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Moonshot AI vs Wafer
Moonshot's slow, strong Kimi K3 against Wafer's agent-tuned open models, billed per token. The trade is top open capability versus speed.
By The Subconscious Team · Updated
Moonshot AI vs Wafer: key differences
Wafer's pitch starts where Kimi K3 struggles. K3 runs around 33 tokens per second on Moonshot's API, and Wafer's agents tune inference stacks to run open models faster on the same weights. 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 a vLLM baseline, all self-reported against stock setups. Its serverless API bills per token and drops into Claude Code, Cline and OpenHands. Kimi is not in Wafer's listed catalog, so switching means switching models too.
K3 still offers things that catalog may not match: near-frontier coding scores confirmed by independent testers, a 1M window and native vision, billed at $3 in and $15 out with cached input at $0.30. Wafer is a very young company with a small hosted catalog, and its speedups deserve a check against hosts that already tune their stacks. For dedicated work, Wafer builds deployments around a customer's model and SLO on NVIDIA or AMD. Pick K3 for hard unattended work, and Wafer for fast interactive coding.
What Moonshot AI and Wafer do
Moonshot AI
Moonshot AI is the Beijing lab behind the Kimi models. Its flagship Kimi K3 launched July 16, 2026 as a 2.8 trillion parameter mixture-of-experts model that activates 16 of 896 experts per token, with native vision and a 1M token context. It is the first open model in the 3T class, and full weights landed on Hugging Face on July 27. The hosted API costs $3 in and $15 out per million tokens, with cached input at $0.30, and it runs through an OpenAI compatible endpoint, Kimi Code in the terminal, OpenRouter and Cloudflare Workers AI.
Example models: Kimi K3.1 Pro, Kimi K3
Full Moonshot AI 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 Moonshot AI or Wafer?
Moonshot AI
Choose Moonshot AI for
- Hard coding tasks where K3's benchmark results matter
- 1M context and native vision in one model
- Per-token billing with cheap cached input
Wafer
Choose Wafer for
- Interactive coding on big open models at tuned speed
- Dedicated endpoints tuned to a latency SLO
- Hedging GPU supply across NVIDIA and AMD
Moonshot AI vs Wafer at a glance
| Attribute | Moonshot AI | Wafer |
|---|---|---|
| Model access | Open weights, custom license | Open weights |
| Flagship models | Kimi K3.1 Pro, Kimi K3 | GLM-5.3, DeepSeek V4.1 Flash |
| Speed | ~33 tok/s on Kimi K3 | ~168 tok/s on GLM-5.3; 2–2.8x vs stock vLLM or SGLang (vendor) |
| Price | $2 in, $10 out (K3.1 Pro); $3 in, $15 out (K3) | Per token, prepaid credits |
| Customization | Open weights to fine-tune | Agent-tuned dedicated deployments |
| Deployment | API, Kimi Code, OpenRouter | Serverless, dedicated |
| Long context | 1M | Up to 1M (GLM-5.3, DeepSeek V4.1 Flash) |
Frequently asked questions
What is the difference between Moonshot AI and Wafer?
Moonshot's slow, strong Kimi K3 against Wafer's agent-tuned open models, billed per token. The trade is top open capability versus speed.
When should I choose Moonshot AI over Wafer?
Hard coding tasks where K3's benchmark results matter; 1M context and native vision in one model; Per-token billing with cheap cached input.
When should I choose Wafer over Moonshot AI?
Interactive coding on big open models at tuned speed; Dedicated endpoints tuned to a latency SLO; Hedging GPU supply across NVIDIA and AMD.
Is Moonshot AI or Wafer cheaper?
Moonshot AI: $2 in, $10 out (K3.1 Pro); $3 in, $15 out (K3). Wafer: Per token, prepaid credits. The cheaper choice depends on the model and workload.
Which has more context, Moonshot AI or Wafer?
Moonshot AI: 1M. Wafer: Up to 1M (GLM-5.3, DeepSeek V4.1 Flash).
Related comparisons
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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.