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Comparison · 2 models · Updated Oct 4, 2026

Llama-3.2-11B-Vision-Instruct vs Phi-4-mini

Too close to call on our weighted score (Phi-4-mini 58, Llama-3.2-11B-Vision-Instruct 58). The right pick depends on what you value most.

  1. Meta

    Llama-3.2-11B-Vision-Instruct

    Released Sep 25, 2024

    58/100
    • ECI—
    • Price$0.197 / $0.51
    • Context128K
    Full specs Remove Llama-3.2-11B-Vision-Instruct

  2. Microsoft

    Phi-4-mini

    Released Dec 11, 2024

    58/100
    • ECI—
    • Price$0.075 / $0.30
    • Context128K
    Full specs Remove Phi-4-mini

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Phi-4-mini 58/100, Llama-3.2-11B-Vision-Instruct 58/100), so choose by what matters most for your work: Phi-4-mini on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest pricePhi-4-miniPhi-4-mini $0.131 · Llama-3.2-11B-Vision-Instruct $0.275 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameLlama-3.2-11B-Vision-Instruct 128,000 · Phi-4-mini 128,000 tokens
  • Widest inputsLlama-3.2-11B-Vision-InstructLlama-3.2-11B-Vision-Instruct: Text, Images · Phi-4-mini: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama-3.2-11B-Vision-InstructPhi-4-mini
Price50%7692
Inputs & features30%5025
Context window20%2424
Overall100%58/10058/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Llama-3.2-11B-Vision-Instruct vs Phi-4-mini specifications side by side
SpecificationLlama-3.2-11B-Vision-InstructMetaPhi-4-miniMicrosoft
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.197$0.075 (best)
Output$0.51$0.30 (best)
Cached input——
Blended (3:1)$0.275$0.131 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Azure API
Limits
Context window128,000 tokens128,000 tokens
Max output4,096 tokens4,096 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model ID—phi-4-mini
API providers2 (best)1
ReleasedSep 25, 2024Dec 11, 2024
Knowledge cutoffDec 2023Oct 2023
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Llama-3.2-11B-Vision-Instruct$2.99
  • Phi-4-mini$1.35
04 — Questions

Which should you choose?

Which is better: Llama-3.2-11B-Vision-Instruct or Phi-4-mini?

It is close. Our weighted score puts them within a point (Phi-4-mini 58/100, Llama-3.2-11B-Vision-Instruct 58/100), so choose by what matters most for your work: Phi-4-mini on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Llama-3.2-11B-Vision-Instruct or Phi-4-mini?

Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). Llama-3.2-11B-Vision-Instruct costs $0.197 input / $0.51 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.131 per million tokens for Phi-4-mini versus $0.275 for Llama-3.2-11B-Vision-Instruct (2.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Llama-3.2-11B-Vision-Instruct has not been scored yet and Phi-4-mini has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.2-11B-Vision-Instruct and Phi-4-mini yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Llama-3.2-11B-Vision-Instruct and Phi-4-mini share the same 128,000-token context window. Maximum output per response: Llama-3.2-11B-Vision-Instruct up to 4,096, Phi-4-mini up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Llama-3.2-11B-Vision-Instruct accepts text and images; Phi-4-mini accepts text. Llama-3.2-11B-Vision-Instruct handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Phi-4-mini is the newest, released Dec 11, 2024. Llama-3.2-11B-Vision-Instruct came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-11B-Vision-Instruct Dec 2023, Phi-4-mini Oct 2023.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.

05 — Keep comparing

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