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Comparison · 2 models · Updated Oct 4, 2026

Kimi K2 Thinking vs o4-mini

Too close to call on our weighted score (o4-mini 59, Kimi K2 Thinking 58). The right pick depends on what you value most.

  1. 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

  2. OpenAI

    o4-mini

    Released Apr 16, 2025Deprecated

    59/100
    • ECI145.6
    • Price$1.10 / $4.40
    • Context200K
    Full specs Remove o4-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 2 points (o4-mini 59/100, Kimi K2 Thinking 58/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability. 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
  • Lowest priceKimi K2 ThinkingKimi K2 Thinking $1.07 · o4-mini $1.93 per 1M tokens (3:1 blend)
  • Longest contextKimi K2 ThinkingKimi K2 Thinking 262,144 · o4-mini 200,000 tokens
  • Widest inputso4-miniKimi K2 Thinking: Text · o4-mini: Text, Images
  • Self-hostingKimi K2 ThinkingPublishes downloadable weights
How the score is built
MeasureWeightKimi K2 Thinkingo4-mini
CapabilityCapabilities Index (ECI)50%7373
Price25%4836
Inputs & features15%3570
Context window10%3732
Overall100%58/10059/100
02 — Side by side

Every spec in one table

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

Kimi K2 Thinking vs o4-mini specifications side by side
SpecificationKimi K2 ThinkingMoonshot AIo4-miniOpenAI
Capability
Capabilities Index (ECI)146.0 (best)145.6
ECI rank#72 of 148 (best)#76 of 148
GPQA DiamondGraduate-level science questions84.2% (best)79.6%
FrontierMath Tiers 1–3Research-level mathematics—36.1%
OTIS Mock AIME 2024–2025Competition mathematics83.1% (best)81.7%
SimpleQA VerifiedShort factual questions—19.6%
Price per million tokens
Input$0.60 (best)$1.10
Output$2.50 (best)$4.40
Cached input—$0.275
Blended (3:1)$1.07 (best)$1.93
Long-context rateSame rateSame rate
Price sourceMedian of 10 providersOfficial OpenAI API
Limits
Context window262,144 tokens (best)200,000 tokens
Max output262,144 tokens (best)100,000 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesYeslow · medium · high
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenProprietary
API model ID—o4-mini
API providers1019 (best)
ReleasedNov 6, 2025Apr 16, 2025
Knowledge cutoffAug 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.

  • Kimi K2 Thinking$11.00
  • o4-mini$19.80
04 — Questions

Which should you choose?

Which is better: Kimi K2 Thinking or o4-mini?

It is close. Our weighted score puts them within 2 points (o4-mini 59/100, Kimi K2 Thinking 58/100), so choose by what matters most for your work: Kimi K2 Thinking for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, 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). 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).

Which scores higher on benchmarks?

Kimi K2 Thinking scores higher on the Capabilities Index (ECI): Kimi K2 Thinking 146.0 (#72 of 148) and o4-mini 145.6 (#76 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 — Kimi K2 Thinking 84.2%, o4-mini 79.6%; OTIS Mock AIME 2024–2025 — 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. Both support tool calling for agent workflows.

Which has the bigger context window?

Kimi K2 Thinking has the largest context window at 262,144 tokens, against 200,000 for o4-mini. Maximum output per response: Kimi K2 Thinking up to 262,144, o4-mini up to 100,000 tokens.

Which can read images, PDFs, audio or video?

Kimi K2 Thinking accepts text; o4-mini accepts text and images. o4-mini handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Kimi K2 Thinking is the newest, released Nov 6, 2025. o4-mini came out Apr 16, 2025. Knowledge cutoff: 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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