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Wafer vs RunInfra
Two young open-model hosts that both serve coding agents and automate deployment tuning. Wafer aims at big models at speed; RunInfra at small teams shipping mid-size models.
By The Subconscious Team · Updated
Wafer vs RunInfra: key differences
These two look alike on paper. Both are young companies, both serve open weights, both plug into coding harnesses like Claude Code and Cline, and both use an agent to tune deployments. The difference is where each points that agent. Wafer's agents act as GPU performance engineers, rewriting kernels and configs around a customer's model and SLO on NVIDIA or AMD, and Wafer reports its tuned Qwen 3.5 397B running 2.8x faster than stock SGLang. RunInfra's agent takes a plain-English request, benchmarks models across GPUs from L4 to B200, tries quantized variants like AWQ, GPTQ and FP8, and ships an endpoint that scales to zero with cold starts under two seconds.
Model size is the practical split. Wafer's hosted catalog is small but includes large models such as GLM-5.3 and DeepSeek V4.1 Flash. RunInfra's library centers on mid-size models like Nemotron 3.5 Lightning 30B and Qwen 3.8 27B, plus GLM 5.3. Pricing differs too: Wafer bills serverless use per token, while RunInfra sells coding plans from $10 a month. RunInfra also accepts custom uploads up to 50 GB and chains voice pipelines. Both speed claims are self-reported, so test on your own traffic.
What Wafer and RunInfra 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 profileRunInfra
RunInfra pitches open models built for agents, with two ways in. Its hosted Model APIs serve an eight-model library, including Nemotron 3.5 Lightning 30B, Qwen 3.8 27B, Ornith 1.5 35B and 122B, GLM 5.3, GLM 5.3 Flash and two versions of DeepSeek V4.1 Flash, behind one key that works with both the OpenAI and Anthropic SDKs. Prices run from $0.05 in and $0.15 out on Nemotron to $1.30 in and $4.20 out on GLM 5.3, and cached input starts at $0.01. Coding plans start at $10 a month with limits that reset every five hours and every week, and they plug into Claude Code, Codex, OpenCode, Cline, Aider and dozens of other agent CLIs.
Example models: Nemotron 3.5 Lightning 30B, Qwen 3.8 27B
Full RunInfra profileShould you choose Wafer or RunInfra?
Wafer
Choose Wafer for
- Coding agents that need large open models at interactive speed.
- Dedicated endpoints with a strict latency SLO, retuned as load changes.
- Teams hedging GPU supply across NVIDIA and AMD.
RunInfra
Choose RunInfra for
- The lowest-cost coding plan for a mid-size open model.
- Small teams deploying a custom upload without ML ops staff.
- Voice pipelines chaining Whisper, an LLM and TTS.
Wafer vs RunInfra at a glance
| Attribute | Wafer | RunInfra |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GLM-5.3, DeepSeek V4.1 Flash | Nemotron 3.5 Lightning 30B, Qwen 3.8 27B |
| Speed | ~168 tok/s on GLM-5.3; 2–2.8x vs stock vLLM or SGLang (vendor) | ~541 tok/s on Nemotron 3.5 Lightning 30B (vendor); cold starts under 2s |
| Price | Per token, prepaid credits | From $0.05 in, $0.15 out; coding plans from $10 a month |
| Customization | Agent-tuned dedicated deployments | Uploads up to 50 GB; auto-quantization |
| Deployment | Serverless, dedicated | Model APIs, agent-built endpoints |
| Long context | Up to 1M (GLM-5.3, DeepSeek V4.1 Flash) | Varies by model |
Frequently asked questions
What is the difference between Wafer and RunInfra?
Two young open-model hosts that both serve coding agents and automate deployment tuning. Wafer aims at big models at speed; RunInfra at small teams shipping mid-size models.
When should I choose Wafer over RunInfra?
Coding agents that need large open models at interactive speed; Dedicated endpoints with a strict latency SLO, retuned as load changes; Teams hedging GPU supply across NVIDIA and AMD.
When should I choose RunInfra over Wafer?
The lowest-cost coding plan for a mid-size open model; Small teams deploying a custom upload without ML ops staff; Voice pipelines chaining Whisper, an LLM and TTS.
Is Wafer or RunInfra cheaper?
Wafer: Per token, prepaid credits. RunInfra: From $0.05 in, $0.15 out; coding plans from $10 a month. The cheaper choice depends on the model and workload.
Which has more context, Wafer or RunInfra?
Wafer: Up to 1M (GLM-5.3, DeepSeek V4.1 Flash). RunInfra: Varies by model.
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