Llama 4 Scout 17B 16E vs Stable Diffusion 3.5 Medium
At a Glance
| Compare | Stable Diffusion 3.5 MediumStability AI | |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 10,000K | 0K |
| Model facts checked | Aug 28, 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 | Llama-4-Scout-17B-16E | stable-diffusion-3.5-medium |
|---|---|---|
| Developer | Meta | Stability AI |
| Family | Llama 4 Scout 17b 16e | Stable Diffusion 3 5 Medium |
| Model | Llama-4-Scout-17B-16E | stable-diffusion-3.5-medium |
| Version | Llama-4-Scout-17B-16E | stable-diffusion-3.5-medium |
| Lifecycle | active | active |
| Released | 2025-04-05 | 2024-10-29 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Image |
| Context window | 10,000K | 0K |
| Total parameters | 108.6B | 2.5B |
| Active parameters | 17B | Unknown |
| License | other | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Together Ai (Standard) | Hugging Face (Standard), Stability AI (Pay as you go) |
| Capabilities | chat, generation, tools | generation |
Llama 4 Scout 17B 16E Capabilities
Stable Diffusion 3.5 Medium Capabilities
Primary Evidence
Sources and Freshness
Questions
Llama 4 Scout 17B 16E vs Stable Diffusion 3.5 Medium FAQs
Is Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E and Stable Diffusion 3.5 Medium, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium?+
Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.
Which has a larger context window, Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium?+
Llama 4 Scout 17B 16E has the larger sourced context window. Llama 4 Scout 17B 16E supports 10,000K and Stable Diffusion 3.5 Medium supports 0K.
Which performs better in benchmarks, Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium be self-hosted?+
Both models have the same recorded self-hosting status: supported. Llama 4 Scout 17B 16E is open weight; Stable Diffusion 3.5 Medium is open weight.
Can Llama 4 Scout 17B 16E and Stable Diffusion 3.5 Medium understand images?+
Llama 4 Scout 17B 16E is documented with image input; Stable Diffusion 3.5 Medium is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium?+
Neither has a larger sourced maximum output. Llama 4 Scout 17B 16E is — and Stable Diffusion 3.5 Medium is —.
Do Llama 4 Scout 17B 16E and Stable Diffusion 3.5 Medium support reasoning and tool use?+
Llama 4 Scout 17B 16E: tool calling and image input. Stable Diffusion 3.5 Medium: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium?+
Llama 4 Scout 17B 16E has 1 sourced provider route; Stable Diffusion 3.5 Medium has 2, so Stable Diffusion 3.5 Medium has broader tracked availability.
Which offers better value, Llama 4 Scout 17B 16E or Stable Diffusion 3.5 Medium?+
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.