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Wafer vs Particle.AI
Wafer tunes serving stacks to run big open models faster. Particle.AI sells cheap Flash-class models with 1M context through Vercel AI Gateway. Speed and size versus price per token.
By The Subconscious Team · Updated
Wafer vs Particle.AI: key differences
Wafer and Particle.AI are both very early companies with small catalogs, but they compete on different numbers. Wafer's pitch is speed on the same weights: its agents tune batching, decoding, quantization and kernels, and it reports GLM 5.1 and DeepSeek V4 Pro each running 2x faster than a vLLM baseline. Access comes through Wafer Pass, a flat-rate subscription from $10 a week, or dedicated deployments built around your SLO. Particle's pitch is cost. On Vercel AI Gateway it lists GLM 5.3 Flash at $0.10 in and $0.40 out and DeepSeek V4.1 Flash at $0.25 in and $1 out, with 1M context and $0.03 cache reads.
The workloads rarely overlap. Wafer suits a coding agent that wants a large model like Qwen 3.5 397B to respond at interactive speed, billed as a predictable weekly fee. Particle suits high-volume, per-token calls on small Flash models, or a price-optimized fallback route inside a gateway, with no new contract to sign. Particle's weak spot is latency, about 3.5 seconds on some DeepSeek V4.1 Flash listings. Wafer's weak spot is proof: its speedups are measured against stock baselines, not against other tuned hosts.
What Wafer and Particle.AI 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. 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: Qwen 3.5 397B Turbo, GLM 5.1 Turbo
Full Wafer profile
Particle.AI
Particle AI is an early San Francisco infrastructure startup with a mission to make intelligence as cheap and abundant as electricity. The team works on post-training, inference optimization and distributed systems, all aimed at pushing down cost per unit of intelligence. It is still hiring its founding team and works fully in person. Public detail about funding and founders is thin as of this writing.
Example models: DeepSeek V4.1 Flash, GLM 5.3 Flash
Full Particle.AI profileShould you choose Wafer or Particle.AI?
Wafer
Choose Wafer for
- Interactive coding agents on large open models.
- Flat weekly pricing instead of metered tokens.
- Custom dedicated deployments tuned to a latency target.
Particle.AI
Choose Particle.AI for
- Cheap high-volume calls on DeepSeek and GLM Flash models.
- Full 1M context on a small model at low per-token prices.
- Adding a fallback route through Vercel AI Gateway with no contract.
Wafer vs Particle.AI at a glance
| Attribute | Wafer |  Particle.AI |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | Qwen 3.5 397B Turbo, GLM 5.1 Turbo | DeepSeek V4.1 Flash, GLM 5.3 Flash |
| Speed | 2–2.8x vs stock vLLM or SGLang | ~157 tok/s on DeepSeek V4.1 Flash |
| Price | Wafer Pass from $10 a week | $0.10 in, $0.40 out (GLM 5.3 Flash) |
| Customization | Agent-tuned dedicated deployments | Unknown |
| Deployment | Serverless pass, dedicated | Via Vercel AI Gateway |
| Long context | Varies by model | 1M |
Frequently asked questions
What is the difference between Wafer and Particle.AI?
Wafer tunes serving stacks to run big open models faster. Particle.AI sells cheap Flash-class models with 1M context through Vercel AI Gateway. Speed and size versus price per token.
When should I choose Wafer over Particle.AI?
Interactive coding agents on large open models; Flat weekly pricing instead of metered tokens; Custom dedicated deployments tuned to a latency target.
When should I choose Particle.AI over Wafer?
Cheap high-volume calls on DeepSeek and GLM Flash models; Full 1M context on a small model at low per-token prices; Adding a fallback route through Vercel AI Gateway with no contract.
Is Wafer or Particle.AI cheaper?
Wafer: Wafer Pass from $10 a week. Particle.AI: $0.10 in, $0.40 out (GLM 5.3 Flash). The cheaper choice depends on the model and workload.
Which has more context, Wafer or Particle.AI?
Wafer: Varies by model. Particle.AI: 1M.
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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.