GPT-5 Mini vs Stable Diffusion 3.5 Large
At a Glance
| Compare |  GPT-5 MiniOpenAI |  Stable Diffusion 3.5 LargeStability AI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #45 of 460.0 score · 2/3 sources · provisional · missing LiveBench · full-core range 0.0–33.4 | UnrankedNot in the 46-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.125Openrouter ↗ · Sep 3, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $1.00Openrouter ↗ · Sep 3, 2026 | Not reported |
| Context windowMaximum documented tokens | 400K | 0K |
| Model facts checked | Sep 3, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | GPT-5 Mini | stable-diffusion-3.5-large |
|---|---|---|
| Developer | OpenAI | Stability AI |
| Family | Gpt 5 | Stable Diffusion 3 5 Large |
| Model | GPT-5 Mini | stable-diffusion-3.5-large |
| Version | GPT-5 Mini | stable-diffusion-3.5-large |
| Lifecycle | active | active |
| Released | 2025-08-07 | 2024-10-22 |
| Knowledge cutoff | 2024-05-31 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Image |
| Context window | 400K | 0K |
| Total parameters | Unknown | 8.1B |
| Active parameters | Unknown | Unknown |
| License | Unknown | other |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Openai (Standard), Openrouter (Standard) | Hugging Face (Standard), Stability AI (Pay as you go) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | generation |
GPT-5 Mini Capabilities
Stable Diffusion 3.5 Large Capabilities
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Primary Evidence
Sources and Freshness
Questions
GPT-5 Mini vs Stable Diffusion 3.5 Large FAQs
Is GPT-5 Mini or Stable Diffusion 3.5 Large better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5 Mini and Stable Diffusion 3.5 Large, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-5 Mini or Stable Diffusion 3.5 Large?+
Only GPT-5 Mini has a directly sourced input price: $0.125 per million tokens. Only GPT-5 Mini has a directly sourced output price: $1.00 per million tokens.
Which has a larger context window, GPT-5 Mini or Stable Diffusion 3.5 Large?+
GPT-5 Mini has the larger sourced context window. GPT-5 Mini supports 400K and Stable Diffusion 3.5 Large supports 0K.
Which performs better in benchmarks, GPT-5 Mini or Stable Diffusion 3.5 Large?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can GPT-5 Mini or Stable Diffusion 3.5 Large be self-hosted?+
Stable Diffusion 3.5 Large is the only model in this pair currently marked as self-hostable. GPT-5 Mini is not marked open weight; Stable Diffusion 3.5 Large is open weight.
Can GPT-5 Mini and Stable Diffusion 3.5 Large understand images?+
GPT-5 Mini is documented with image input; Stable Diffusion 3.5 Large is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-5 Mini or Stable Diffusion 3.5 Large?+
Neither has a larger sourced maximum output. GPT-5 Mini is 128K and Stable Diffusion 3.5 Large is —.
Do GPT-5 Mini and Stable Diffusion 3.5 Large support reasoning and tool use?+
GPT-5 Mini: reasoning, tool calling, and image input. Stable Diffusion 3.5 Large: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-5 Mini or Stable Diffusion 3.5 Large?+
GPT-5 Mini has 2 sourced provider routes; Stable Diffusion 3.5 Large has 2, a tie.
Which offers better value, GPT-5 Mini or Stable Diffusion 3.5 Large?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.