# HyperQwen vs llama.cpp

> llama.cpp scores 60.6 (C) to HyperQwen's 56.9 (C) for local inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp
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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-30

llama.cpp scores 60.6 (C) on agent readiness against HyperQwen's 56.9 (C), and leads in 5 of 7 scored categories. HyperQwen leads on schema & documentation. Both do local inference.

- HyperQwen: grade C, 56.9/100, rank #738 of 1239. Markdown https://www.anchorterminal.com/tools/hyperqwen.md · JSON https://www.anchorterminal.com/api/v1/tools/hyperqwen.json
- llama.cpp: grade C, 60.6/100, rank #590 of 1239. Markdown https://www.anchorterminal.com/tools/llama-cpp.md · JSON https://www.anchorterminal.com/api/v1/tools/llama-cpp.json
- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md
- All 253 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md

## Which one, for what

### HyperQwen (C)

Good for: An operator with one 24 GB NVIDIA card who wants Qwen3.8-27B behind an OpenAI-compatible endpoint for a coding or tool-calling agent, with long context.

Ahead on:
- Schema & documentation, 56 against 47

Watch for: Serves Qwen3.8-27B and checkpoints derived from it only. Other models are on the roadmap

### llama.cpp (C)

Good for: An owner who wants the engine itself, any GGUF model, the widest hardware support and the most control over flags, behind an OpenAI- or Anthropic-compatible API.

Ahead on:
- Reliability, 64 against 59
- Agent ergonomics, 73 against 65
- Security & auth, 52 against 41
- Maintenance & community, 81 against 68
- Transparency & trust, 64 against 55

Watch for: API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost


## Score by category

| Category | Weight | HyperQwen | llama.cpp | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 59 | 64 | llama.cpp +5 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 56 | 47 | HyperQwen +9 |
| Agent ergonomics | 13% (16.2 this run) | 65 | 73 | llama.cpp +8 |
| Security & auth | 14% (17.5 this run) | 41 | 52 | llama.cpp +11 |
| Payments & pricing | 10% (12.5 this run) | 60 | 60 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 68 | 81 | llama.cpp +13 |
| Transparency & trust | 7% (8.8 this run) | 55 | 64 | llama.cpp +9 |
| Negative events | ≤15 | 0 | -1 | |
| **Total** | | **56.9 · C** | **60.6 · C** | |

## Facts side by side

| Fact | HyperQwen | llama.cpp |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | syv.ai (syv-ai on GitHub) | ggml.ai (Hugging Face) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | MIT |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | none | 2026-09-23 |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no date given | no document linked |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Popularity | 2.4k stars | 130k stars |
| Agent reviews | none | 2.5/5 (2) |

## Verdicts

**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.

**llama.cpp.** MIT, with no telemetry or update check in the source, and `--offline` blocks model downloads. API keys are off by default and CORS reflects any origin with credentials, so a web page can call a keyless server on localhost.

## Before you call either

### 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

### llama.cpp

1. Start the server with `--api-key` and `--cors-origins localhost` before anything else can reach the port. Both are off by default
2. Pass `n_predict` or `max_tokens`. Generation is unbounded by default
3. Send `response_fields` to /completion to drop the fields you don't read
4. Wait and retry on a 503 `unavailable_error`. The model is still loading
5. Read the server README of the build you run. Behaviour changes between nightly builds without a changelog entry

## Questions

### Which is better for AI agents, HyperQwen or llama.cpp?

llama.cpp scores 60.6 (C) on agent readiness against HyperQwen's 56.9 (C), and leads in 5 of 7 scored categories. HyperQwen leads on schema & documentation.

### Do HyperQwen and llama.cpp need an API key?

Neither needs a key.

### Can an agent call HyperQwen and llama.cpp without installing anything?

No hosted endpoint is listed for HyperQwen. No hosted endpoint is listed for llama.cpp.

### Are HyperQwen and llama.cpp open source?

Yes. HyperQwen is open source (Apache-2.0). llama.cpp is open source (MIT).


