AWS Lambda: prompt compression in one line
The static prefix is formatted for the provider cache (Anthropic breakpoints, OpenAI prompt_cache_key or 12h retention) and tool schemas are minified losslessly before they are sent. Here is the change for AWS Lambda, the switch that turns it on, and the arithmetic on claude-sonnet-5-5.
AWS Lambda reaches TokenZero with one base-URL argument and keeps your anthropic key. On claude-sonnet-5-5 a cached input token costs $0.100 per million instead of $2.00, so 100,000 calls with a 1,500-token static prefix drop from $700 to $415 a month, 41% less, before any routing. Gateway overhead is 1.52 ms at p50, measured; every call returns an Ed25519-signed receipt.
· Source: pricing table 2026-10-26; overhead from the published benchmark on /benchmarks
At a glance
- Framework
- AWS Lambda (Python)
- Capability
- prompt compression
- Change
- handler.py: base URL argument
- Request shape
- Anthropic Messages
- Turn it on
- X-TokenZero-Cache-Strategy: static
- Workspace setting
- cache_strategy: static, prompt_cache_ttl: 1h
- Reference model
- claude-sonnet-5-5 ($2.00 in / $10.00 out per 1M, table 2026-10-26)
- Cache-formatting saving on the reference workload
- $285/month (41%) (computed)
- Gateway overhead (measured)
- 1.52 ms p50, 3.42 ms p95
- Parity floor
- 99.8%
- Free tier
- $500/month routed spend
Reference workload on claude-sonnet-5-5: 2,000 input (1,500 static) / 300 output tokens, 100,000 calls per month, table 2026-10-26
| Scenario | Per call | Per month | Delta |
|---|---|---|---|
| List price, no gateway | $0.00700 | $700 | — |
| Static prefix cached (prompt compression) | $0.00415 | $415 | $285 (41%) |
| 20% exact-cache repeats | $0.00560 | $560 | $140 (20%) |
| All calls cascaded to claude-haiku-5-5 | $0.00035 | $35 | $665 (95%) |
| Budget guardrail at $500/month | — | capped at $500.00 | 402 after 71,428 calls |
The change
1. Point AWS Lambda at the gateway (handler.py):
-client = Anthropic()
+client = Anthropic(base_url="https://tokenzero.sh")
def handler(event, context):
return client.messages.create(model="claude-sonnet-5-5", max_tokens=512, system=SYSTEM, messages=event["messages"]).model_dump()Cold starts are unaffected: the gateway holds no connection state your function needs.
2. Turn on prompt compression. Per request: X-TokenZero-Cache-Strategy: static (default) · X-TokenZero-Prompt-Cache-TTL: 1h or 12h. Per workspace (applies to every call without touching code): PATCH /v1/workspaces/settings {cache_strategy: static, prompt_cache_ttl: 1h} or the dashboard toggle.
3. Prove it. npx -y @tokenzero/cli doctor checks the gateway, the signer, the pricing table and your key; then watch input_tokens_cached_pct and compaction tokens saved on the scorecard.
Questions people ask
How do I point AWS Lambda at TokenZero?
Pass base_url / baseURL = https://tokenzero.sh where AWS Lambda builds its client (handler.py) and keep your anthropic key; nothing else changes.
What does prompt compression save on claude-sonnet-5-5?
On claude-sonnet-5-5 a cached input token costs $0.100 per million instead of $2.00, so 100,000 calls with a 1,500-token static prefix drop from $700 to $415 a month, 41% less, before any routing.
Does prompt compression change the model's output?
No. Cache formatting only marks or keys the static prefix and tool minification only collapses whitespace in descriptions; names, enums, defaults and examples are never touched.
What does TokenZero cost?
Free up to $500 per month of routed spend; then 15% of verified savings with a 3x-ROI-or-$0 rule, capped plans available. Gateway overhead measured at 1.52 ms p50.