Muse Glimmer 30B vs Stable Diffusion 3.5 Medium
At a Glance
| Compare | Muse Glimmer 30BMeta | Stable Diffusion 3.5 MediumStability AI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.30Deepinfra ↗ · Sep 22, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $1.20Deepinfra ↗ · Sep 22, 2026 | Not reported |
| Context windowMaximum documented tokens | 131K | 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 | Muse Glimmer 30B | stable-diffusion-3.5-medium |
|---|---|---|
| Developer | Meta | Stability AI |
| Family | Muse Glimmer | Stable Diffusion 3 5 Medium |
| Model | Muse Glimmer 30B | stable-diffusion-3.5-medium |
| Version | Muse Glimmer 30B | stable-diffusion-3.5-medium |
| Lifecycle | active | active |
| Released | 2026-08-09 | 2024-10-29 |
| Knowledge cutoff | 2026-01-04 | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Image |
| Context window | 131K | 0K |
| Total parameters | 29.8B | 2.5B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard) | Hugging Face (Standard), Stability AI (Pay as you go) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | generation |
Muse Glimmer 30B Capabilities
Stable Diffusion 3.5 Medium Capabilities
Primary Evidence
Sources and Freshness
Questions
Muse Glimmer 30B vs Stable Diffusion 3.5 Medium FAQs
Is Muse Glimmer 30B or Stable Diffusion 3.5 Medium better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Muse Glimmer 30B 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, Muse Glimmer 30B or Stable Diffusion 3.5 Medium?+
Only Muse Glimmer 30B has a directly sourced input price: $0.30 per million tokens. Only Muse Glimmer 30B has a directly sourced output price: $1.20 per million tokens.
Which has a larger context window, Muse Glimmer 30B or Stable Diffusion 3.5 Medium?+
Muse Glimmer 30B has the larger sourced context window. Muse Glimmer 30B supports 131K and Stable Diffusion 3.5 Medium supports 0K.
Which performs better in benchmarks, Muse Glimmer 30B 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 Muse Glimmer 30B or Stable Diffusion 3.5 Medium be self-hosted?+
Both models have the same recorded self-hosting status: supported. Muse Glimmer 30B is open weight; Stable Diffusion 3.5 Medium is open weight.
Can Muse Glimmer 30B and Stable Diffusion 3.5 Medium understand images?+
Muse Glimmer 30B 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, Muse Glimmer 30B or Stable Diffusion 3.5 Medium?+
Neither has a larger sourced maximum output. Muse Glimmer 30B is — and Stable Diffusion 3.5 Medium is —.
Do Muse Glimmer 30B and Stable Diffusion 3.5 Medium support reasoning and tool use?+
Muse Glimmer 30B: reasoning, 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, Muse Glimmer 30B or Stable Diffusion 3.5 Medium?+
Muse Glimmer 30B has 3 sourced provider routes; Stable Diffusion 3.5 Medium has 2, so Muse Glimmer 30B has broader tracked availability.
Which offers better value, Muse Glimmer 30B 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.