseten over Wafer?
Production endpoints backed by a 99.99% SLA; Independently measured low first-token latency; Custom speech, embedding or fine-tuned models.
When should I choose Wafer over Baseten?
Fast open models inside Claude Code or Cline; Dedicated deployments re-tuned as traffic changes; Teams hedging GPU supply across NVIDIA and AMD.
Is Baseten or Wafer cheaper?
Baseten: H100 about $6.50/hr dedicated. Wafer: Per token, prepaid credits. The cheaper choice depends on the model and workload.
Which has more context, Baseten or Wafer?
Baseten: Varies by model. Wafer: Up to 1M (GLM-5.3, DeepSeek V4.1 Flash).
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.