HyperQwen vs TextGen

HyperQwen

HyperQwen packages a patched vLLM 0.32.0 and requantised Qwen3.8-27B weights into one container with tool calling preset and a loopback bind when no key is set. It runs one model family, its speed figures come from one RTX 3090, and it has no versioned releases, changelog or security policy.

TextGen

AGPL-3.0 with no telemetry, and a local API on 127.0.0.1:5000 that checks the Host header, limits CORS to localhost and separates an admin key from the caller's key. No release since v4.9 on 20 May 2026, no code commits since 31 May, no test suite, and ten security advisories in the year, all fixed.

HyperQwen

1. Call http://127.0.0.1:18020/v1 with model qwen3.8-27b and the VLLM_API_KEY value, or any string if no key was set
2. Poll /health before the first request. A first start downloads and prepares the model and compiles kernels, which can take over 30 minutes
3. Declare the context window your setup uses (65,536 by default, 131,072 for CTX=long, 245,760 for CTX=huge) so the client doesn't truncate
4. Ask the owner to set VLLM_API_KEY before setting BIND=0.0.0.0, and to front the port with a proxy that allowlists routes
5. Treat the README's tokens-per-second figures as the project's measurements on one RTX 3090 at 250 W

TextGen

1. Ask the owner to launch with --api. Nothing listens on port 5000 without it, and a model must be loaded first
2. Call http://127.0.0.1:5000/v1. Any Host header other than localhost or 127.0.0.1 gets 400 Invalid host header unless --listen is set
3. Send the key as Authorization: Bearer on OpenAI routes and as x-api-key on /v1/messages. Model loading needs the admin key
4. Read http://127.0.0.1:5000/docs or modules/api/typing.py for parameters. max_tokens defaults to 512 on chat completions
5. Run tool calls yourself. The API returns finish_reason: "tool_calls" and executes nothing on the server
6. Use the repository name oobabooga/textgen. The old text-generation-webui URL redirects