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Wafer vs OpenScale
Wafer sells agent-tuned inference on open models, serverless or dedicated. OpenScale sells DeepSeek V4.1 Flash serverless at promotional low prices.
By The Subconscious Team · Updated
Wafer vs OpenScale: key differences
Wafer, a Y Combinator company in San Francisco, uses agents to tune inference stacks on NVIDIA and AMD, reports 2x to 2.8x speedups over stock vLLM or SGLang, and serves GLM-5.3 and DeepSeek V4.1 Flash through serverless and dedicated deployments. OpenScale's own comparison lists Wafer's DeepSeek V4.1 Flash at $0.045 in, $0.044 cached and $1.20 out. OpenScale, a Y Combinator-backed API out of Singapore, serves DeepSeek V4.1 Flash at $0.06 in, $0.003 cached and $0.24 out per million tokens under a 50% promotion, at 200+ tokens per second, with a fast tier at about twice the speed.
Both plug into Claude Code and similar harnesses with OpenAI- and Anthropic-compatible APIs. Wafer is the pick for big open models at interactive speed or a dedicated endpoint tuned to an SLO. OpenScale is the pick when cached input dominates the bill, since its cached rate is far lower.
What Wafer and OpenScale do
Wafer
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 profileOpenScale
OpenScale is a Y Combinator-backed inference API built by LatentSpace and run out of Singapore. It sells open models behind one endpoint that speaks Chat Completions, the OpenAI Responses API and Anthropic Messages, so Claude Code, Codex, OpenCode, Cline, GitHub Copilot, Zed and other coding agents can point at it with a base URL and key. Its public catalog today is DeepSeek V4.1 Flash in two versions, standard and fast, both with a 1M token context window and up to 384K output tokens.
Example models: DeepSeek V4.1 Flash
Full OpenScale profileShould you choose Wafer or OpenScale?
Wafer vs OpenScale at a glance
| Attribute | Wafer | OpenScale |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GLM-5.3, DeepSeek V4.1 Flash | DeepSeek V4.1 Flash |
| Speed | ~176 tok/s on GLM-5.3; 2–2.8x vs stock vLLM or SGLang (vendor) | 200+ tok/s; fast tier ~2x |
| Price | Per token, prepaid credits | $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash) |
| Customization | Agent-tuned dedicated deployments | N/A |
| Deployment | Serverless, dedicated | Serverless API |
| Long context | Up to 1M (GLM-5.3, DeepSeek V4.1 Flash) | 1M context |
Frequently asked questions
What is the difference between Wafer and OpenScale?
Wafer sells agent-tuned inference on open models, serverless or dedicated. OpenScale sells DeepSeek V4.1 Flash serverless at promotional low prices.
When should I choose Wafer over OpenScale?
GLM-5.3 at interactive speed; Dedicated endpoints tuned to a latency SLO; NVIDIA and AMD hardware.
When should I choose OpenScale over Wafer?
Low cached-input prices on DeepSeek V4.1 Flash; Cache-heavy agent traffic; Zero data retention by default.
Is Wafer or OpenScale cheaper?
Wafer: Per token, prepaid credits. OpenScale: $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, Wafer or OpenScale?
Wafer: Up to 1M (GLM-5.3, DeepSeek V4.1 Flash). OpenScale: 1M context.
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.