---
title: "Undominated · Speculative Decoding Arbitrage Audit: review, setup & limitations · Undominated.ai"
canonical: https://undominated.ai/skills/undominated-speculative-decoding-arbitrage/
description: "Computes draft model acceptance rate thresholds (alpha) and verifies whether speculative decoding delivers net throughput/cost benefit over standard autoregressive decoding."
---

# Undominated · Speculative Decoding Arbitrage Audit: review, setup & limitations · Undominated.ai

> Computes draft model acceptance rate thresholds (alpha) and verifies whether speculative decoding delivers net throughput/cost benefit over standard autoregressive decoding.

[← Explore all skills](/skills/)

EVIDENCE AND EVALUATION / Undominated.ai

# Undominated · Speculative Decoding Arbitrage Audit

Computes draft model acceptance rate thresholds (alpha) and verifies whether speculative decoding delivers net throughput/cost benefit over standard autoregressive decoding.

 [See setup guidance ↓](#setup)[Original source ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/definition.md)

SOURCE REVIEW

 Reviewed 2026-10-14
 Evidence 3 linked sources
 Publisher Undominated.ai
 Licence [MIT ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/LICENSE.txt)
 Revision d5f73141d2aa
 [Read what was—and wasn’t—checked ↓](#review)

“Computes draft model acceptance rate thresholds (alpha) and verifies whether speculative decoding delivers net throughput/cost benefit over standard autoregressive decoding.”

 [Undominated.ai · upstream description ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/definition.md) Our analysis follows below.

01 / THE REASONING

## Why this made the selection.

 - Pairs a bounded workflow with an offline Python checker and explicitly synthetic example inputs.
- Created for recurring evidence and comparison failures: missing facts remain unknown and every conclusion keeps its scope.
- It names a concrete failure mode: Acceptance rates vary significantly across coding, math, and conversational domains.

### A good fit for

 - Use when benchmarking inference providers offering speculative decoding tiers.
- Run the local checker against a supplied file for this stated condition: passes = alpha >= min_alpha.

### Weigh up before choosing

 - Acceptance rates vary significantly across coding, math, and conversational domains.
- Fixture checks establish the documented local behaviour, not performance on an unrestricted set of real tasks.
- Public GitHub source availability is not yet verified; the complete download contains the reviewed source.
- A new npm install path is not yet verified. Use the complete source download.
- Exits `0` on verified pass, `1` on failed assertion, `2` on malformed input.

02 / THE REVIEW RECORD

## What we actually inspected.

Source review has boundaries. A clear record is more useful than a “safe” badge.

### Material inspected

 - skills/undominated-speculative-decoding-arbitrage/SKILL.md
- skills/undominated-speculative-decoding-arbitrage/scripts/check.py
- skills/undominated-speculative-decoding-arbitrage/examples/synthetic.json

### Our findings

 - First-party resource authored by Undominated.ai; this is our own verification record, not an independent endorsement.
- The download preserves the complete source and supporting files. Its manifest hashes identify the exact bytes.
- The checker names its required fields as: required = ["draft_cost_per_token", "target_cost_per_token", "acceptance_rate", "min_breakeven_acceptance_rate"].
- The pass expression is passes = alpha >= min_alpha. The process then runs sys.exit(0 if passes else 1).

### Not established by this review

 - Model compliance with these instructions on arbitrary tasks
- Native integration in every agent host
- Public GitHub source identity
- Remote installation through the standard Skills CLI
- The new npm resource CLI installation

The review applies to the material and revision named here. A newer upstream release can change its behavior.

03 / PUT IT TO WORK

## Add a skill to your workflow.

[Upstream setup instructions ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/definition.md)
 - Download the complete bundle from https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/bundle.zip and extract it into a new directory.
- Place the extracted directory at .agents/skills/undominated-speculative-decoding-arbitrage/ or your host's documented skills directory. Preserve SKILL.md, scripts, examples and licence files together.
- Run the documented synthetic example from the skill directory with Python 3.10 or later before using your own evidence.

