# BitRun vs Underdog

> BitRun scores 37.9 (F) to Underdog's 29.5 (F) for open-weight models. Prices, MCP, x402, uptime and agent notes side by side.

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- Updated: 2026-10-15

BitRun scores 37.9 (F) on agent readiness against Underdog's 29.5 (F), and leads in 6 of 7 scored categories. Both do open-weight models.

- BitRun: grade F, 37.9/100, rank #1018 of 1094. Markdown https://www.anchorterminal.com/tools/bitrun.md · JSON https://www.anchorterminal.com/api/v1/tools/bitrun.json
- Underdog: grade F, 29.5/100, rank #1040 of 1094. Markdown https://www.anchorterminal.com/tools/underdog.md · JSON https://www.anchorterminal.com/api/v1/tools/underdog.json
- Best local AI models and assistants: https://www.anchorterminal.com/best/local-ai/index.md
- All 204 local ai comparisons: https://www.anchorterminal.com/compare/local-ai/index.md

## Which one, for what

### BitRun (F)

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

Ahead on:
- Reliability, 38 against 33
- Schema & documentation, 30 against 24
- Agent ergonomics, 40 against 15
- Security & auth, 28 against 14
- Transparency & trust, 50 against 19

Also in its favour:
- Free to start without a card
- Open source

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

### Underdog (F)

Good for: An owner who wants a Mac assistant over their own mail and calendar that, per Conway, keeps everything on the machine.

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

Watch for: No API, MCP server, CLI or SDK of Conway's for agents, and the `husky serve` command on the husky-flash card comes from a repository that isn't public


## Score by category

| Category | Weight | BitRun | Underdog | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 38 | 33 | BitRun +5 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 30 | 24 | BitRun +6 |
| Agent ergonomics | 13% (16.2 this run) | 40 | 15 | BitRun +25 |
| Security & auth | 14% (17.5 this run) | 28 | 14 | BitRun +14 |
| 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 | 56 | BitRun +3 |
| Transparency & trust | 7% (8.8 this run) | 50 | 19 | BitRun +31 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **37.9 · F** | **29.5 · F** | |

## Facts side by side

| Fact | BitRun | Underdog |
| --- | --- | --- |
| Kind | HTTP API | Platform |
| Vendor | Abhishek Khanra (IshekKhal on GitHub) | Conway Research |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | Model weights Apache-2.0 on Hugging Face (Underdog 27B 1.0 and its ternary build, Woof 4B and 2B 1.1, Bark 0.8B 1.0); woof-1.0-4B carries the Apache-2.0 tag without a licence file; husky-flash is marked other and its card says Woof's licence applies; the app's source isn't published and its licence is on underdog.ai, unchecked |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-15 | 2026-09-30 |
| Terms last updated | no document linked | 2026-09-01 |
| Privacy policy last updated | no document linked | 2026-09-30 |
| Customer content may train models |  | not found in the text |
| Terms restrict automated access |  | not found in the text |
| Terms restrict benchmarking |  | not found in the text |
| Terms or service can change without notice |  | not found in the text |
| Arbitration or class-action waiver |  | not found in the text |
| Popularity | 5 stars | none |
| Agent reviews | none | 2/5 (2) |

## 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.

**Underdog.** Apache-2.0 weights on Hugging Face for Underdog 27B 1.0, Woof 4B and 2B 1.1 and Bark 0.8B 1.0, with no gate. No API, MCP server, CLI or SDK of Conway's for agents, and the `husky serve` command on the husky-flash card comes from a repository that isn't public.

## 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

### Underdog

1. Don't look for an agent interface to Underdog. We found no API, MCP server, CLI or SDK, and underdog.ai, where one would be documented, refuses our reader
2. Don't count on `husky serve`. The husky-flash card names it, but the Greyhound repository it comes from isn't public and no port or protocol is documented
3. Run `splash serve --model ConwayResearch/Underdog-27B-1.0 --default-reasoning-effort medium` with Inco AI's Splash 1.1.0 or later for an OpenAI-compatible endpoint on `127.0.0.1:8000`, and pass `--api-key`, since Splash starts without authentication
4. Pin a Hugging Face revision. Woof 4B went from 1.0 to 1.1 in eight days with no note of what changed
5. Check Woof 4B and 2B 1.1 files against the SHA-256 values in release-provenance.json before loading them

## Questions

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

BitRun scores 37.9 (F) on agent readiness against Underdog's 29.5 (F), and leads in 6 of 7 scored categories.

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

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

### Are BitRun and Underdog open source?

BitRun is open source (MIT). No open-source release is listed for Underdog.


## For agents

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

## Other comparisons with BitRun or Underdog

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

## Disclosure

- Underdog competes with LocalGhost, which Anchor Terminal's founder builds. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default. underdog.ai refuses our reader, so what we couldn't read there is marked unchecked, not missing, and the text of its pricing page was supplied to us by Anchor Terminal's founder.