Shattered Needle

FabricBench / frozen instance v1.0

Shattered Needle

A benchmark of whether an agent can organize a large corpus before seeing the questions, then recover answers from its frozen knowledge base without the source documents.

Frozen Mechanical grading Same-model WEAVE and QUERY Results updated 17 August 2026
877documents
~305kcorpus tokens
12cases
307questions
10displayed runs

Results

Weighted score is primary. Culprit synthesis receives 55% of the weight; resolution and provenance make up the remainder.

GLM-5.3portable100%~$11.01 proxy1h 15m 28scomplete
Gemini 3.7 Flashportable100%$2.40 billed37m 18scomplete
Claude Opus 4.8historical100%~$12.56not capturedcomplete
GPT-5.6 Sol, clarified fabricquery-only100%~$3.266m 43sdiagnostic
Claude Sonnet 5historical95%~$5.78not capturedcomplete
GPT-5.6 Terraportable57%~$7.0034m 28s*resumed
MiniMax M3portable52%~$3.362h 56m 23s*resumed
GPT-5.6 Lunaportable11%~$0.7830m 12scomplete
Claude Haiku 4.5historical2%~$1.01not capturedcomplete
DeepSeek V4 Flashportableno score$3.54+ billed1h 57m 5s+QUERY failed

Historical runs used the byte-identical corpus and frozen gold with earlier prompts. Query-only results are not end-to-end scores. API figures are estimates, not charges paid. * Resumed wall time is incomplete; DeepSeek time excludes later manual repair.

Culprit 55% Resolution 20% Identity provenance 10% Ownership provenance 8% Finding provenance 7%

Benchmark

What it measures

An agent reads scattered fictional records, resolves aliases and relationships, joins evidence across files, and preserves provenance. The held-out quiz tests what the resulting knowledge base can recover.

The knowledge representation is unrestricted. Only answers from the frozen artifact are scored.

  • Instance v1.0 / run21
  • Corpus 877 irregular documents
  • Cases 12 interleaved investigations
  • Evidence six factors per culprit
  • Grading deterministic, including provenance

Protocol

The model knows the task type but not the questions during ingestion.

01 / WEAVE

Build

Read the corpus and write a persistent knowledge base. No questions are visible.

02 / FREEZE

Remove sources

End the session, freeze the artifact, and physically remove the corpus.

03 / QUERY

Recover

A fresh session of the same model answers 307 questions from the artifact alone.

Technical notes

Full score breakdown
Model / runResolutionID provenanceOwner provenanceFinding provenance
GLM-5.3103/103103/10353/5336/36
Gemini 3.7 Flash103/103103/10353/5336/36
Claude Opus 4.8103/103103/10353/5336/36
Claude Sonnet 5103/103103/10353/5333/36
GPT-5.6 Terra103/10392/10353/5335/36
MiniMax M355/10355/10337/5314/36
GPT-5.6 Luna18/10318/10322/5312/36
Claude Haiku 4.56/1030/1030/533/36
GPT-5.6 Sol, clarified fabric102/103102/10353/5336/36
Run comparability

Portable runs use the packaged harness. Historical Claude runs used pre-clarification prompts and in-session Claude Code subagents, but the byte-identical corpus and frozen gold. Terra and MiniMax resumed after interruption. The clarified-fabric Sol result isolates QUERY behavior and is not an end-to-end run.

DeepSeek and interrupted runs

DeepSeek completed coverage of all 877 documents after operator repair and deterministic consolidation, but three autonomous same-model QUERY attempts failed. A separate corpus-free, operator-assisted diagnostic recovered 289/307 answers (89% weighted, 10/12 culprits); it is not an official end-to-end score.

Pricing and token accounting

OpenRouter values are reported bills. Other values apply public standard API rates retrieved on 17 August 2026 to measured usage:

input + cache writes + cache reads + (output + separately reported reasoning)

Anthropic includes extended-thinking tokens in output_tokens. Claude estimates include five-minute cache writes and cache hits recovered from the original transcripts. GLM-5.3 uses GLM-5.2 rates as a proxy because no 5.3 pay-as-you-go tariff was listed.

Sources: OpenAI, Anthropic, MiniMax, Z.AI, and OpenRouter.

Generation and certification

A private generator starts from target propositions, lowers them through a function-free Horn derivation graph, and realizes only the leaves as natural-language documents. The forward engine verifies solvability and uniqueness. Distractors are certified not to license an alternative derivation, and all corpus files are frozen by SHA-256 manifest.

InterpretationThis is one frozen instance, not a population-level model ranking. Three perfect runs show that v1 has reached the frontier ceiling; later versions need larger and harder instances.