| ---
|
| pretty_name: MuxaBench
|
| language:
|
| - en
|
| license: other
|
| license_name: muxa2
|
| license_link: LICENSE
|
| size_categories:
|
| - n<1K
|
| task_categories:
|
| - question-answering
|
| - other
|
| tags:
|
| - benchmark
|
| - evaluation
|
| - code
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| - systems-programming
|
| - zig
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| - coding-benchmark
|
| - llm-benchmark
|
| - rubric
|
| configs:
|
| - config_name: default
|
| data_files:
|
| - split: test
|
| path: MuxaBench.jsonl
|
| dataset_info:
|
| features:
|
| - name: id_aa
|
| dtype: string
|
| - name: title
|
| dtype: string
|
| - name: category
|
| dtype: string
|
| - name: prompt
|
| dtype: string
|
| - name: system_prompt
|
| dtype: string
|
| - name: rubric
|
| dtype: string
|
| - name: expected_deliverables
|
| dtype: string
|
| - name: reference_files
|
| dtype: string
|
| splits:
|
| - name: test
|
| num_bytes: 270174
|
| num_examples: 26
|
| download_size: 270174
|
| dataset_size: 270174
|
| ---
|
|
|
| # MuxaBench: Systems Programming Benchmark
|
|
|
| MuxaBench is an evaluation benchmark designed to assess LLMs and coding agents on 26 staff/principal-level systems programming tasks in pure **Zig 0.15.1**.
|
|
|
| ## Benchmark Overview
|
|
|
| The benchmark contains 26 tasks divided into 5 core engineering domains:
|
| 1. **Rendering and content pipelines** (6 tasks): ReSTIR DI on BVH, perceptual 8 bpp texture codec, analytic-AA vector rasteriser, 10 km² city + navmesh, HZB occlusion culling.
|
| 2. **Physics and motion simulation** (6 tasks): GJK/EPA CCD rigid body, XPBD rope/cloth, active ragdoll, full-body IK, 128³ Eulerian multigrid smoke solver, quadcopter simulator.
|
| 3. **Numerical and ML kernels** (5 tasks): Fused transformer step, Int8 GQA engine with paged KV-cache, runtime SPIR-V shader generator, FlashAttention causal attention, spatial audio synthesizer.
|
| 4. **Systems infrastructure** (5 tasks): Crash-safe WAL KV engine, deterministic matching engine (10M ops/s), x86_64 microkernel slice (4-level VMM/page allocator), Raft under 30% packet loss, JIT compiler with generational GC.
|
| 5. **Security and cryptography** (4 tasks): Constant-time ML-KEM-768, ML-DSA-65 signatures, R1CS SHA-256 prover, static PE heuristic analyzer.
|
|
|
| ## Evaluation Methodology (Score Against Rubric)
|
|
|
| Each task in MuxaBench is scored **against a multi-criteria rubric** with discrete scoring levels (0 to 2 or 3) across ~6 explicit criteria per task.
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| Models are evaluated on:
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| - Strict correctness and mathematical formulation
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| - Enforcing zero dynamic allocation in hot loops after initialization
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| - Deterministic hashing across runs and threads
|
| - metric_provenance: verifying that reported metrics trace directly to executable test harness code
|
|
|
