GPT-5 Image Mini vs Stable Diffusion 3.5
| Signal | GPT-5 Image Mini | Delta | Stable Diffusion 3.5 |
|---|---|---|---|
Capabilities | 86 | +71 | |
Benchmarks | 88 | +88 | |
Pricing | 98 | +93 | |
Context window size | 100 | +100 | |
Recency | 79 | +65 | |
Output Capacity | 100 | +80 | |
| Overall Result | 6 wins | of 6 | 0 wins |
Score History
88.5
current score
GPT-5 Image Mini
right now
11.4
current score
GPT-5 Image Mini
OpenAI
Stable Diffusion 3.5
Stability AI
Stable Diffusion 3.5 saves you $350.00/month
That's $4200.00/year compared to GPT-5 Image Mini at your current usage level of 100K calls/month.
| Metric | GPT-5 Image Mini | Stable Diffusion 3.5 | Winner |
|---|---|---|---|
| Overall Score | 89 | 11 | GPT-5 Image Mini |
| Rank | #2 | #10 | GPT-5 Image Mini |
| Quality Rank | #2 | #10 | GPT-5 Image Mini |
| Adoption Rank | #2 | #10 | GPT-5 Image Mini |
| Parameters | -- | -- | -- |
| Context Window | 400K | -- | -- |
| Pricing | $2.50/$2.00/M | Free | -- |
| Signal Scores | |||
| Capabilities | 86 | 14 | GPT-5 Image Mini |
| Benchmarks | 88 | -- | GPT-5 Image Mini |
| Pricing | 98 | 5 | GPT-5 Image Mini |
| Context window size | 100 | 0 | GPT-5 Image Mini |
| Recency | 79 | 14 | GPT-5 Image Mini |
| Output Capacity | 100 | 20 | GPT-5 Image Mini |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 89/100 (rank #2), placing it in the top 100% of all 290 models tracked.
Scores 11/100 (rank #10), placing it in the top 97% of all 290 models tracked.
GPT-5 Image Mini has a 77-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Choose GPT-5 Image Mini when you need:
- Processing long documents or large codebases (400K token context)
- Multimodal workflows that require image understanding
- Step-by-step reasoning and chain-of-thought problem solving
Choose Stable Diffusion 3.5 when you need:
- High-volume production workloads where API costs must be minimized
- Self-hosted deployments where you need full control over the model
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Stable Diffusion 3.5 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (89/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-5 Image Mini clearly outperforms Stable Diffusion 3.5 with a significant 77.1-point lead. For most general use cases, GPT-5 Image Mini is the stronger choice. However, Stable Diffusion 3.5 may still excel in niche scenarios.
By Use Case
Best for Quality
GPT-5 Image Mini
Marginally better benchmark scores; both are excellent
Best for Cost
Stable Diffusion 3.5
100% lower pricing; better value at scale
Best for Reliability
GPT-5 Image Mini
Higher uptime and faster response speeds
Best for Prototyping
GPT-5 Image Mini
Stronger community support and better developer experience
Best for Production
GPT-5 Image Mini
Wider enterprise adoption and proven at scale
by OpenAI
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | GPT-5 Image Mini | Stable Diffusion 3.5 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streamingdiffers | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
GPT-5 Image Mini
OpenAI
Stable Diffusion 3.5
Stability AI
Stable Diffusion 3.5 saves you $6.90/month
That's 100% cheaper than GPT-5 Image Mini at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-5 Image Mini | Stable Diffusion 3.5 |
|---|---|---|
| Context Window | 400K | -- |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | Oct 16, 2025 | Oct 22, 2024 |
GPT-5 Image Mini's perfect score reflects its multimodal capabilities beyond just image generation - it processes vision inputs, handles 400K token contexts, and outputs both text and images. While Stable Diffusion 3.5 is open source with free input pricing, its $35,000/M output cost is 17,500x higher than GPT-5's $2/M, making it paradoxically more expensive for actual image generation despite the free input.
GPT-5 Image Mini's input pricing enables complex multimodal workflows where you can feed it existing images, files, and up to 400K tokens of context to guide generation, while Stable Diffusion 3.5's text-only input limits you to prompts. For a typical 1,000-image batch with detailed prompts, GPT-5 would cost ~$2.50 for inputs plus $2 for outputs, while Stable Diffusion 3.5 would cost $0 for inputs but $35,000 for the same outputs.
GPT-5 Image Mini isn't just an image generator - it's a full multimodal system with reasoning, function calling, JSON mode, and web search capabilities that scored 100/100. Stable Diffusion 3.5 scores 17/100 because it's a specialized text-to-image model with zero token context window and no additional capabilities beyond image output.
Migration becomes cost-effective when your volume exceeds roughly 57 images per month - at that point, GPT-5's $2/M output pricing beats Stable Diffusion's $35,000/M even accounting for GPT-5's $2.5/M input costs. Additionally, GPT-5's 128K max output tokens and multimodal capabilities enable workflows impossible with Stable Diffusion's image-only output.
With 400K tokens, GPT-5 Image Mini can process entire design documents, brand guidelines, and reference image sets in a single request, then generate images with full context awareness. Stable Diffusion 3.5's 0-token context means each generation starts fresh, requiring careful prompt engineering and external workflow management to maintain consistency across image sets.