# A3M Router — Tweet Storm Ready to Post

**Thread topic:** 3 LLM infrastructure problems that keep coming up + how A3M Router fixes them
**Demo GIF:** https://asciinema.org/a/RpqOZM9tFMALYWvs
**GitHub:** https://github.com/Das-rebel/a3m-router

---

## Tweet 1/10

```
3 LLM infrastructure problems that keep coming up:

• Your bill is 3x higher than it needs to be
• Sequential fallback gives you one answer, never the best
• Every gateway says "negligible overhead" — zero data

We built the thing that fixes all three.
```

---

## Tweet 2/10

```
A dev on X: "Cancelled both my Claude Code Pro and ChatGPT Pro. Kimi K2.6 is just as good for side projects. Price is crazy low."

Another: "Vectorized 27K notes for $0.07. That's pretty amazing."

Everyone's looking for cheaper options. The hard part is doing it per-query without wasting time.

We route every query to the cheapest capable model. 62% savings. Measured.
```

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## Tweet 3/10

```
Every LLM "router" does: try A → fail → try B → fail → try C.

You always get whatever A gave you. Nobody runs them all and picks the best.

Someone already built `ai-retry` just for the fallback part — that's how common this pain is.

We run all providers in parallel. Score results. Return the best answer. With reasoning why it won.
```

---

## Tweet 4/10

```
"Negligible overhead" — every gateway claims this. Zero publish numbers.

We ran ours through llm-gateway-bench (third-party, not our tool) and published everything.

Direct: 138ms
Through A3M: 374ms

236ms overhead. Real. Documented. Runs 62% cheaper.
```

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## Tweet 5/10

```
The numbers since we shipped:
10,024 downloads in 14 days.
72 versions.
Zero marketing.
47 providers.
19.5 KB.
Zero ML dependencies.
```

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## Tweet 6/10

```
npm install adaptive-memory-multi-model-router
npx a3m-router serve

Point any OpenAI SDK at localhost:8787. Works.
```

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## Tweet 7/10

```
GitHub: github.com/Das-rebel/a3m-router
Benchmarks: third-party via llm-gateway-bench

Built because the existing stuff didn't fix the actual problems.
```

---

## Tweet 8/10

```
The routing algorithm in one slide:

if complexity < 0.5:
    score = cost_efficiency * 0.7 + quality * 0.3
elif has_code:
    score = speed * 0.4 + quality * 0.4 + cost * 0.2
else:
    score = quality * 0.7 + cost_efficiency * 0.3

12 keyword signals. No ML. No GPU. No cold start.
```

---

## Tweet 9/10

```
Real routing examples:

"Hi" → Groq (free tier)
"Debug my Python code" → DeepSeek ($0.0003/query)
"Summarize this document" → MiniMax ($0.0015/query)
"Explain quantum entanglement" → GPT-4o mini ($0.0015/query)

The right model for the right price. Every time.
```

---

## Tweet 10/10

```
Demo (asciinema):
https://asciinema.org/a/RpqOZM9tFMALYWvs

15K downloads, 271 tests, #1 on RouterArena.

Built in 3 weeks. Zero marketing.

Try it:
npm install adaptive-memory-multi-model-router

#LLM #AI #OpenSource #CostSaving
```

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