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Llama 3.2 90B Vision vs Phi-4 Mini Flash Reasoning

Llama 3.2 90B Vision (2024) and Phi-4 Mini Flash Reasoning (2025) are frontier reasoning models from AI at Meta and Microsoft Research. Llama 3.2 90B Vision ships a 128K-token context window, while Phi-4 Mini Flash Reasoning ships a 128K-token context window. 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 Flash Reasoning is safer overall; choose Llama 3.2 90B Vision when vision-heavy evaluation matters.

Decision scorecard

Local evidence first
SignalLlama 3.2 90B VisionPhi-4 Mini Flash Reasoning
Decision fitRAG, Long context, and VisionLong context
Context window128K128K
Cheapest output$1.8/1M tokens-
Provider routes1 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Llama 3.2 90B Vision when...
  • Llama 3.2 90B Vision uniquely exposes Vision and Structured outputs in local model data.
  • Local decision data tags Llama 3.2 90B Vision for RAG, Long context, and Vision.
Choose Phi-4 Mini Flash Reasoning when...
  • Phi-4 Mini Flash Reasoning uniquely exposes Reasoning in local model data.
  • Local decision data tags Phi-4 Mini Flash Reasoning for Long context.

Monthly cost at traffic

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

Llama 3.2 90B Vision

$1,530

Cheapest tracked route: AWS Bedrock

Phi-4 Mini Flash Reasoning

Unavailable

No complete token price in local provider data

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

Switch friction

Llama 3.2 90B Vision -> Phi-4 Mini Flash Reasoning
  • No overlapping tracked provider route is sourced for Llama 3.2 90B Vision and Phi-4 Mini Flash Reasoning; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision and Structured outputs before moving production traffic.
  • Phi-4 Mini Flash Reasoning adds Reasoning in local capability data.
Phi-4 Mini Flash Reasoning -> Llama 3.2 90B Vision
  • No overlapping tracked provider route is sourced for Phi-4 Mini Flash Reasoning and Llama 3.2 90B Vision; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning before moving production traffic.
  • Llama 3.2 90B Vision adds Vision and Structured outputs in local capability data.

Specs

Specification
Released2024-09-252025-12-01
Context window128K128K
Parameters88.8B
Architecturedecoder onlydecoder only
LicenseOpen Source1
Knowledge cutoff2024-03-

Pricing and availability

Pricing attributeLlama 3.2 90B VisionPhi-4 Mini Flash Reasoning
Input price$1.35/1M tokens-
Output price$1.8/1M tokens-
Providers

Capabilities

CapabilityLlama 3.2 90B VisionPhi-4 Mini Flash Reasoning
VisionYesNo
MultimodalNoNo
ReasoningNoYes
Function callingNoNo
Tool useNoNo
Structured outputsYesNo
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Llama 3.2 90B Vision, reasoning mode: Phi-4 Mini Flash Reasoning, and structured outputs: Llama 3.2 90B Vision. 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: Llama 3.2 90B Vision has $1.35/1M input tokens and Phi-4 Mini Flash Reasoning has no token price sourced yet. Provider availability is 1 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Llama 3.2 90B Vision when vision-heavy evaluation are central to the workload. Choose Phi-4 Mini Flash Reasoning when reasoning depth 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.

FAQ

Which has a larger context window, Llama 3.2 90B Vision or Phi-4 Mini Flash Reasoning?

Llama 3.2 90B Vision supports 128K tokens, while Phi-4 Mini Flash Reasoning supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Llama 3.2 90B Vision or Phi-4 Mini Flash Reasoning open source?

Llama 3.2 90B Vision is listed under Open Source. Phi-4 Mini Flash Reasoning is listed under 1. 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, Llama 3.2 90B Vision or Phi-4 Mini Flash Reasoning?

Llama 3.2 90B Vision 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.

Which is better for reasoning mode, Llama 3.2 90B Vision or Phi-4 Mini Flash Reasoning?

Phi-4 Mini Flash Reasoning has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Llama 3.2 90B Vision or Phi-4 Mini Flash Reasoning?

Llama 3.2 90B Vision 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 Llama 3.2 90B Vision and Phi-4 Mini Flash Reasoning?

Llama 3.2 90B Vision is available on AWS Bedrock. Phi-4 Mini Flash Reasoning is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

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