LLM ReferenceLLM Reference

Phi-4 Mini vs Qwen-Max

Phi-4 Mini (2024) and Qwen-Max (2024) are compact production models from Microsoft Research and Alibaba. Phi-4 Mini ships a not-yet-sourced context window, while Qwen-Max ships a 128K-token context window. On pricing, Phi-4 Mini costs $0.05/1M input tokens versus $1.04/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

Phi-4 Mini is ~1980% cheaper at $0.05/1M; pay for Qwen-Max only for vision-heavy evaluation.

Decision scorecard

Local evidence first
SignalPhi-4 MiniQwen-Max
Decision fitClassificationRAG, Long context, and Vision
Context window128K
Cheapest output$0.15/1M tokens$4.16/1M tokens
Provider routes3 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Phi-4 Mini when...
  • Phi-4 Mini has the lower cheapest tracked output price at $0.15/1M tokens.
  • Phi-4 Mini has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Phi-4 Mini for Classification.
Choose Qwen-Max when...
  • Qwen-Max has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen-Max uniquely exposes Vision and Structured outputs in local model data.
  • Local decision data tags Qwen-Max for RAG, Long context, and Vision.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate Phi-4 Mini

Phi-4 Mini

$77.50

Cheapest tracked route: Novita AI

Qwen-Max

$1,872

Cheapest tracked route: OpenRouter

Estimated monthly gap: $1,795. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Phi-4 Mini -> Qwen-Max
  • No overlapping tracked provider route is sourced for Phi-4 Mini and Qwen-Max; plan for SDK, billing, or endpoint changes.
  • Qwen-Max is $4.01/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Qwen-Max adds Vision and Structured outputs in local capability data.
Qwen-Max -> Phi-4 Mini
  • No overlapping tracked provider route is sourced for Qwen-Max and Phi-4 Mini; plan for SDK, billing, or endpoint changes.
  • Phi-4 Mini is $4.01/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision and Structured outputs before moving production traffic.

Specs

Specification
Released2024-12-132024-05-11
Context window128K
Parameters3.8B
Architecture-decoder only
LicenseMicrosoft ResearchApache 2.0
Knowledge cutoff--

Pricing and availability

Pricing attributePhi-4 MiniQwen-Max
Input price$0.05/1M tokens$1.04/1M tokens
Output price$0.15/1M tokens$4.16/1M tokens
Providers

Capabilities

CapabilityPhi-4 MiniQwen-Max
VisionNoYes
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Qwen-Max and structured outputs: Qwen-Max. 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.

For cost, Phi-4 Mini lists $0.05/1M input and $0.15/1M output tokens, while Qwen-Max lists $1.04/1M input and $4.16/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Phi-4 Mini lower by about $1.9 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.

Choose Phi-4 Mini when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen-Max when vision-heavy evaluation 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

Which is cheaper, Phi-4 Mini or Qwen-Max?

Phi-4 Mini is cheaper on tracked token pricing. Phi-4 Mini costs $0.05/1M input and $0.15/1M output tokens. Qwen-Max costs $1.04/1M input and $4.16/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Phi-4 Mini or Qwen-Max open source?

Phi-4 Mini is listed under Microsoft Research. Qwen-Max 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 vision, Phi-4 Mini or Qwen-Max?

Qwen-Max has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for structured outputs, Phi-4 Mini or Qwen-Max?

Qwen-Max 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-4 Mini and Qwen-Max?

Phi-4 Mini is available on Fireworks AI, NVIDIA NIM, and Novita AI. Qwen-Max is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

When should I pick Phi-4 Mini over Qwen-Max?

Phi-4 Mini is ~1980% cheaper at $0.05/1M; pay for Qwen-Max only for vision-heavy evaluation. If your workload also depends on provider fit, start with Phi-4 Mini; if it depends on vision-heavy evaluation, run the same evaluation with Qwen-Max.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.