PostTrainBench vs teaql-agent-kit
teaql-agent-kit is much bigger: 2.8k stars against 546. Over the days we have tracked them PostTrainBench moved +55.6% and teaql-agent-kit +1.2%, so PostTrainBench is growing faster right now.
PostTrainBench leads on context depth and model freedom. teaql-agent-kit does not take any axis by a clear margin.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Measures autonomous CLI agents' ability to post-train base LLMs within a 10‑hour H100 budget, evaluating agent-driven R&D rather than only inference.
- Stars
- 546
- Tracked growth
- +55.6%
- Maturity
- ●●●●●
- Last commit
- 2d ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API keys + H100 GPU (cluster or rented)
Provides a TEAQL-focused, auditable evaluation harness that measures software-engineering discipline and token-efficiency for coding agents rather than offering general-purpose agent automation.
- Stars
- 2.8k
- Tracked growth
- +1.2%
- Maturity
- ●●●●●
- Last commit
- 2d ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API key or model costs may apply
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | PostTrainBench | teaql-agent-kit |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Whole-repo access | ●●●●● Diff + related files |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Judge + rules | ●●●●● Guides & checkpoints |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Configurable CLI options | ●●●●● Config & prompts |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● APIs with your key | ●●●●● Cloud via API key |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● BYO key + local models | ●●●●● Single fixed provider |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Container + cluster setup | ●●●●● Manual setup |
Which one to pick
Pick PostTrainBench if…
Autonomy-focused — use this to benchmark end-to-end agent-driven post-training of base models on an H100 with built-in evaluation tasks and reward‑hacking mitigations.
- Context depth: Whole-repo access (5/5 against 3/5)
- Model freedom: BYO key + local models (5/5 against 1/5)
Pick teaql-agent-kit if…
Evaluation-first — pick this when you need reproducible, auditable benchmarks of coding agents working with TEAQL contracts, explicit guardrails, and token-efficiency measurement.
What people want from each one
aisa-group/PostTrainBench
Questions people ask
Is PostTrainBench better than teaql-agent-kit?
PostTrainBench leads on context depth and model freedom. teaql-agent-kit does not take any axis by a clear margin. PostTrainBench is worth picking when autonomy-focused — use this to benchmark end-to-end agent-driven post-training of base models on an H100 with built-in evaluation tasks and reward‑hacking mitigations.
Which of PostTrainBench and teaql-agent-kit keeps my code private?
PostTrainBench: APIs with your key (3/5). teaql-agent-kit: Cloud via API key (3/5).
What does each one cost to run?
PostTrainBench: Your API keys + H100 GPU (cluster or rented). teaql-agent-kit: Your API key or model costs may apply.
Full profiles: aisa-group/PostTrainBench and teaql/teaql-agent-kit. Everything else in Evals & benchmarks.