vs
Anthropic vs Wafer
Wafer tunes open models to run faster on the same weights and sells per-token access that drops into Claude Code. It is a budget open-model route next to Anthropic's closed frontier models.
By The Subconscious Team · Updated
Anthropic vs Wafer: key differences
Wafer uses AI agents to tune GPU serving stacks, then sells inference on the result. It reports its tuned 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. Wafer Serverless bills per token from prepaid credits and plugs into Claude Code, Cline and OpenHands. Anthropic's models cost far more per token, from $0.10 in on Haiku 5.5 to $10 in on Fable 5.1, but they lead on coding benchmarks and carry 1M context.
Developers watching their spend can put Wafer inside the same harness they use with Claude and move routine work to it. Teams with a strict latency SLO and no kernel engineers can buy a dedicated Wafer deployment that keeps retuning on NVIDIA or AMD hardware. Wafer is a very young company with a small hosted catalog, and its speedups should be checked against tuned hosts rather than stock baselines. For hard coding, long unattended runs and enterprise procurement, Anthropic is the safer bet.
What Anthropic and Wafer do
Anthropic
Anthropic sells the Claude family of closed models through its own API, Amazon Bedrock, Google Vertex AI and Microsoft Foundry. The public lineup today runs from Claude Fable 5.1 at the top, released September 1, 2026, through Opus 5.5 ($4 in, $20 out) and Sonnet 5.5 ($2 in, $10 out) down to Haiku 5.5. List prices span a hundredfold range, from $10 in and $50 out on Fable to $0.10 in and $0.50 out on Haiku. All four tiers have a 1M token context window. The top three bill it at standard pricing, while Haiku 5.5 charges more past 100K.
Example models: Claude Fable 5.1, Claude Opus 5.5, Claude Haiku 5.5
Full Anthropic 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 Anthropic or Wafer?
Anthropic vs Wafer at a glance
| Attribute | Anthropic | Wafer |
|---|---|---|
| Model access | Closed | Open weights |
| Flagship models | Claude Fable 5.1, Opus 5.5, Sonnet 5.5, Haiku 5.5 | GLM-5.3, DeepSeek V4.1 Flash |
| Speed | Fable is the slowest tier | ~176 tok/s on GLM-5.3; 2–2.8x vs stock vLLM or SGLang (vendor) |
| Price | $0.10–$10 in, $0.50–$50 out per 1M | Per token, prepaid credits |
| Customization | N/A | Agent-tuned dedicated deployments |
| Deployment | API, Bedrock, Vertex AI, Microsoft Foundry | Serverless, dedicated |
| Long context | 1M; Haiku 5.5 costs more past 100K | Up to 1M (GLM-5.3, DeepSeek V4.1 Flash) |
Frequently asked questions
What is the difference between Anthropic and Wafer?
Wafer tunes open models to run faster on the same weights and sells per-token access that drops into Claude Code. It is a budget open-model route next to Anthropic's closed frontier models.
When should I choose Anthropic over Wafer?
Hard coding tasks where frontier quality matters; Enterprise buyers needing an established vendor; Long contexts on managed models.
When should I choose Wafer over Anthropic?
Fast open models inside Claude Code or Cline; Dedicated endpoints tuned to a latency SLO; Teams hedging across NVIDIA and AMD.
Is Anthropic or Wafer cheaper?
Anthropic: $0.10–$10 in, $0.50–$50 out per 1M. Wafer: Per token, prepaid credits. The cheaper choice depends on the model and workload.
Which has more context, Anthropic or Wafer?
Anthropic: 1M; Haiku 5.5 costs more past 100K. 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.