ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Kimi K2 Thinking vs DeepSeek OCR 2

Kimi K2 Thinking comes out ahead, 42 to 32 on our weighted score.

  1. Our pick

    Moonshot AI

    Kimi K2 Thinking

    Released Nov 6, 2025

    42/100
    • ECI146.0
    • Price$0.60 / $2.50
    • Context262K
  2. DeepSeek

    DeepSeek OCR 2

    Released Jan 27, 2026

    32/100
    • ECI—
    • Price$0.89 / $1.47
    • Context8K
  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Kimi K2 Thinking is our pick

Kimi K2 Thinking is the better all-round choice, scoring 42/100 against DeepSeek OCR 2 (32). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceDeepSeek OCR 2DeepSeek OCR 2 $1.03 · Kimi K2 Thinking $1.07 per 1M tokens (3:1 blend)
  • Longest contextKimi K2 ThinkingKimi K2 Thinking 262,144 · DeepSeek OCR 2 8,192 tokens
  • Widest inputsDeepSeek OCR 2Kimi K2 Thinking: Text · DeepSeek OCR 2: Text, Images
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightKimi K2 ThinkingDeepSeek OCR 2
Price50%4849
Inputs & features30%3525
Context window20%370
Overall100%42/10032/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

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 DeepSeek OCR 2 specifications side by side
SpecificationKimi K2 ThinkingMoonshot AIDeepSeek OCR 2DeepSeek
Capability
Capabilities Index (ECI)146.0—
ECI rank#72 of 148—
GPQA DiamondGraduate-level science questions84.2%—
OTIS Mock AIME 2024–2025Competition mathematics83.1%—
Price per million tokens
Input$0.60 (best)$0.89
Output$2.50$1.47 (best)
Cached input——
Blended (3:1)$1.07$1.03 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 10 providersMedian of 1 providers
Limits
Context window262,144 tokens (best)8,192 tokens
Max output262,144 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesNo
Tool callingYesNo
Structured outputNoNo
Availability
WeightsOpenOpen
API model ID——
API providers10 (best)2
ReleasedNov 6, 2025Jan 27, 2026
Knowledge cutoffAug 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
  • DeepSeek OCR 2$11.83
04 — Questions

Which should you choose?

Which is better: Kimi K2 Thinking or DeepSeek OCR 2?

Kimi K2 Thinking is the better all-round choice, scoring 42/100 against DeepSeek OCR 2 (32). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Kimi K2 Thinking or DeepSeek OCR 2?

DeepSeek OCR 2 is cheaper at $0.89 input / $1.47 output per million tokens (median across 1 API provider). Kimi K2 Thinking costs $0.60 input / $2.50 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $1.03 per million tokens for DeepSeek OCR 2 versus $1.07 for Kimi K2 Thinking (1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Kimi K2 Thinking has an ECI of 146.0 and DeepSeek OCR 2 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2 Thinking and DeepSeek OCR 2 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that DeepSeek OCR 2 does not support tool calling, which most coding agents need.

Which has the bigger context window?

Kimi K2 Thinking has the largest context window at 262,144 tokens, against 8,192 for DeepSeek OCR 2. Maximum output per response: Kimi K2 Thinking up to 262,144, DeepSeek OCR 2 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Kimi K2 Thinking accepts text; DeepSeek OCR 2 accepts text and images. DeepSeek OCR 2 handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

DeepSeek OCR 2 is the newest, released Jan 27, 2026. Kimi K2 Thinking came out Nov 6, 2025. Knowledge cutoff: Kimi K2 Thinking Aug 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.