ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Kimi K2 Thinking vs o3

Too close to call on our weighted score (o3 58, 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

    o3

    Released Apr 16, 2025

    58/100
    • ECI146.9
    • Price$2.00 / $8.00
    • Context200K
    Full specs Remove o3

  3. Add a model

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (o3 58/100, Kimi K2 Thinking 58/100), so choose by what matters most for your work: o3 for raw capability, Kimi K2 Thinking on price and Kimi K2 Thinking for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • Capabilityo3Capabilities Index (ECI): o3 146.9 · Kimi K2 Thinking 146.0
  • Lowest priceKimi K2 ThinkingKimi K2 Thinking $1.07 · o3 $3.50 per 1M tokens (3:1 blend)
  • Longest contextKimi K2 ThinkingKimi K2 Thinking 262,144 · o3 200,000 tokens
  • Widest inputso3Kimi K2 Thinking: Text · o3: Text, Images, PDFs
  • Self-hostingKimi K2 ThinkingPublishes downloadable weights
How the score is built
MeasureWeightKimi K2 Thinkingo3
CapabilityCapabilities Index (ECI)50%7374
Price25%4824
Inputs & features15%3580
Context window10%3732
Overall100%58/10058/100
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 o3 specifications side by side
SpecificationKimi K2 ThinkingMoonshot AIo3OpenAI
Capability
Capabilities Index (ECI)146.0146.9 (best)
ECI rank#72 of 148#63 of 148 (best)
GPQA DiamondGraduate-level science questions84.2% (best)81.8%
FrontierMath Tiers 1–3Research-level mathematics—33.3%
OTIS Mock AIME 2024–2025Competition mathematics83.1%84.4% (best)
SWE-bench VerifiedFixing real GitHub issues—62.3%
SimpleQA VerifiedShort factual questions—49.4%
Price per million tokens
Input$0.60 (best)$2.00
Output$2.50 (best)$8.00
Cached input—$0.50
Blended (3:1)$1.07 (best)$3.50
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
PDFsNoYes
AudioNoNo
VideoNoNo
ReasoningYesYeslow · medium · high
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenProprietary
API model ID—o3
API providers1018 (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
  • o3$36.00
04 — Questions

Which should you choose?

Which is better: Kimi K2 Thinking or o3?

It is close. Our weighted score puts them within a point (o3 58/100, Kimi K2 Thinking 58/100), so choose by what matters most for your work: o3 for raw capability, Kimi K2 Thinking on price and Kimi K2 Thinking for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Kimi K2 Thinking or o3?

Kimi K2 Thinking is cheaper at $0.60 input / $2.50 output per million tokens (median across 10 API providers). o3 costs $2.00 input / $8.00 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 $3.50 for o3 (3.3× as much).

Which scores higher on benchmarks?

o3 scores higher on the Capabilities Index (ECI): o3 146.9 (#63 of 148) and Kimi K2 Thinking 146.0 (#72 of 148). The confidence ranges of the top two overlap (144.9–148.6 vs 143.4–147.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Kimi K2 Thinking 84.2%, o3 81.8%; OTIS Mock AIME 2024–2025 — o3 84.4%, Kimi K2 Thinking 83.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2 Thinking yet, so there is no like-for-like coding score. On overall capability, o3 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 o3. Maximum output per response: Kimi K2 Thinking up to 262,144, o3 up to 100,000 tokens.

Which can read images, PDFs, audio or video?

Kimi K2 Thinking accepts text; o3 accepts text, images and PDFs. o3 handles the widest range of inputs.

Are any of these open source?

Kimi K2 Thinking publishes its weights and can be self-hosted; o3 is proprietary.

Which is newer?

Kimi K2 Thinking is the newest, released Nov 6, 2025. o3 came out Apr 16, 2025. Knowledge cutoff: Kimi K2 Thinking Aug 2024, o3 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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