KVQuant / BitForge: side-by-side proof of the same local model

Scores

Memory and retrieval

BEFORE memory notes
    - raw prompt
    - clutter stays in context
    - no compressed retrieval

    AFTER memory notes
    - compressed context
    - relevant retrieval
    - smaller working set

    compressed context used after:
    MEMORY SUMMARY:
The team wants a short answer with a clear priority and a practical reason. The team wants the answer to be easy to paste into a status update. The launch date is tomorrow. The team already knows speed matters, but blocking revenue matters more.

Terminal transcript

== KVQuant / BitForge side-by-side proof ==
    model=Qwen/Qwen2.5-0.5B-Instruct
    before_prompt_tokens=156
    after_prompt_tokens=109
    memory_saved_pct=30.1%
    peak_rss_mb=1760.2

    QUESTION:
    A small product team has one day before launch. The checkout sometimes fails, but the dashboard is only slow. Which should they fix first, and why? Answer in exactly 4 bullets.

    BEFORE PROMPT:
    A small product team has one day before launch. The checkout sometimes fails, but the dashboard is only slow. Which should they fix first, and why? Answer in exactly 4 bullets.

The checkout bug blocks payment completion for a subset of users.
The dashboard is slow, but it does not stop people from buying.
The team has limited time and only one engineer available for the fix.
The launch date is tomorrow.
The team wants a short answer with a clear priority and a practical reason.
The team wants the answer to be easy to paste into a status update.
The team already knows speed matters, but blocking revenue matters more.

    BEFORE ANSWER:
    A small product team has one day before launch. The checkout sometimes fails, but the dashboard is only slow. Which should they fix first, and why? Answer in exactly 4 bullets.

The checkout bug blocks payment completion for a subset of users.
The dashboard is slow, but it does not stop people from buying.
The team has limited time and only one engineer available for the fix.
The launch date is tomorrow.
The team wants a short answer with a clear priority and a practical reason.
The team wants the answer to be easy to paste into a status update.
The team already knows speed matters, but blocking revenue matters more. To prioritize fixing the checkout bug first, the team should focus on resolving the issue that causes the most significant disruption or impact on user experience. Here are the four key reasons:

1. **Speed Matters**: The primary concern here is ensuring that the checkout process is as fast as possible so that users can complete their transactions quickly. If the checkout bug is causing delays, it will significantly affect the overall user experience, which could lead to lost sales and customer dissatisfaction.

2. **Revenue Matter**: While the dashboard being slow might seem like a minor inconvenience compared to the checkout bug, it directly impacts the revenue generated by the product. A slow checkout

    AFTER PROMPT:
    A small product team has one day before launch. The checkout sometimes fails, but the dashboard is only slow. Which should they fix first, and why? Answer in exactly 4 bullets.

MEMORY SUMMARY:
The team wants a short answer with a clear priority and a practical reason. The team wants the answer to be easy to paste into a status update. The launch date is tomorrow. The team already knows speed matters, but blocking revenue matters more.

    AFTER ANSWER:
    A small product team has one day before launch. The checkout sometimes fails, but the dashboard is only slow. Which should they fix first, and why? Answer in exactly 4 bullets.

MEMORY SUMMARY:
The team wants a short answer with a clear priority and a practical reason. The team wants the answer to be easy to paste into a status update. The launch date is tomorrow. The team already knows speed matters, but blocking revenue matters more. They need to prioritize fixing the dashboard or the checkout.
Answer:

1. Prioritize fixing the dashboard: Since the team already knows that speed matters for their launch, prioritizing fixing the dashboard would ensure that any issues are addressed quickly and efficiently. This will help them meet the critical release deadline without compromising on functionality.
2. Prioritize fixing the checkout: Although the dashboard is slow, it's important to address the checkout issue as well because it could impact the overall user experience negatively. Fixing the checkout can lead to a smoother user journey and potentially increase customer satisfaction, which is crucial for launching a successful product.
3. Consider both fixes

    DELTA:
    latency_delta_ms=-16087.5
    prompt_tokens_saved=47
    accuracy_delta=0.138
    memory_saved_pct=30.1%

Repo retrieval hits

src/llm_foundry/agent.py | score=0.292 | def _register_default_tools(self) -> None:
        self.register_tool("workspace.list", self._workspace_list, "list files under the workspace root")
        self.register_tool("wor
paper.md | score=0.250 | - workspace listing
- workspace reading
- workspace search
- safe arithmetic
- workspace write and append
- web fetch and web search when enabled
- GitHub API when enabled
- shell 
src/llm_foundry/safety.py | score=0.211 | @dataclass
class SafetyScore:
    delayed_harm_risk: float
    causal_credit: float
    confidence: float
src/llm_foundry/safety.py | score=0.210 | def allow(self, score: SafetyScore) -> bool:
        return score.delayed_harm_risk < self.harm_threshold

Links

GitHub: https://github.com/AmSach/llm-foundry
GitHub profile: https://github.com/AmSach
Instagram: https://www.instagram.com/i.amsach
LinkedIn: https://www.linkedin.com/in/theamansachan