phi-4 vs Stable Diffusion 3.5 Medium

At a Glance

Compare
phi-4Microsoft
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.070Deepinfra · Sep 21, 2026Not reported
Output priceFrom · USD / 1M tokens$0.14Deepinfra · Sep 21, 2026Not reported
Context windowMaximum documented tokens16K0K
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 →

Different Model RolesThese models do not share a sourced market category. Their primary-source facts remain comparable below, while performance claims require matched evidence.

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

Fieldphi-4stable-diffusion-3.5-medium
DeveloperMicrosoftStability AI
FamilyPhi 4Stable Diffusion 3 5 Medium
Modelphi-4stable-diffusion-3.5-medium
Versionphi-4stable-diffusion-3.5-medium
Lifecycleactiveactive
Released2024-12-122024-10-29
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextImage
Context window16K0K
Total parameters14.7B2.5B
Active parametersUnknownUnknown
Licensemitother
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Hugging Face (Standard), Stability AI (Pay as you go)
Capabilitieschat, generationgeneration

phi-4 Capabilities

chatgeneration
Serving providers3
Canonical IDmicrosoft/phi-4

Stable Diffusion 3.5 Medium Capabilities

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

Primary Evidence

Sources and Freshness

Questions

phi-4 vs Stable Diffusion 3.5 Medium FAQs

Is phi-4 or Stable Diffusion 3.5 Medium better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both phi-4 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, phi-4 or Stable Diffusion 3.5 Medium?+

Only phi-4 has a directly sourced input price: $0.070 per million tokens. Only phi-4 has a directly sourced output price: $0.14 per million tokens.

Which has a larger context window, phi-4 or Stable Diffusion 3.5 Medium?+

phi-4 has the larger sourced context window. phi-4 supports 16K and Stable Diffusion 3.5 Medium supports 0K.

Which performs better in benchmarks, phi-4 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 phi-4 or Stable Diffusion 3.5 Medium be self-hosted?+

Both models have the same recorded self-hosting status: supported. phi-4 is open weight; Stable Diffusion 3.5 Medium is open weight.

Can phi-4 and Stable Diffusion 3.5 Medium understand images?+

phi-4 is not 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, phi-4 or Stable Diffusion 3.5 Medium?+

Neither has a larger sourced maximum output. phi-4 is — and Stable Diffusion 3.5 Medium is —.

Do phi-4 and Stable Diffusion 3.5 Medium support reasoning and tool use?+

phi-4: none of these features are definitively sourced. 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, phi-4 or Stable Diffusion 3.5 Medium?+

phi-4 has 3 sourced provider routes; Stable Diffusion 3.5 Medium has 2, so phi-4 has broader tracked availability.

Which offers better value, phi-4 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.

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