AI · alternatives · 2026
24 alternatives to Compress By Light Reach
AI is a commodity. Your bill should reflect that.
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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AgentReady▲118Compression API that reduces prompt size by 40-60% before sending to your LLM. Your API key never leaves your environment.
Feb 2026 · agentready.cloud · its alternatives →
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I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com · its alternatives →
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Context Gateway▲220We built an open-source proxy that sits between coding agents (Claude Code, OpenClaw, etc.) and the LLM, compressing tool outputs before they enter the context window. Demo: https://www.youtube.com/watch?v=-vFZ6MPrwjw#t=9s. Motivation: Agents are terrible at managing context. A single file read or grep can dump thousands of tokens into the window, most of it noise. This isn't just expensive — it actively degrades quality. Long-context benchmarks consistently show steep accuracy drops as context grows (OpenAI's GPT-5.4 eval goes from 97.2% at 32k to 36.6% at 1M…
Mar 2026 · github.com · its alternatives →
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Paritok▲258Spend up to 85% less and run 3× longer coding agent sessions
Aug 2026 · paritok.com · its alternatives →
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I started leaning in on AI heavily this year, as I wanted to get more done autonomously, but then my token usage climbed dramatically to the point where my weekly quota would run out before the end of the week, sometimes a couple of days into the week. I realised I had to do something about it else I'd have to double my spend. So I decided to start tracking my cost per task type. This revealed that a lot of my spend went to searches/scans or simple things like scouting tasks. I then decided to turn this into a simple CLI tool that can be used to read your OpenAI-style logs locally, and…
Jul 2026 · github.com · its alternatives →
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Tokenwise▲143A smart LLM proxy that shows where you're overpaying
Jun 2026 · tokenwisehq.com · its alternatives →
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Free real-time, low latency lossless LLM prompt compression
2025 · promptfold.web.app · its alternatives →
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Credyt▲100Hey HN! I'm the founder of Credyt (https://credyt.ai). If you're running an AI product that burns $0.50+ per interaction, you need to bill customers as usage happens, not at the end of the month. Otherwise you're a bank for your customers, and you'll run out of money before they do. Why invoice-based billing doesn't work for AI: Most usage-based billing tools (Stripe Billing, Orb, etc.) were built for SaaS. They meter usage all month, then send an invoice. That works fine when your COGS is 5%. It's a disaster when you're paying your AI vendor upfront for every request and your…
Nov 2025 · credyt.ai · its alternatives →
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Promptly▲13An AI Cost Optimization Infrastructure for LLM Applications
Mar 2026 · getpromptly.in · its alternatives →
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Reduce your LLM API bill 11–45% with zero code changes
Apr 2026 · textcompressor.unmutedlive.com · its alternatives →
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Hi HN, we are the founders of Relari (https://www.relari.ai). We launched our LLM evaluation stack on HN a few months ago (https://news.ycombinator.com/item?id=39641105), which is now used in production by AI teams at companies like Vanta and PwC. We have since expanded to directly optimizing parts of an LLM pipeline using a data-driven approach. In particular, we see a lot of potential in the Auto Prompt Optimization—which could be an attractive alternative to fine-tuning in many cases—to use data to align LLMs for domain-specific tasks. Here’s a demo video:…
2024 · its alternatives →
- 15CG
Hey HN! I recently built Prompt Reducer, an app that makes it easier to compress GPT-4 prompts. The main goal is to reduce the number of tokens in each prompt, thereby reducing the cost of running GPT-4. I figured since @gfodor tweeted about compressing GPT-4. It’s still early, and it does not work perfectly, but I’d love to hear any feedback or suggestions for how to make it faster or more efficient.
2023 · promptreducer.com · its alternatives →
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OptiLLM▲5Intelligent LLM Cost Optimization Platform
Mar 2026 · optillm.puniminds.com · its alternatives →
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Argmin AI▲32Hey, HN community! We've built Argmin AI after shipping LLM features where the demo worked, then the bill and latency got unpredictable in production. Prompts expanded, context grew, retrieval got noisy, retries appeared, and agent workflows added loops. Argmin AI optimizes LLM-related expenses as a system: 1. prompt and context efficiency 2. model selection and routing 3. RAG inefficiencies and caching opportunities 4. agent workflows (tool calls, retries, loop control) Changes are validated with evals and guardrails (tests, gates, judges), tailored to your quality definition and goals.…
Jul 2026 · argminai.com · its alternatives →
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Hi HN, I was once given the advice: Don't waste expensive frontier model credits (GPT/Claude/etc.) on bulk work. Send the boring, repetitive, high-volume jobs to a smaller model, and save the expensive prompts for when you actually need frontier-level reasoning. I complained and told my manager that I shouldnt have to think about using certain models for certain coding tasks, and that one model should handle everything. Well, here we are anyway. If anyone needs a place to absolutely abuse an LLM with high-volume tasks, come beat ours up at https://yolo-auto.com. Here are…
Jul 2026 · yolo-auto.com · its alternatives →
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Cut LLM token costs 40-70% with offline prompt compression
Jul 2026 · llmslim.app · its alternatives →
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Cut LLM costs. Free audit, pay only if it works.
Jun 2026 · decomp-ai.vercel.app · its alternatives →
- 23RC
Hello HN! We're building a caching solution for LLMs (ChatGPT, Claude). By combining cutting-edge approaches, such as edge computing, prompt compression, vectorization, and others - it can reduce your AI bills by up to 10x and significantly lower response times. Key Features: - cost efficiency: our system stores frequent queries, reducing the number of upstream (paid) API calls - fast responses: with various nodes globally, we reduce latency by serving data from the nearest location - scalability: designed to handle increasing loads and data sizes without degrading performance. The cache…
2024 · edgematic.dev · its alternatives →
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Intelligently cut token costs by 80% in AI context workflows
2025 · image-optimizer.app · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →