Stop sending every request to your most expensive model

A 500-word essay and a one-line sentiment check should not cost the same. Here's how to stop overpaying.

# Hard reasoning → flagship
curl https://aibridge-api.com/v1/chat/completions \
  -H "Authorization: Bearer mb-xxxxxxxx" \
  -d '{"model":"deepseek-v4-pro","messages":[{"role":"user","content":"Compare merge sort and quicksort, then prove the worst-case complexity."}]}'

# Trivial classification → flash
curl https://aibridge-api.com/v1/chat/completions \
  -H "Authorization: Bearer mb-xxxxxxxx" \
  -d '{"model":"glm-4-flash","messages":[{"role":"user","content":"Sentiment of: \"The checkout button is broken.\" — positive or negative?"}]}'

Same endpoint. Same SDK. Two wildly different jobs, two different models. That's the whole idea.

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The default mistake

Most developers pick one flagship model and route everything through it. A support-ticket classifier, a JSON validator, a title generator — all burning flagship tokens.

That's like taking an Uber Black to grab milk from the corner store. It works, but you're paying first-class prices for a two-minute errand.

Match the model to the job

AIBridge puts 15 models across 4 vendors behind one endpoint, so you can grade your workload instead of brute-forcing it:

If you're doing…	Use…	Why
Complex reasoning, math, logic	deepseek-reasoner / deepseek-v4-pro	Chain-of-thought, top-tier
Code generation & debugging	deepseek-coder	Purpose-built for code
High-volume, low-stakes tasks	glm-4-flash / deepseek-v4-flash	Fast, cost-effective
Multilingual or long context	qwen-plus (131K)	Cheap and long
Flagship Qwen performance	qwen3-235b-a22b	Best overall Qwen3
1M-token documents	kimi-k3	Million-token context, always-on reasoning
Advanced reasoning / complex tasks	glm-4-plus	GLM's heavy hitter

The full lineup also includes deepseek-chat, qwen-max, glm-4-air, and the moonshot-v1 family (8K / 32K / 128K). Something for every cost point and every context window.

What this looks like in practice

A typical mixed workload — say, an AI writing assistant — might route like this:

• Brainstorming & outlining → deepseek-v4-pro
• Draft expansion → qwen-plus
• Grammar & tone fixes → glm-4-flash
• Summarizing a 100K-token PDF → kimi-k3

You pick the model per call. It's a one-field change, not a refactor, so you can tune your cost/quality curve continuously instead of living with a single blunt instrument.

The numbers

• Free tier: 500K tokens/month (weighted) — test all 15 models
• Pro: $9.90/month for 5M tokens
• Top-ups: 1M / $2.99 · 5M / $9.90 · 20M / $29.90 (one-time, never expire)

One key, one predictable bill — no per-model price matrix to reverse-engineer.

Everything else you get

• Playground — try any model in the browser before wiring it up
• Usage dashboard — real-time token & cost tracking with a usage bar
• Prompt library — save your best prompts and reuse them
• GitHub OAuth — one-click sign-in
• Per-token atomic quota + rate limiting — so a runaway loop can't surprise you

The takeaway

You don't have a "model problem." You have a routing problem. The fix isn't a bigger model — it's the freedom to pick the right one for every single call.

Try all 15 models free, no credit card.

→ aibridge-api.com · [e-mail]