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Comparison · 3 models · Updated Oct 4, 2026

Gemini 2.5 Pro vs Kimi K2 Thinking vs o4-mini

Gemini 2.5 Pro comes out ahead, 63 to 59 and 58 on our weighted score, though Kimi K2 Thinking is 3.2× cheaper per token.

  1. Our pick

    Google

    Gemini 2.5 Pro

    Released Jun 17, 2025

    63/100
    • ECI145.3
    • Price$1.25 / $10.00
    • Context1.05M
    Full specs Remove Gemini 2.5 Pro

  2. Moonshot AI

    Kimi K2 Thinking

    Released Nov 6, 2025

    58/100
    • ECI146.0
    • Price$0.60 / $2.50
    • Context262K
    Full specs Remove Kimi K2 Thinking

  3. OpenAI

    o4-mini

    Released Apr 16, 2025Deprecated

    59/100
    • ECI145.6
    • Price$1.10 / $4.40
    • Context200K
    Full specs Remove o4-mini
01 — Verdict

Gemini 2.5 Pro is our pick

Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against o4-mini (59) and Kimi K2 Thinking (58). It leads on inputs & features and context window. Kimi K2 Thinking wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityKimi K2 ThinkingCapabilities Index (ECI): Kimi K2 Thinking 146.0 · o4-mini 145.6 · Gemini 2.5 Pro 145.3
  • Lowest priceKimi K2 ThinkingKimi K2 Thinking $1.07 · 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 · Kimi K2 Thinking 262,144 · o4-mini 200,000 tokens
  • Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · Kimi K2 Thinking: Text · o4-mini: Text, Images
  • Self-hostingKimi K2 ThinkingPublishes downloadable weights
How the score is built
MeasureWeightGemini 2.5 ProKimi K2 Thinkingo4-mini
CapabilityCapabilities Index (ECI)50%727373
Price25%244836
Inputs & features15%1003570
Context window10%613732
Overall100%63/10058/10059/100
02 — Side by side

Every spec in one table

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

Gemini 2.5 Pro vs Kimi K2 Thinking vs o4-mini specifications side by side
SpecificationGemini 2.5 ProGoogleKimi K2 ThinkingMoonshot AIo4-miniOpenAI
Capability
Capabilities Index (ECI)145.3146.0 (best)145.6
ECI rank#78 of 148#72 of 148 (best)#76 of 148
GPQA DiamondGraduate-level science questions85.3% (best)84.2%79.6%
FrontierMath Tiers 1–3Research-level mathematics24.6%—36.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics84.7% (best)83.1%81.7%
SWE-bench VerifiedFixing real GitHub issues57.6%——
SimpleQA VerifiedShort factual questions——19.6%
Price per million tokens
Input$1.25$0.60 (best)$1.10
Output$10.00$2.50 (best)$4.40
Cached input$0.125 (best)—$0.275
Blended (3:1)$3.44$1.07 (best)$1.93
Long-context rateOver 200K: $2.50 / $15.00Same rateSame rate
Price sourceOfficial Google APIMedian of 10 providersOfficial OpenAI API
Limits
Context window1,048,576 tokens (best)262,144 tokens200,000 tokens
Max output65,536 tokens262,144 tokens (best)100,000 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsYesNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesYesYeslow · medium · high
Tool callingYesYesYes
Structured outputYesNoYes
Availability
WeightsProprietaryOpenProprietary
API model IDgemini-2.5-pro—o4-mini
API providers22 (best)1019
ReleasedJun 17, 2025Nov 6, 2025Apr 16, 2025
Knowledge cutoffJan 2025Aug 2024May 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.

  • Gemini 2.5 Pro$32.50
  • Kimi K2 Thinking$11.00
  • o4-mini$19.80
04 — Questions

Which should you choose?

Which is better: Gemini 2.5 Pro, Kimi K2 Thinking or o4-mini?

Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against o4-mini (59) and Kimi K2 Thinking (58). It leads on inputs & features and context window. Kimi K2 Thinking wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Gemini 2.5 Pro, Kimi K2 Thinking or o4-mini?

Kimi K2 Thinking is cheaper at $0.60 input / $2.50 output per million tokens (median across 10 API providers). 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 $1.07 per million tokens for Kimi K2 Thinking versus $1.93 for o4-mini (1.8× as much) and $3.44 for Gemini 2.5 Pro (3.2× as much).

Which scores higher on benchmarks?

Kimi K2 Thinking scores higher on the Capabilities Index (ECI): Kimi K2 Thinking 146.0 (#72 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 (143.4–147.6 vs 143.0–147.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemini 2.5 Pro 85.3%, Kimi K2 Thinking 84.2%, o4-mini 79.6%; OTIS Mock AIME 2024–2025 — Gemini 2.5 Pro 84.7%, Kimi K2 Thinking 83.1%, o4-mini 81.7%.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2 Thinking and o4-mini yet, so there is no like-for-like coding score. On overall capability, Kimi K2 Thinking 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 262,144 for Kimi K2 Thinking and 200,000 for o4-mini. Maximum output per response: Gemini 2.5 Pro up to 65,536, Kimi K2 Thinking up to 262,144, o4-mini up to 100,000 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Pro accepts text, images, PDFs, audio and video; Kimi K2 Thinking accepts text; o4-mini accepts text and images. Gemini 2.5 Pro handles the widest range of inputs.

Are any of these open source?

Kimi K2 Thinking publishes its weights and can be self-hosted; Gemini 2.5 Pro and o4-mini is proprietary.

Which is newer?

Kimi K2 Thinking is the newest, released Nov 6, 2025. Gemini 2.5 Pro came out Jun 17, 2025; o4-mini came out Apr 16, 2025. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, Kimi K2 Thinking Aug 2024, o4-mini May 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.

05 — Keep comparing

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