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Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5-VL 7B Instruct vs Phi-4-mini

Phi-4-mini comes out ahead, 58 to 51 on our weighted score, and it is the cheaper option too.

  1. Alibaba (Qwen)

    Qwen2.5-VL 7B Instruct

    Released Sep 2024

    51/100
    • ECI—
    • Price$0.35 / $1.05
    • Context131K
    Full specs Remove Qwen2.5-VL 7B Instruct
  2. Our pick

    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

Phi-4-mini is our pick

Phi-4-mini is the better all-round choice, scoring 58/100 against Qwen2.5-VL 7B Instruct (51). It leads on price. Qwen2.5-VL 7B Instruct wins on inputs & features. 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 · Qwen2.5-VL 7B Instruct $0.525 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5-VL 7B InstructQwen2.5-VL 7B Instruct 131,072 · Phi-4-mini 128,000 tokens
  • Widest inputsQwen2.5-VL 7B InstructQwen2.5-VL 7B 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
MeasureWeightQwen2.5-VL 7B InstructPhi-4-mini
Price50%6392
Inputs & features30%5025
Context window20%2424
Overall100%51/10058/100

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.

Qwen2.5-VL 7B Instruct vs Phi-4-mini specifications side by side
SpecificationQwen2.5-VL 7B InstructAlibaba (Qwen)Phi-4-miniMicrosoft
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.35$0.075 (best)
Output$1.05$0.30 (best)
Cached input——
Blended (3:1)$0.525$0.131 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Azure API
Limits
Context window131,072 tokens (best)128,000 tokens
Max output8,192 tokens (best)4,096 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDqwen2-5-vl-7b-instructphi-4-mini
API providers11
ReleasedSep 2024Dec 11, 2024
Knowledge cutoffApr 2024Oct 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.

  • Qwen2.5-VL 7B Instruct$5.60
  • Phi-4-mini$1.35
04 — Questions

Which should you choose?

Which is better: Qwen2.5-VL 7B Instruct or Phi-4-mini?

Phi-4-mini is the better all-round choice, scoring 58/100 against Qwen2.5-VL 7B Instruct (51). It leads on price. Qwen2.5-VL 7B Instruct wins on inputs & features. 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, Qwen2.5-VL 7B Instruct or Phi-4-mini?

Phi-4-mini is cheaper at $0.075 input / $0.30 output per million tokens (official Azure API price). Qwen2.5-VL 7B Instruct costs $0.35 input / $1.05 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.131 per million tokens for Phi-4-mini versus $0.525 for Qwen2.5-VL 7B Instruct (4× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen2.5-VL 7B 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 Qwen2.5-VL 7B 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?

Qwen2.5-VL 7B Instruct has the largest context window at 131,072 tokens, against 128,000 for Phi-4-mini. Maximum output per response: Qwen2.5-VL 7B Instruct up to 8,192, Phi-4-mini up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5-VL 7B Instruct accepts text and images; Phi-4-mini accepts text. Qwen2.5-VL 7B 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. Qwen2.5-VL 7B Instruct came out Sep 2024. Knowledge cutoff: Qwen2.5-VL 7B Instruct Apr 2024, 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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