Nemotron 3 Nano · Nebius Token Factory

CacheForge

Context Compactor for Coding Agents

Coding agents re-send every test log on every turn. CacheForge condenses them before they reach the model.

more agent sessions per dollar

That tower is one real test log. Scroll.

Scroll

One real test run ·

characters

The tower is that log, lines. CacheForge keeps what an agent needs to fix a failing test and drops the passing-test noise. It sent lines, characters.

failures, kept kept verbatim dropped

Every kept line is copied verbatim, and a few summary lines are added on top. It's plain code, not another model call, so it can't invent a test result.


      

The same session, every request

Without it, every turn re-sends the whole history.

Each tower is one request to Nemotron 3 Nano, drawn to the same scale. Amber is the agent alone; cyan is the same task through CacheForge.

Without
largest request (tokens)
turns · bugs fixed
With CacheForge
largest request (tokens)
turns · bugs fixed

One session (). The full record is below.

Every Token Factory run

more agent sessions per dollar, in every pre-registered run.

comparisons of 15 paired sessions, with the metric and test written down before each run.

lower cost per session
CacheForge sessions ran out of context, against without it
on bugs fixed: no consistent change. The claim is cost, not quality.
RunTaskCondenserPrompt tokensCost / sessionSessions / $Bugs fixed

Nemotron 3 Nano on Nebius Token Factory, full 262,144-token context, list price. Bugs fixed is without → with CacheForge over 15 sessions; p is a two-sided paired exact permutation test. “Rescored” means sessions were re-checked by replaying their saved code changes against the original tests.

How it works

Change one setting: the base URL.

Your agent
Any coding agent
OpenAI-compatible client. Same tools, same prompts.
→
Gateway
CacheForge
Condenses tool output. Your prompts and the model's replies pass through byte for byte.
→
Model
Nemotron 3 Nano
On Nebius Token Factory, with native tool calling.

Keeps what matters

Pass and fail counts per file, each failing test's assertion and error, the setup lines it depends on, and file and line.

Never rewrites you

System prompts, your messages, the model's replies and file reads are never touched.

Deterministic

No extra model call. Every kept line is copied verbatim, so it can't hallucinate a test result.

Get the code python -m src.tui replay

The terminal app replays every recorded session, raw log next to what the model saw. It needs no API key.