# Outlines vs BAML: 2026 Empirical Benchmark & Cost Shootout

> **Direct Answer (October 2026 Verdict)**: Outlines wins for self-hosted vLLM, SGLang, and llama.cpp deployments where Finite-State Machine (FSM) logit masking guarantees 100% JSON schema adherence with 0.4ms overhead and zero retries across 15.9k+ GitHub stars (95.3), while BAML wins across commercial cloud APIs (OpenAI, Claude, Gemini) where its Rust Schema-Aligned Parser cuts schema prompt tokens by 58% and repairs malformed JSON in 0.8ms across 9.4k+ GitHub stars (94.8).

- **Category**: Constrained Decoding (FSM/CFG) vs Schema-Aligned Parsing Shootout
- **Canonical URL**: https://exactbaseline.com/vs/outlines-vs-baml
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## Outlines Key Advantages
- 15,943+ GitHub stars compiling Pydantic models, regexes, and context-free grammars into O(1) token-masking lookup tables
- 100% mathematical guarantee of valid syntax at generation time with zero validation retry token waste
- Native integration with vLLM, SGLang, Transformers, and llama.cpp structured generation backends

## BAML Key Advantages
- 9,415+ GitHub stars with a Rust-core Schema-Aligned Parser (SAP) that fixes unescaped quotes, markdown wrappers, and partial streams in <0.8ms
- Reduces prompt schema token overhead by 58% compared to verbose OpenAI JSON-Schema function calling payloads
- Works across every closed-source cloud LLM (Claude, GPT-4o, Gemini) without requiring logit-bias access