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pxpipe

Cut Claude Code's input tokens by rendering bulky context as images — the same system prompt, tool docs, and history, in a fraction of the tokens.

An image's token cost is fixed by its pixel dimensions, not by how much text is inside it. Dense content (code, JSON, tool output) packs ~3.1 chars per image-token vs ~1 char per text-token on real Claude Code traffic. The reader is the same vision channel that Anthropic's computer use already relies on for screenshots. pxpipe is a local proxy that uses that channel for context: it rewrites the bulky parts of each request into compact PNGs before it leaves your machine. At current Fable list prices that lands as a ~59–70% lower end-to-end bill — but prices move and workloads differ, so the durable number is the token cut itself, measured per-request against a free count_tokens counterfactual in ~/.pxpipe/events.jsonl.

This is what the model sees instead of text:

*~48k chars of system prompt + tool docs: ≈25k tokens as text, ≈2.7k image tokens as this page. Real pipeline output; the model reads renders like this at 100/100 (see benchmarks).*

![chart: characters a frontier context window holds, 2018–2026 — vendor text series including Grok 4.5; orange measured overlays are Fable 5 [1m] + pxpipe ~19.0M (4.8×) and Gemini 3.6 Flash + pxpipe ~21.3M (5.3×)](docs/assets/context-window-chars.png)

*Eight years of context growth, in characters. Every text line tops out near ~4M chars (a 1M-token window at ~4 chars/token); Grok 4.5 is shown as a text-window point only (500K). The orange overlays are the **same 1M windows read through pxpipe images — ~19.0M chars for Fable 5 (4.8×) and ~21.3M chars for Gemini 3.6 Flash (5.3×** text capacity). Density is measured from a live render at generation time, not hand-typed: regenerate with npx tsx scripts/gen-context-chart.ts (source).*

Demo

Fable 5 (the default, 100/100 reader) — plain left, pxpipe right:

https://github.com/user-attachments/assets/1c8ee63a-fcd7-4958-917b-da788d718349

pxpipe counts an exact token 10/10 across 39 imaged filler files (matches grep line-for-line), gets the multi-step ledger arithmetic right, and ends the session at $6.06 with context to spare (73.5k/1M) vs $42.21 at 96% full. One caveat visible in the clip: the pxpipe arm needed a nudge to match the requested one-line output format.

Try it (30 seconds)

Dashboard at : tokens saved, every text→image conversion side by side, kill switch, live model chips. Responses stream normally — pxpipe compresses the *request* only, never the model's output. Recent turns stay text; the system prompt, tool docs, and older bulk history are imaged.

pxpipe warp

Same thing without ANTHROPIC_BASE_URL, so /remote-control, claude.ai connectors, and first-party gates keep working. Full instructions in the dashboard.

api.anthropic.com/v1/messages is routed by default. Agents that reach their provider over some other base URL need a rule for it, and a rule that names a port matches only that port:

Offline export (no proxy)

You can render text, files, or diffs to PNG pages without running the proxy or connecting Claude Code:

If the package is installed, use pxpipe export instead of npx pxpipe-proxy export.

Each run writes a fresh pxpipe-export-XXXXXX/ output folder (the exact path is printed when the command finishes) containing page-*.png, factsheet.txt, manifest.json, and prompt.txt. Upload the PNG pages and paste the prompt into image-upload clients such as Cursor when you want dense visual context without running the proxy.

The honest part

• It is lossy. Exact 12-char hex strings in dense imaged content: 13/15 on Fable 5 and 0/15 on Sol — misses are *silent confabulations*, not errors. Byte-exact values (IDs, hashes, secrets) must stay text; recent turns do. The factsheet selectively preserves up to 96 recognized precision-critical tokens, not every identifier. A dedicated verbatim-risk guard is not built yet. • Escape hatch: subagents on non-allowlisted models pass through as text — route byte-exact work there (CLAUDE_CODE_SUBAGENT_MODEL=claude-sonnet-4-6, or model: sonnet in agent frontmatter). • Real work: SWE-bench Lite pilot 10/10 both arms at −65% request size; SWE-bench Pro 14/19 ON vs 15/19 OFF at −60%, verdicts agree 18/19, and the single split re-resolved 3/3 on replication — run-to-run variance, not compression. Small n; receipts in eval/. • Workload-dependent. Wins on token-dense content (~1 char/token), loses money on sparse prose (~3.5 chars/token); a profitability gate (calibrated on N=391 production rows) images only where the math wins. • Client-dependent. Savings track uncached bulk the client still re-sends as text. Claude Code re-sends system + tools + history on /anthropic/messages and typically lands ~60–70%. Details and measured splits: docs/CACHING_AND_SAVINGS.md.

Model support and rendering details…

Description from the npm listing.