ZMIME
Comparison · 3 models · Updated Oct 4, 2026

o4-mini vs Qwen3.5 Plus vs Gemini 2.5 Pro

Qwen3.5 Plus comes out ahead, 66 to 63 and 59 on our weighted score, and it is the cheaper option too.

  1. OpenAI

    o4-mini

    Released Apr 16, 2025Deprecated

    59/100
    • ECI145.6
    • Price$1.10 / $4.40
    • Context200K
  2. Our pick

    Alibaba (Qwen)

    Qwen3.5 Plus

    Released Feb 16, 2026

    66/100
    • ECI146.8
    • Price$0.40 / $2.40
    • Context1M
  3. Google

    Gemini 2.5 Pro

    Released Jun 17, 2025

    63/100
    • ECI145.3
    • Price$1.25 / $10.00
    • Context1.05M
01 — Verdict

Qwen3.5 Plus is our pick

Qwen3.5 Plus is the better all-round choice, scoring 66/100 against Gemini 2.5 Pro (63) and o4-mini (59). It leads on price. Gemini 2.5 Pro wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 PlusCapabilities Index (ECI): Qwen3.5 Plus 146.8 · o4-mini 145.6 · Gemini 2.5 Pro 145.3
  • Lowest priceQwen3.5 PlusQwen3.5 Plus $0.90 · o4-mini $1.93 · Gemini 2.5 Pro $3.44 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · Qwen3.5 Plus 1,000,000 · o4-mini 200,000 tokens
  • Widest inputsGemini 2.5 Proo4-mini: Text, Images · Qwen3.5 Plus: Text, Images, Video · Gemini 2.5 Pro: Text, Images, PDFs, Audio, Video
  • Self-hostingNo open weightsAll three are available only through APIs
How the score is built
MeasureWeighto4-miniQwen3.5 PlusGemini 2.5 Pro
CapabilityCapabilities Index (ECI)50%737472
Price25%365224
Inputs & features15%7070100
Context window10%326061
Overall100%59/10066/10063/100
02 — Side by side

Every spec in one table

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

o4-mini vs Qwen3.5 Plus vs Gemini 2.5 Pro specifications side by side
Specificationo4-miniOpenAIQwen3.5 PlusAlibaba (Qwen)Gemini 2.5 ProGoogle
Capability
Capabilities Index (ECI)145.6146.8 (best)145.3
ECI rank#76 of 148#65 of 148 (best)#78 of 148
GPQA DiamondGraduate-level science questions79.6%84.9%85.3% (best)
FrontierMath Tiers 1–3Research-level mathematics36.1% (best)—24.6%
OTIS Mock AIME 2024–2025Competition mathematics81.7%86.7% (best)84.7%
SWE-bench VerifiedFixing real GitHub issues——57.6%
SimpleQA VerifiedShort factual questions19.6%25.4% (best)—
Price per million tokens
Input$1.10$0.40 (best)$1.25
Output$4.40$2.40 (best)$10.00
Cached input$0.275—$0.125 (best)
Blended (3:1)$1.93$0.90 (best)$3.44
Long-context rateSame rateSame rateOver 200K: $2.50 / $15.00
Price sourceOfficial OpenAI APIOfficial Alibaba APIOfficial Google API
Limits
Context window200,000 tokens1,000,000 tokens1,048,576 tokens (best)
Max output100,000 tokens (best)65,536 tokens65,536 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoYes
AudioNoNoYes
VideoNoYesYes
ReasoningYeslow · medium · highYesYes
Tool callingYesYesYes
Structured outputYesNoYes
Availability
WeightsProprietaryProprietaryProprietary
API model IDo4-miniqwen3.5-plusgemini-2.5-pro
API providers191022 (best)
ReleasedApr 16, 2025Feb 16, 2026Jun 17, 2025
Knowledge cutoffMay 2024Apr 2025Jan 2025
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.

  • o4-mini$19.80
  • Qwen3.5 Plus$8.80
  • Gemini 2.5 Pro$32.50
04 — Questions

Which should you choose?

Which is better: o4-mini, Qwen3.5 Plus or Gemini 2.5 Pro?

Qwen3.5 Plus is the better all-round choice, scoring 66/100 against Gemini 2.5 Pro (63) and o4-mini (59). It leads on price. Gemini 2.5 Pro wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, o4-mini, Qwen3.5 Plus or Gemini 2.5 Pro?

Qwen3.5 Plus is cheaper at $0.40 input / $2.40 output per million tokens (official Alibaba API price). o4-mini costs $1.10 input / $4.40 output per million tokens (official OpenAI API price); Gemini 2.5 Pro costs $1.25 input / $10.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.90 per million tokens for Qwen3.5 Plus versus $1.93 for o4-mini (2.1× as much) and $3.44 for Gemini 2.5 Pro (3.8× as much).

Which scores higher on benchmarks?

Qwen3.5 Plus scores higher on the Capabilities Index (ECI): Qwen3.5 Plus 146.8 (#65 of 148), o4-mini 145.6 (#76 of 148) and Gemini 2.5 Pro 145.3 (#78 of 148). The confidence ranges of the top two overlap (144.6–148.1 vs 143.0–147.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemini 2.5 Pro 85.3%, Qwen3.5 Plus 84.9%, o4-mini 79.6%; OTIS Mock AIME 2024–2025 — Qwen3.5 Plus 86.7%, Gemini 2.5 Pro 84.7%, o4-mini 81.7%.

Which is better for coding?

There are no published SWE-bench Verified results for o4-mini and Qwen3.5 Plus yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 Plus 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?

Gemini 2.5 Pro has the largest context window at 1,048,576 tokens, against 1,000,000 for Qwen3.5 Plus and 200,000 for o4-mini. Maximum output per response: o4-mini up to 100,000, Qwen3.5 Plus up to 65,536, Gemini 2.5 Pro up to 65,536 tokens.

Which can read images, PDFs, audio or video?

o4-mini accepts text and images; Qwen3.5 Plus accepts text, images and video; Gemini 2.5 Pro accepts text, images, PDFs, audio and video. Gemini 2.5 Pro handles the widest range of inputs.

Are any of these open source?

No. o4-mini, Qwen3.5 Plus and Gemini 2.5 Pro are proprietary and only available through APIs and apps.

Which is newer?

Qwen3.5 Plus is the newest, released Feb 16, 2026. Gemini 2.5 Pro came out Jun 17, 2025; o4-mini came out Apr 16, 2025. Knowledge cutoff: o4-mini May 2024, Qwen3.5 Plus Apr 2025, Gemini 2.5 Pro Jan 2025.

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.