Save 50% on every LLM API call
InferCut is a drop-in proxy for your LLM calls. Same output quality, one line of code, half the cost. If we can’t save you money on a call, you aren’t charged.
from openai import OpenAI
# Switch to InferCut in one line
client = OpenAI(
base_url="https://infercut.com/v1",
api_key="INFER_..."
)
# 50% cheaper, same output
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "..."}]
)Works with every major model
- OpenAI
- Anthropic
- Gemini
- Llama
- Grok
- Mistral
- DeepSeek
The numbers speak for themselves
Move the slider to your monthly LLM spend. We cut roughly half of it — same quality, one line of code.
$2,500/mo
$30,000/yr
Three steps. That’s it.
Drop InferCut in front of any OpenAI-compatible client. You’re live in under five minutes.
Change one line
Point your API base URL to InferCut. No custom SDKs, no migration, no downtime.
base_url="https://infercut.com/v1"Calls flow through
Your existing application works exactly the same. We handle the routing and optimization layer automatically.
Same quality, half the cost
Identical outputs from the models you already use. Your bill drops by up to 50% immediately.
Where the savings come from
A stack of inference-level optimizations, applied automatically on every call. Nothing for you to configure.
Semantic caching
Queries with the same intent are served instantly from cache, with zero inference cost.
Prompt compression
Context is transparently compressed up to 20× using state-of-the-art techniques, while preserving output quality.
Response caching
Deterministic queries never pay for inference twice. Identical inputs return in microseconds.
Batch API optimization
Async workloads are transparently served via batch endpoints at up to 50% off on supported models.
Provider-native prompt caching
KV-cache reuse is automatically engaged whenever the upstream API supports it — so repeated prefixes cost a fraction.
Smaller wins compound
Fine-grained optimizations that add up call after call.
Context deduplication
Redundant chunks are removed from RAG pipelines before they hit the model.
Constrained decoding
Structured outputs (JSON, tool args, enums) produced with fewer tokens.
Tool-call memoization
Agent workflows cache deterministic tool steps across runs.
Reasoning budget control
Thinking tokens on reasoning models are capped when the task doesn't need them.
Streaming with early termination
Stop tokens and length hints cut output tokens — and output cost — as soon as the answer is done.
Same quality. Guaranteed.
If quality would ever dip, calls pass through to your original model at no markup. You never pay more than you would have.
Built for teams shipping with LLMs
If your bill has a line for inference, you’re overpaying. Here’s who benefits most.
AI startups
Shipping fast with tight budgets. Cut inference costs from day one and extend your runway.
SaaS with LLM features
AI-powered features shouldn't eat your margins. Same quality, half the API bill.
Inference-heavy agencies
Running LLM workloads across many clients. Save 50% on every single project.
Enterprise AI teams
Large-scale inference at serious volume. The bigger the spend, the bigger the savings.
Frequently asked questions
Simple: you pay less than you do today. The fee is baked into the savings — no tiers, no hidden costs. For every $5 in InferCut credits, the average team saves about $10 on their provider bill.
No. You get the same output quality you get today. If quality would ever dip, calls automatically pass through to your original model at no markup. You never pay more.
One line. You change your API base URL to point to InferCut. Everything else stays the same — your prompts, your client library, your business logic.
Yes. We do not store, log, or train on your prompts or completions. Requests pass through securely and are not retained after the response is returned.
No minimum. You can start with as little as $5 in credits and scale up as you go. InferCut works for solo developers and large engineering teams alike.
Sign up, grab your API key, and change one line of code. The whole process takes under two minutes — most teams are saving within the first day.
Stop overpaying for inference
One line of code. Up to 50% savings. Zero risk — if we can’t save you money on a call, you aren’t charged.