### Before you start

 - An Agent Skills compatible host
- Python 3.10 or later for the optional checker

### Compatibility

Agent Skills compatible hosts · Python 3.10+

### Implementation

Python · Markdown

### Local, explicit inputs

 - read:user-selected-local-file

### Cost model

MIT source at no charge. Your agent host or model provider may charge for use; the included offline checks require no paid API.

THE COMPLETE REVIEWED DEFINITION

## Read it before you reuse it.

Original source bytes, with attribution. Review the host-specific setup notes above.

 Copy definition ↗ [Download complete resource + licence ↗](/resources/skills/undominated-speculative-decoding-arbitrage/bundle.zip)[Raw Markdown ↗](/resources/skills/undominated-speculative-decoding-arbitrage/definition.md)
 ---
name: undominated-speculative-decoding-arbitrage
description: Computes draft model acceptance rate thresholds (alpha) and verifies whether speculative decoding delivers net throughput/cost benefit over standard autoregressive decoding.
license: MIT
metadata:
 author: Undominated.ai
 version: "1.0.0"
 tags: ["speculative-decoding", "throughput", "latency", "arbitrage"]
---

# Speculative Decoding Arbitrage Audit

Computes draft model acceptance rate thresholds (alpha) and verifies whether speculative decoding delivers net throughput/cost benefit over standard autoregressive decoding.

## When to Use
Use when benchmarking inference providers offering speculative decoding tiers.

## Limitations
Acceptance rates vary significantly across coding, math, and conversational domains.

## Verification Script
Run the deterministic stdlib checker:
```bash
python3 scripts/check.py examples/synthetic.json
```
Exits `0` on verified pass, `1` on failed assertion, `2` on malformed input.

The download contains SKILL.md . Extract the whole bundle; the supporting files are required. Inspect the included MANIFEST.json for file hashes.

By **Undominated.ai**. [Exact upstream source ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/definition.md) · [Licence](/resources/skills/undominated-speculative-decoding-arbitrage/LICENSE.txt) · [Attribution](/resources/skills/undominated-speculative-decoding-arbitrage/ATTRIBUTION.txt)

SHA-256 d5f73141d2aa9583d52705e0873aaaeb3734c54398346e698a240f519dc6a8b5

 Read the applicable licence MIT License

Copyright (c) 2026 Undominated.ai

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

04 / FOLLOW THE EVIDENCE

## The source trail.

Our notes are separate from the original resource. Check upstream before adopting a new version.

 - [Original Undominated definition ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/definition.md) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/definition.md Supports: Workflow and input requirements, Stated limitations
- [MIT licence ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/LICENSE.txt) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/LICENSE.txt Supports: Redistribution terms and attribution
- [Complete source bundle ↗](https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/bundle.zip) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-speculative-decoding-arbitrage/bundle.zip Supports: Full local source, supporting files and integrity manifest

KEEP COMPARING

## Other approaches to consider.

Related by category or shared topics. These are alternatives to inspect, not a measured quality order.

 [### Undominated · Throughput benchmark audit ↗ Audit throughput and latency claims (tokens/second, TTFT, concurrency, batch sizes) to ensure apples-to-apples comparisons and detect deceptive single-user vs batched measurements.](/skills/undominated-throughput-benchmark-audit/)[### Undominated · Chunked Prefill Scheduler Audit ↗ Calibrates chunked prefill chunk sizes to eliminate inter-token latency (ITL) spikes while preserving prefill throughput.](/skills/undominated-chunked-prefill-scheduler-audit/)[### Undominated · Concurrency cliff audit ↗ Audit inference throughput degradation, queue build-up, and throughput cliff saturation as concurrency scales.](/skills/undominated-concurrency-cliff-audit/)

 [AI Tools ↗](/tools/)[Skills ↗](/skills/)[Agents ↗](/agents/)[MCP Servers ↗](/mcp-servers/)[Workflows ↗](/workflows/)

## Continue your investigation

 - [Choose a toolkit](/tools/)
- [Inspect execution hosts](/agents/)
- [Check tool access](/mcp-servers/)
- [Check project dependencies](/check-repo/)
