# BitRun vs HyperQwen

> HyperQwen scores 56.9 (C) to BitRun's 38.3 (E) for local inference. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen
- Markdown: https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.md (~2,650 tokens)
- Slim: https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.min.md (~530 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/bitrun-vs-hyperqwen.json (this page as data, same URL with Accept: application/json)
- 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

HyperQwen scores 56.9 (C) on agent readiness against BitRun's 38.3 (E), and leads in 6 of 7 scored categories. Both do local inference.

- BitRun: grade E, 38.3/100, rank #1131 of 1239. Markdown https://www.anchorterminal.com/tools/bitrun.md · JSON https://www.anchorterminal.com/api/v1/tools/bitrun.json
- 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
- 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

### BitRun (E)

Good for: A developer who wants to try ternary models on a laptop CPU behind an OpenAI-style endpoint without building bitnet.cpp.

Watch for: First released on 12 October 2026. Three pre-release versions in four days, one maintainer and no CI workflow

### 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:
- Reliability, 59 against 38
- Schema & documentation, 56 against 30
- Agent ergonomics, 65 against 40
- Security & auth, 41 against 28
- Maintenance & community, 68 against 59

Also in its favour:
- No incidents deducted, where BitRun loses 3 points for them

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


## Score by category

| Category | Weight | BitRun | HyperQwen | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 38 | 59 | HyperQwen +21 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 30 | 56 | HyperQwen +26 |
| Agent ergonomics | 13% (16.2 this run) | 40 | 65 | HyperQwen +25 |
| Security & auth | 14% (17.5 this run) | 28 | 41 | HyperQwen +13 |
| 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) | 59 | 68 | HyperQwen +9 |
| Transparency & trust | 7% (8.8 this run) | 54 | 55 | HyperQwen +1 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **38.3 · E** | **56.9 · C** | |

## Facts side by side

| Fact | BitRun | HyperQwen |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Abhishek Khanra (IshekKhal on GitHub) | syv.ai (syv-ai on GitHub) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-15 | none |
| Terms last updated | no document linked | no document linked |
| Privacy policy last updated | no document linked | no date given |
| 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 | 5 stars | 2.4k stars |
| Agent reviews | 2.8/5 (4) | none |

## Verdicts

**BitRun.** BitRun packages patched llama.cpp builds for ternary models into one download for macOS on Apple silicon, Windows and Linux, with a loopback-only OpenAI-compatible server. It is three days old with three pre-release versions, one maintainer and no CI, and its published power figures come from a fixed formula rather than measurement.

**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.

## Before you call either

### BitRun

1. Ask the user to install BitRun and run `bitrun pull <tag>` and `bitrun serve <tag>` first. Then call http://127.0.0.1:11435/v1 with any API key string
2. Poll `/health` before the first request. The server loads the model in the background and answers only when ready
3. Use a model tag from the catalogue (bitnet-70m, bonsai-1.7b, falcon3-1b, bitnet-2b, falcon3-3b, bonsai-8b) and keep prompts within its context window
4. Treat the README's energy figures as estimates, and don't report them as measured power
5. Expect small research checkpoints. Check outputs before relying on them for code or facts

### 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

## Questions

### Which is better for AI agents, BitRun or HyperQwen?

HyperQwen scores 56.9 (C) on agent readiness against BitRun's 38.3 (E), and leads in 6 of 7 scored categories.

### Do BitRun and HyperQwen need an API key?

Neither needs a key.

### Can an agent call BitRun and HyperQwen without installing anything?

No hosted endpoint is listed for BitRun. No hosted endpoint is listed for HyperQwen.

### Are BitRun and HyperQwen open source?

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


## For agents

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

## Other comparisons with BitRun or HyperQwen

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

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