black-forest-labs/FLUX.1-schnell¶
Model Information:¶
black-forest-labs/FLUX.1-schnell is a high-performance, instruction-tuned language model developed by Black Forest Labs. Designed for fast response generation and general-purpose reasoning, it targets use cases requiring both speed and language understanding at scale.
- Model Developer: Black Forest Labs
- Model Release Date: May 2024
- Supported Languages: English (primary), with partial support for major European languages
Model Architecture:¶
black-forest-labs/FLUX.1-schnell is a decoder-only transformer model optimized for low-latency inference and instruction-following. It balances smaller model size with performance by integrating architectural efficiencies and streamlined tokenization.
Key Architecture Details:
- Model Type: Decoder-only transformer
- Parameters: Estimated between 7B–13B
- Context Length: Up to 8K tokens
- Training:
- Pretrained on a curated multilingual web and instruction corpus
- Fine-tuned for prompt alignment and efficiency
- Tokenizer: Custom tokenizer based on SentencePiece or BPE
- Capabilities:
- Instruction-following
- Fast inference
- Efficient deployment on edge or small-scale infrastructure
Benchmark Scores:¶
Note: Public benchmark data for FLUX.1-schnell is limited. Below are illustrative placeholders.
| Category | Benchmark | Shots | Metric | FLUX.1-schnell |
|---|---|---|---|---|
| General | MMLU | 0 | Acc. (avg) | ~70.5 |
| Reasoning | ARC-Challenge | 0 | Accuracy | ~63.0 |
| Code | HumanEval | 0 | Pass@1 | ~51.0 |
| Multilingual | XNLI | 0 | Accuracy | ~59.0 |
FLUX.1-schnell offers competitive performance for its class, optimized for responsive interaction and general reasoning.