Black Forest Labs
FLUX — the new standard for image generation quality
Black Forest Labs created FLUX, a family of image generation models that have rapidly become the quality benchmark for open and commercial image generation. FLUX 1.1 Pro Ultra produces photorealistic images at high resolution.
FLUX 1.1 Pro Ultra produces some of the highest-quality AI images available, consistently outperforming Stable Diffusion and competing with Midjourney on photorealism benchmarks.
- State-of-the-art image quality
- Open-weight dev/schnell variants
- Fast inference on schnell model
- Newer company with smaller ecosystem
- Pro models require API access
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Full comparison tableBlack Forest Labs LLM pricing overview
Black Forest Labs is a proprietary AI lab that develops and hosts its own large language models. Black Forest Labs created FLUX, a family of image generation models that have rapidly become the quality benchmark for open and commercial image generation. FLUX 1.1 Pro Ultra produces photorealistic images at high resolution. Common use cases include Image generation, Commercial image production, Creative AI, Self-hosted image generation. Headquartered in Freiburg, Germany, founded 2024. All models are accessible via a REST API compatible with standard OpenAI-style request formats, enabling drop-in integration with most LLM frameworks and orchestration tools.
Black Forest Labs vs other LLM providers
Black Forest Labs competes with OpenAI, Anthropic, Google, Groq, Together AI, Mistral, Cohere, and other inference API providers across dimensions of price, throughput, latency, context window, and model intelligence. FLUX 1.1 Pro Ultra produces some of the highest-quality AI images available, consistently outperforming Stable Diffusion and competing with Midjourney on photorealism benchmarks. Use the LLM provider comparison tool to see Black Forest Labs token pricing, latency, and throughput side-by-side with any other provider. The full LLM pricing table shows all providers ranked by input token cost, output token cost, and throughput in a single sortable view.
Why choose Black Forest Labs?
Black Forest Labs's key strengths are: State-of-the-art image quality; Open-weight dev/schnell variants; Fast inference on schnell model. Limitations to consider: Newer company with smaller ecosystem; Pro models require API access. For teams running high-volume inference workloads, prompt caching and batch API endpoints can reduce effective input token costs by 50–90% — check the context window cost guide for a full breakdown of caching economics.
Understanding Black Forest Labs token pricing
Black Forest Labs charges separately for input (prompt) and output (completion) tokens, priced per 1M tokens in USD. Output tokens are typically 3–5× more expensive than input tokens due to the compute cost of autoregressive generation. Prices shown are sourced from Black Forest Labs's public pricing page and updated daily. Need help estimating your spend? Read the LLM API cost calculator guide — it covers tokens, context windows, prompt caching, and batch discounts with worked examples for RAG, chat history, and document processing workloads.
Black Forest Labs context window and model capabilities
Context window size directly affects both capability and cost — every token in the context window is charged as an input token. For RAG and document processing workloads, longer context windows enable richer retrieval but increase per-call costs proportionally. Prompt caching — where supported — stores the KV state of repeated prefixes and charges 75–90% less for cache hits, making it the most impactful cost optimization for applications with consistent system prompts or retrieved documents. See the LLM context window cost guide for a full analysis of how context length affects your API bill.
Self-hosted vs managed inference: when Black Forest Labs makes sense
Managed inference APIs like Black Forest Labs eliminate infrastructure overhead — no GPU provisioning, driver management, or model serving stack to maintain. The trade-off is cost at scale: a single H100 at ~$2.50/hr can serve ~500K tokens/min of Llama 3.3 70B, which at Black Forest Labs API rates would cost significantly more per token. The break-even point depends on your request volume, latency requirements, and engineering capacity. For teams processing fewer than ~10M tokens/day, managed APIs are almost always cheaper when total cost of ownership is considered. Above that threshold, self-hosted inference on rented GPU compute typically wins on unit economics. Read the cheapest GPU cloud guide for a full break-even analysis. Historical Black Forest Labs token price data is available in the LLM price history charts.