If you are comparing Crazyrouter vs Vercel AI Gateway, the real question is not which homepage sounds better. The practical question is: which gateway fits your production workflow, model coverage, pricing expectations, deployment stack and migration path?
Vercel AI Gateway is attractive for teams already building on Vercel and the AI SDK. Crazyrouter is attractive for teams that want broad model access, OpenAI-compatible routing and a gateway that is not tied to one frontend hosting platform.
Use Vercel AI Gateway when your app is already deeply built around Vercel, the Vercel AI SDK, and you want a framework-native gateway experience.
Use Crazyrouter when your priority is broad model families, one OpenAI-compatible base URL, model experimentation across GPT, Claude, Gemini, Qwen, DeepSeek, GLM, image and video routes, and a gateway layer that can be used from any backend.
Real test evidence used in this article:
Sample model families discovered by /v1/models:
deepseek-v4-flash, deepseek-v4-proqwen3-vl-plus, qwen2.5-coder-14b-instruct, qwen2-vl-72b-instruct, qwen3-coder-480b-a35b-instruct, qwen3-vl-30b-a3b-instruct, qwen3-30b-a3b, qwen-plus, qwen2.5-72b-instructglm-5v-turbo, glm-4-flash, glm-4.1v-thinking-flash, glm-5-turbo, glm-5, glm-4.5-flash, glm-4.5, glm-4vThis matters because gateway comparison should not stop at feature tables. A gateway has to list models, accept real payloads, return usage data and let developers switch model IDs without rewriting the app.
Do not compare only the marketing plan price. For an AI gateway, compare:
Vercel AI Gateway is easiest to evaluate inside a Vercel stack. Crazyrouter is easiest to evaluate as an OpenAI-compatible API endpoint:
Crazyrouter returned 262 models in this test, including GPT, Claude, Gemini, Qwen, DeepSeek, GLM, Kimi, image-generation and video-generation routes.
A practical routing map:
| Workload | Gateway requirement | Why it matters |
|---|---|---|
| SaaS chatbot | cheap fast model + fallback | reduce cost per conversation |
| Coding agent | stronger reasoning/coding route | code quality varies by task |
| RAG app | stable JSON + long context | retrieval output must be validated |
| Image/video product | multimodal model access | text-only gateways are not enough |
| Internal automation | logs, usage and model switching | operations teams need visibility |
| Tested model | HTTP | Latency | Prompt tokens | Completion tokens | Total tokens | Note |
|---|---|---|---|---|---|---|
gpt-4o-mini | 200 | 2.9s | 39 | 53 | 92 | stop |
qwen-plus | 200 | 3.69s | 40 | 42 | 82 | stop |
glm-4-flash | 200 | 5.54s | 34 | 47 | 81 | stop |
deepseek-chat | 200 | 3.27s | 36 | 180 | 216 | returned reasoning tokens, empty content at max_tokens=180; useful validation/fallback example |
qwen3-coder-480b-a35b-instruct | 200 | 28.53s | 40 | 47 | 87 | stop |
The DeepSeek route example is especially useful: HTTP 200 does not automatically mean usable final content. It returned reasoning tokens and hit the output limit with empty final content under this constrained prompt. Production gateways need validators, fallbacks and task-specific max token settings.
| Dimension | Crazyrouter | Vercel AI Gateway |
|---|---|---|
| Best fit | Multi-model API access from any stack | Vercel-native AI SDK apps |
| Migration style | OpenAI-compatible base URL | Vercel AI SDK/provider integration |
| Model strategy | Broad model families and multimodal routes | Gateway inside Vercel ecosystem |
| Lock-in risk | Lower if you keep OpenAI-compatible client code | Higher if app logic is Vercel-specific |
| Use case | API gateway, routing, model choice, cost control | frontend/serverless AI app delivery |
| Evaluation metric | cost per successful task | convenience inside Vercel workflow |
Vercel AI Gateway can be a good fit when:
Crazyrouter is a stronger fit when:
Yes, for teams that mainly want unified model access and OpenAI-compatible API routing. It is not a Vercel hosting replacement; it is an AI API gateway.
Often yes, especially if your app is already built around Vercel and the Vercel AI SDK. But if model coverage and cross-stack portability matter more, Crazyrouter is worth testing.
The answer depends on your model routes, retries, failed outputs and traffic profile. Compare cost per successful task, not only nominal token price.
Yes. A Vercel app can call Crazyrouter through the OpenAI SDK by setting base_url to https://cn.crazyrouter.com/v1.
Vercel AI Gateway is framework-native. Crazyrouter is model-access-native. If your main problem is building a Vercel AI SDK app, evaluate Vercel first. If your main problem is routing across many model families with one OpenAI-compatible API, test Crazyrouter.
Start here: Crazyrouter
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