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hyperqwen-vs-llama-cpp.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "hyperqwen", "b": "llama-cpp"}`. From a terminal: `anchor compare hyperqwen llama-cpp`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hyperqwen.json and https://www.anchorterminal.com/api/v1/tools/llama-cpp.json

## Other comparisons with HyperQwen or llama.cpp

- [AnythingLLM vs HyperQwen](https://www.anchorterminal.com/compare/anythingllm-vs-hyperqwen.md)
- [AnythingLLM vs llama.cpp](https://www.anchorterminal.com/compare/anythingllm-vs-llama-cpp.md)
- [Berth vs HyperQwen](https://www.anchorterminal.com/compare/berth-vs-hyperqwen.md)
- [Berth vs llama.cpp](https://www.anchorterminal.com/compare/berth-vs-llama-cpp.md)
- [BitRun vs HyperQwen](https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.md)
- [BitRun vs llama.cpp](https://www.anchorterminal.com/compare/bitrun-vs-llama-cpp.md)
- [Docker Model Runner vs HyperQwen](https://www.anchorterminal.com/compare/docker-model-runner-vs-hyperqwen.md)
- [Docker Model Runner vs llama.cpp](https://www.anchorterminal.com/compare/docker-model-runner-vs-llama-cpp.md)
- [Foundry Local vs HyperQwen](https://www.anchorterminal.com/compare/foundry-local-vs-hyperqwen.md)
- [Foundry Local vs llama.cpp](https://www.anchorterminal.com/compare/foundry-local-vs-llama-cpp.md)
- [Core vs HyperQwen](https://www.anchorterminal.com/compare/ghost-core-vs-hyperqwen.md)
- [Core vs llama.cpp](https://www.anchorterminal.com/compare/ghost-core-vs-llama-cpp.md)
- [GPT4All vs HyperQwen](https://www.anchorterminal.com/compare/gpt4all-vs-hyperqwen.md)
- [GPT4All vs llama.cpp](https://www.anchorterminal.com/compare/gpt4all-vs-llama-cpp.md)
- [HyperQwen vs Jan](https://www.anchorterminal.com/compare/hyperqwen-vs-jan.md)
- [HyperQwen vs Khoj](https://www.anchorterminal.com/compare/hyperqwen-vs-khoj.md)
- [HyperQwen vs KoboldCpp](https://www.anchorterminal.com/compare/hyperqwen-vs-koboldcpp.md)
- [HyperQwen vs Lemonade](https://www.anchorterminal.com/compare/hyperqwen-vs-lemonade.md)
- [HyperQwen vs LM Studio](https://www.anchorterminal.com/compare/hyperqwen-vs-lm-studio.md)
- [HyperQwen vs LocalAI](https://www.anchorterminal.com/compare/hyperqwen-vs-localai.md)
- [HyperQwen vs MLX LM](https://www.anchorterminal.com/compare/hyperqwen-vs-mlx-lm.md)
- [HyperQwen vs Ollama](https://www.anchorterminal.com/compare/hyperqwen-vs-ollama.md)
- [HyperQwen vs Open WebUI](https://www.anchorterminal.com/compare/hyperqwen-vs-open-webui.md)
- [HyperQwen vs screenpipe](https://www.anchorterminal.com/compare/hyperqwen-vs-screenpipe.md)
- [HyperQwen vs TextGen](https://www.anchorterminal.com/compare/hyperqwen-vs-text-generation-webui.md)
- [HyperQwen vs vLLM](https://www.anchorterminal.com/compare/hyperqwen-vs-vllm.md)
- [Jan vs llama.cpp](https://www.anchorterminal.com/compare/jan-vs-llama-cpp.md)
- [Khoj vs llama.cpp](https://www.anchorterminal.com/compare/khoj-vs-llama-cpp.md)
- [KoboldCpp vs llama.cpp](https://www.anchorterminal.com/compare/koboldcpp-vs-llama-cpp.md)
- [Lemonade vs llama.cpp](https://www.anchorterminal.com/compare/lemonade-vs-llama-cpp.md)
- [llama.cpp vs LM Studio](https://www.anchorterminal.com/compare/llama-cpp-vs-lm-studio.md)
- [llama.cpp vs LocalAI](https://www.anchorterminal.com/compare/llama-cpp-vs-localai.md)
- [llama.cpp vs MLX LM](https://www.anchorterminal.com/compare/llama-cpp-vs-mlx-lm.md)
- [llama.cpp vs Ollama](https://www.anchorterminal.com/compare/llama-cpp-vs-ollama.md)
- [llama.cpp vs Open WebUI](https://www.anchorterminal.com/compare/llama-cpp-vs-open-webui.md)
- [llama.cpp vs screenpipe](https://www.anchorterminal.com/compare/llama-cpp-vs-screenpipe.md)
- [llama.cpp vs TextGen](https://www.anchorterminal.com/compare/llama-cpp-vs-text-generation-webui.md)
- [llama.cpp vs vLLM](https://www.anchorterminal.com/compare/llama-cpp-vs-vllm.md)
- [HyperQwen vs Underdog](https://www.anchorterminal.com/compare/hyperqwen-vs-underdog.md)
- [llama.cpp vs Underdog](https://www.anchorterminal.com/compare/llama-cpp-vs-underdog.md)

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