GPT-4o vs stable-diffusion-3.5-large

This comparison does not currently contain a protocol-matched coding benchmark for both GPT-4o and stable-diffusion-3.5-large, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Only GPT-4o has a directly sourced input price: $2.50 per million tokens. Only GPT-4o has a directly sourced output price: $10.00 per million tokens.

GPT-4o has the larger sourced context window. GPT-4o supports 128,000 and stable-diffusion-3.5-large supports 256.

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

stable-diffusion-3.5-large is the only model in this pair currently marked as self-hostable. GPT-4o is not marked open weight; stable-diffusion-3.5-large is open weight.

GPT-4o is documented with image input; stable-diffusion-3.5-large is not documented with image input. This reflects supported input modalities, not vision quality.

Neither has a larger sourced maximum output. GPT-4o is 16,384 and stable-diffusion-3.5-large is —.

GPT-4o: tool calling and image input. stable-diffusion-3.5-large: none of these features are definitively sourced. Feature support does not establish relative quality.

GPT-4o has 2 sourced provider routes; stable-diffusion-3.5-large has 1, so GPT-4o has broader tracked availability.

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.