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Comparison · 3 models · Updated Oct 4, 2026

GPT-4o vs GPT-4o mini vs Qwen2.5 72B Instruct

GPT-4o mini comes out ahead, 56 to 43 and 40 on our weighted score, and it is the cheaper option too.

  1. OpenAI

    GPT-4o

    Released May 13, 2024

    43/100
    • ECI129.0
    • Price$2.50 / $10.00
    • Context128K
  2. Our pick

    OpenAI

    GPT-4o mini

    Released Jul 18, 2024

    56/100
    • ECI126.6
    • Price$0.15 / $0.60
    • Context128K
  3. Alibaba (Qwen)

    Qwen2.5 72B Instruct

    Released Sep 19, 2024

    40/100
    • ECI129.0
    • Price$1.40 / $5.60
    • Context131K
01 — Verdict

GPT-4o mini is our pick

GPT-4o mini is the better all-round choice, scoring 56/100 against GPT-4o (43) and Qwen2.5 72B Instruct (40). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 72B InstructCapabilities Index (ECI): Qwen2.5 72B Instruct 129.0 · GPT-4o 129.0 · GPT-4o mini 126.6
  • Lowest priceGPT-4o miniGPT-4o mini $0.263 · Qwen2.5 72B Instruct $2.45 · GPT-4o $4.38 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 72B InstructQwen2.5 72B Instruct 131,072 · GPT-4o 128,000 · GPT-4o mini 128,000 tokens
  • Widest inputsGPT-4o and GPT-4o miniGPT-4o: Text, Images, PDFs · GPT-4o mini: Text, Images, PDFs · Qwen2.5 72B Instruct: Text
  • Self-hostingQwen2.5 72B InstructPublishes downloadable weights
How the score is built
MeasureWeightGPT-4oGPT-4o miniQwen2.5 72B Instruct
CapabilityCapabilities Index (ECI)50%524952
Price25%197731
Inputs & features15%707025
Context window10%242424
Overall100%43/10056/10040/100
02 — Side by side

Every spec in one table

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

GPT-4o vs GPT-4o mini vs Qwen2.5 72B Instruct specifications side by side
SpecificationGPT-4oOpenAIGPT-4o miniOpenAIQwen2.5 72B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)129.0126.6129.0 (best)
ECI rank#129 of 148#135 of 148#128 of 148 (best)
GPQA DiamondGraduate-level science questions48.9%37.7%49.2% (best)
FrontierMath Tiers 1–3Research-level mathematics—0.7%—
OTIS Mock AIME 2024–2025Competition mathematics6.3%6.9%8.1% (best)
SimpleQA VerifiedShort factual questions—8.3%—
Price per million tokens
Input$2.50$0.15 (best)$1.40
Output$10.00$0.60 (best)$5.60
Cached input$1.25$0.075 (best)—
Blended (3:1)$4.38$0.263 (best)$2.45
Long-context rateSame rateSame rateSame rate
Price sourceOfficial OpenAI APIOfficial OpenAI APIOfficial Alibaba API
Limits
Context window128,000 tokens128,000 tokens131,072 tokens (best)
Max output16,384 tokens (best)16,384 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsYesYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsProprietaryProprietaryOpen
API model IDgpt-4ogpt-4o-miniqwen2-5-72b-instruct
API providers1921 (best)1
ReleasedMay 13, 2024Jul 18, 2024Sep 19, 2024
Knowledge cutoffSep 2023Sep 2023Apr 2024
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.

  • GPT-4o$45.00
  • GPT-4o mini$2.70
  • Qwen2.5 72B Instruct$25.20
04 — Questions

Which should you choose?

Which is better: GPT-4o, GPT-4o mini or Qwen2.5 72B Instruct?

GPT-4o mini is the better all-round choice, scoring 56/100 against GPT-4o (43) and Qwen2.5 72B Instruct (40). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-4o, GPT-4o mini or Qwen2.5 72B Instruct?

GPT-4o mini is cheaper at $0.15 input / $0.60 output per million tokens (official OpenAI API price). Qwen2.5 72B Instruct costs $1.40 input / $5.60 output per million tokens (official Alibaba API price); GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT-4o mini versus $2.45 for Qwen2.5 72B Instruct (9.3× as much) and $4.38 for GPT-4o (17× as much).

Which scores higher on benchmarks?

Qwen2.5 72B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 72B Instruct 129.0 (#128 of 148), GPT-4o 129.0 (#129 of 148) and GPT-4o mini 126.6 (#135 of 148). The confidence ranges of the top two overlap (123.8–130.7 vs 124.2–131.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 72B Instruct 49.2%, GPT-4o 48.9%, GPT-4o mini 37.7%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, GPT-4o mini 6.9%, GPT-4o 6.3%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-4o, GPT-4o mini and Qwen2.5 72B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 72B Instruct leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen2.5 72B Instruct has the largest context window at 131,072 tokens, against 128,000 for GPT-4o and 128,000 for GPT-4o mini. Maximum output per response: GPT-4o up to 16,384, GPT-4o mini up to 16,384, Qwen2.5 72B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

GPT-4o accepts text, images and PDFs; GPT-4o mini accepts text, images and PDFs; Qwen2.5 72B Instruct accepts text. GPT-4o handles the widest range of inputs.

Are any of these open source?

Qwen2.5 72B Instruct publishes its weights and can be self-hosted; GPT-4o and GPT-4o mini is proprietary.

Which is newer?

Qwen2.5 72B Instruct is the newest, released Sep 19, 2024. GPT-4o mini came out Jul 18, 2024; GPT-4o came out May 13, 2024. Knowledge cutoff: GPT-4o Sep 2023, GPT-4o mini Sep 2023, Qwen2.5 72B Instruct Apr 2024.

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.