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Summary
DeepSeek V4 Flash from DeepSeek scored 32.7 on BIRD-CRITIC, placing it top 10 (rank 4 of 25) on this benchmark. This places the model in the weak band for BIRD-CRITIC. Below the threshold for production reliance on this benchmark family. Consider only for narrow, fully-tested tasks.
Model details
- Provider: DeepSeek
- Model key:
deepseek/deepseek-v4-flash - Context length: 1,048,576 tokens
- License: MIT
- Open weights: yes
Benchmark methodology
Benchmark goal: BIRD-CRITIC is designed to evaluate the performance of models in text-to-SQL tasks, specifically focusing on a comprehensive range of SQL operations and addressing user issues in multi-turn interactions.
Analysis
Key takeaways:
- DeepSeek V4 Flash demonstrates a solid foundation in generating standard SQL queries for common data manipulation and retrieval tasks.
- The model struggles significantly with tasks involving complex temporal logic, advanced window functions, and intricate set-based operations.
- Performance is notably weaker in scenarios requiring dynamic schema interaction or precise control over unique constraints and triggers.
- While capable of basic array and JSONB operations, advanced transformations within these structures often result in errors.
Failure modes observed
Common failure modes:
- Incorrect window function usage: Many errors stem from misapplying ROW_NUMBER(), LAG(), LEAD(), or custom aggregates within complex partitioning schemes.
- Temporal logic errors: Miscalculations or incorrect filtering when dealing with dates and times.
- JSON/JSONB manipulation issues: Errors arise in handling complex nested JSONB structures.
- Constraint and trigger logic: Functions and triggers often fail due to unique constraint violations.
- Subquery and CTE inefficiencies: Using subqueries or CTEs in ways that lead to incorrect results.
Secondary metrics
- Readability score: 0.0
- Toxicity score: 0.000
- Ethics score: 0.000
Run this evaluation yourself
LayerLens evaluates DeepSeek V4 Flash continuously across 11+ benchmarks. To replicate this BIRD-CRITIC evaluation on your own model, traces, or a different benchmark configuration, open the model in $LayerLens/$.
Source: LayerLens evaluation 69efc9abd05530877e5d4eeb. Updated 2026-04-27.