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Stability AI

Stable Diffusion 3.5 Large and Stable Image Ultra — open-weight image generation

Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation.

Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.

Image editingInpaintingSelf-hosted AI artFine-tuning
Stability AI Models
2
Stability AI Cheapest Input
—
per 1M tokens
Stability AI Max Throughput
0 t/s
Stability AI Min Latency
7.0s
TTFT p50
Stability AI Best Intelligence
0/100
Stability AI Vision Models
0
Stability AI Strengths
  • Open-weight SD 3.5 models — self-host on any GPU cloud
  • Largest community ecosystem of fine-tuned variants and LoRAs
  • Stable Image Ultra for photorealistic output
  • Stable Video Diffusion for short video generation
  • Competitive API pricing vs DALL-E 3
  • Inpainting and outpainting support
Stability AI Weaknesses
  • Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
  • Company has faced financial challenges and leadership changes
  • SD 3.5 adoption slower than FLUX in the community
Stability AI Model Tiers
frontier
1
advanced
1
efficient
0
budget
0
Stability AI Capabilities
Vision0
Tool Use0
Reasoning0
Open Weights1
Multilingual0
RAG / Search0
Structured Out0
Embeddings0
Stability AI Intelligence vs Pricelog scale
frontieradvancedefficientbudget
Stability AI Throughput (tokens/sec)
Stability AI Input vs Output Pricing ($/1M tokens)
InputOutput
Stability AI Context Window (tokens)
Stability AI Best Model by Use Case
image-generation
stable-diffusion-3.5-large
advanced$0.00/1M in
open-weights
stable-diffusion-3.5-large
advanced$0.00/1M in
quality
stable-image-ultra
frontier$0.00/1M in

Stability AI Models

Sort by:
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ModelModalityTierPriceCached /1MTTFTThroughputContextIntel.Caps
stable-diffusion-3.5-large
Stable Diffusion
Imageadvanced
$0.07
per image
EST Jul 2026
—7.0s0 t/s4K
0
stable-image-ultra
Stable Image
Imagefrontier
$0.14
per image
EST Jul 2026
—8.0s0 t/s4K
0

Stability AI — Frequently Asked Questions (FAQs)

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Stability AI LLM pricing overview

Stability AI is a proprietary AI lab that develops and hosts its own large language models. Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation. Common use cases include Image generation, Image editing, Inpainting, Video generation. Headquartered in London, UK, founded 2020. 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.

Stability AI vs other LLM providers

Stability AI 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. Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline. Use the LLM provider comparison tool to see Stability AI 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 Stability AI?

Stability AI stands out because: Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.. The API currently offers 2 models, spanning 1 frontier, 1 advanced tiers. 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 Stability AI token pricing

Stability AI 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 Stability AI's public pricing page and updated every 15 minutes. 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.

Stability AI 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. Stability AI's largest context window is 4K tokens. 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 Stability AI makes sense

Managed inference APIs like Stability AI 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 Stability AI 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 Stability AI token price data is available in the LLM price history charts.

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