Qwen3.5 35B A3B vs Stable Diffusion 3.5 Medium
At a Glance
| Compare | Qwen3.5 35B A3BQwen | Stable Diffusion 3.5 MediumStability AI |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.14Deepinfra ↗ · Sep 22, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $1.00Deepinfra ↗ · Sep 22, 2026 | Not reported |
| Context windowMaximum documented tokens | 262K | 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 | Qwen3.5-35B-A3B | stable-diffusion-3.5-medium |
|---|---|---|
| Developer | Qwen | Stability AI |
| Family | Qwen3 5 35b A3b | Stable Diffusion 3 5 Medium |
| Model | Qwen3.5-35B-A3B | stable-diffusion-3.5-medium |
| Version | Qwen3.5-35B-A3B | stable-diffusion-3.5-medium |
| Lifecycle | active | active |
| Released | Unknown | 2024-10-29 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Image |
| Context window | 262K | 0K |
| Total parameters | 36B | 2.5B |
| Active parameters | 3B | Unknown |
| License | apache-2.0 | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Hugging Face (Standard), Stability AI (Pay as you go) |
| Capabilities | chat, generation, reasoning, tools | generation |
Qwen3.5 35B A3B Capabilities
Stable Diffusion 3.5 Medium Capabilities
Primary Evidence
Sources and Freshness
Questions
Qwen3.5 35B A3B vs Stable Diffusion 3.5 Medium FAQs
Is Qwen3.5 35B A3B or Stable Diffusion 3.5 Medium better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 35B A3B 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, Qwen3.5 35B A3B or Stable Diffusion 3.5 Medium?+
Only Qwen3.5 35B A3B has a directly sourced input price: $0.14 per million tokens. Only Qwen3.5 35B A3B has a directly sourced output price: $1.00 per million tokens.
Which has a larger context window, Qwen3.5 35B A3B or Stable Diffusion 3.5 Medium?+
Qwen3.5 35B A3B has the larger sourced context window. Qwen3.5 35B A3B supports 262K and Stable Diffusion 3.5 Medium supports 0K.
Which performs better in benchmarks, Qwen3.5 35B A3B 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 Qwen3.5 35B A3B or Stable Diffusion 3.5 Medium be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3.5 35B A3B is open weight; Stable Diffusion 3.5 Medium is open weight.
Can Qwen3.5 35B A3B and Stable Diffusion 3.5 Medium understand images?+
Qwen3.5 35B A3B 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, Qwen3.5 35B A3B or Stable Diffusion 3.5 Medium?+
Neither has a larger sourced maximum output. Qwen3.5 35B A3B is — and Stable Diffusion 3.5 Medium is —.
Do Qwen3.5 35B A3B and Stable Diffusion 3.5 Medium support reasoning and tool use?+
Qwen3.5 35B A3B: 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, Qwen3.5 35B A3B or Stable Diffusion 3.5 Medium?+
Qwen3.5 35B A3B has 4 sourced provider routes; Stable Diffusion 3.5 Medium has 2, so Qwen3.5 35B A3B has broader tracked availability.
Which offers better value, Qwen3.5 35B A3B 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.