Qwen3.5 35B A3B vs Stable Diffusion 3.5 Large

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokens$0.14Deepinfra · Sep 21, 2026Not reported
Output priceFrom · USD / 1M tokens$1.00Deepinfra · Sep 21, 2026Not reported
Context windowMaximum documented tokens262K0K
Model facts checkedAug 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

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldQwen3.5-35B-A3Bstable-diffusion-3.5-large
DeveloperQwenStability AI
FamilyQwen3 5 35b A3bStable Diffusion 3 5 Large
ModelQwen3.5-35B-A3Bstable-diffusion-3.5-large
VersionQwen3.5-35B-A3Bstable-diffusion-3.5-large
Lifecycleactiveactive
ReleasedUnknown2024-10-22
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextImage
Context window262K0K
Total parameters36B8.1B
Active parameters3BUnknown
Licenseapache-2.0other
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)Hugging Face (Standard), Stability AI (Pay as you go)
Capabilitieschat, generation, reasoning, toolsgeneration

Qwen3.5 35B A3B Capabilities

chatgenerationreasoningtools
Serving providers4
Canonical IDQwen/Qwen3.5-35B-A3B

Stable Diffusion 3.5 Large Capabilities

generation
Serving providers2
Canonical IDstabilityai/stable-diffusion-3.5-large

Primary Evidence

Sources and Freshness

Questions

Qwen3.5 35B A3B vs Stable Diffusion 3.5 Large FAQs

Is Qwen3.5 35B A3B or Stable Diffusion 3.5 Large 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 Large, 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 Large?+

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 Large?+

Qwen3.5 35B A3B has the larger sourced context window. Qwen3.5 35B A3B supports 262K and Stable Diffusion 3.5 Large supports 0K.

Which performs better in benchmarks, Qwen3.5 35B A3B 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 Qwen3.5 35B A3B or Stable Diffusion 3.5 Large be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3.5 35B A3B is open weight; Stable Diffusion 3.5 Large is open weight.

Can Qwen3.5 35B A3B and Stable Diffusion 3.5 Large understand images?+

Qwen3.5 35B A3B 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, Qwen3.5 35B A3B or Stable Diffusion 3.5 Large?+

Neither has a larger sourced maximum output. Qwen3.5 35B A3B is — and Stable Diffusion 3.5 Large is —.

Do Qwen3.5 35B A3B and Stable Diffusion 3.5 Large support reasoning and tool use?+

Qwen3.5 35B A3B: 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, Qwen3.5 35B A3B or Stable Diffusion 3.5 Large?+

Qwen3.5 35B A3B has 4 sourced provider routes; Stable Diffusion 3.5 Large has 2, so Qwen3.5 35B A3B has broader tracked availability.

Which offers better value, Qwen3.5 35B A3B 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.

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