LLM Reference

Phi-3 Silica vs Qwen3-235B-A22B

Phi-3 Silica (2024) and Qwen3-235B-A22B (2025) are compact production models from Microsoft Research and Alibaba. Phi-3 Silica ships a not-yet-sourced context window, while Qwen3-235B-A22B ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

Qwen3-235B-A22B is safer overall; choose Phi-3 Silica when provider fit matters.

Decision scorecard

Local evidence first
SignalPhi-3 SilicaQwen3-235B-A22B
Best forgeneral production evaluationprovider-routed production
Decision fitGeneralCoding, RAG, and Long context
Context window—128k
Cheapest output-$0.58/1M tokens
Provider routes0 tracked5 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Phi-3 Silica when...
  • Use Phi-3 Silica when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Choose Qwen3-235B-A22B when...
  • Qwen3-235B-A22B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3-235B-A22B has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3-235B-A22B uniquely exposes Structured outputs in local model data.
  • Local decision data tags Qwen3-235B-A22B for Coding, RAG, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Phi-3 Silica

Unavailable

No complete token price in local provider data

Qwen3-235B-A22B

$217

Cheapest tracked route/tier: Novita AI

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Phi-3 Silica -> Qwen3-235B-A22B
  • No overlapping tracked provider route is sourced for Phi-3 Silica and Qwen3-235B-A22B; plan for SDK, billing, or endpoint changes.
  • Qwen3-235B-A22B adds Structured outputs in local capability data.
Qwen3-235B-A22B -> Phi-3 Silica
  • No overlapping tracked provider route is sourced for Qwen3-235B-A22B and Phi-3 Silica; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2024-06-012025-04-29
Context window—128k
Parameters3.3B235B
ArchitectureDecoder OnlyDecoder Only
LicenseMITOSI-approvedApache 2.0OSI-approved
OpennessOpen sourceOpen source
WeightsUnknownUnknown
CodeUnknownUnknown
Commercial useCommercial use: permittedCommercial use: permitted
Knowledge cutoff--

Pricing and availability

Pricing attributePhi-3 SilicaQwen3-235B-A22B
Input price-$0.09/1M tokens
Output price-$0.58/1M tokens
Providers-
Fireworks AIAWS BedrockOpenRouterVenice AINovita AI

Capabilities

CapabilityPhi-3 SilicaQwen3-235B-A22B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on structured outputs: Qwen3-235B-A22B. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: Phi-3 Silica has no token price sourced yet and Qwen3-235B-A22B has $0.09/1M input tokens. Provider availability is 0 tracked routes versus 5. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Phi-3 Silica when provider fit are central to the workload. Choose Qwen3-235B-A22B when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Is Phi-3 Silica or Qwen3-235B-A22B open source?

Phi-3 Silica is listed under MIT. Qwen3-235B-A22B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for structured outputs, Phi-3 Silica or Qwen3-235B-A22B?

Qwen3-235B-A22B has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Phi-3 Silica and Qwen3-235B-A22B?

Phi-3 Silica is available on the tracked providers still being sourced. Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, Venice AI, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Phi-3 Silica over Qwen3-235B-A22B?

Qwen3-235B-A22B is safer overall; choose Phi-3 Silica when provider fit matters. If your workload also depends on provider fit, start with Phi-3 Silica; if it depends on provider fit, run the same evaluation with Qwen3-235B-A22B.

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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.