ZMIME
Comparison · 2 models · Updated Oct 4, 2026

GPT-5.3 Codex vs Kimi K2.7 Code

Too close to call on our weighted score (Kimi K2.7 Code 64, GPT-5.3 Codex 64). The right pick depends on what you value most.

  1. OpenAI

    GPT-5.3 Codex

    Released Feb 5, 2026

    64/100
    • ECI156.8
    • Price$1.75 / $14.00
    • Context400K
  2. Moonshot AI

    Kimi K2.7 Code

    Released Jun 12, 2026

    64/100
    • ECI150.0
    • Price$0.95 / $4.00
    • Context262K
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01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Kimi K2.7 Code 64/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: GPT-5.3 Codex for raw capability and Kimi K2.7 Code on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5.3 CodexCapabilities Index (ECI): GPT-5.3 Codex 156.8 · Kimi K2.7 Code 150.0
  • Lowest priceKimi K2.7 CodeKimi K2.7 Code $1.71 · GPT-5.3 Codex $4.81 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.3 CodexGPT-5.3 Codex 400,000 · Kimi K2.7 Code 262,144 tokens
  • Widest inputsSame inputsGPT-5.3 Codex: Text, Images, PDFs · Kimi K2.7 Code: Text, Images, Video
  • Self-hostingKimi K2.7 CodePublishes downloadable weights
How the score is built
MeasureWeightGPT-5.3 CodexKimi K2.7 Code
CapabilityCapabilities Index (ECI)50%8778
Price25%1839
Inputs & features15%8080
Context window10%4437
Overall100%64/10064/100
02 — Side by side

Every spec in one table

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

GPT-5.3 Codex vs Kimi K2.7 Code specifications side by side
SpecificationGPT-5.3 CodexOpenAIKimi K2.7 CodeMoonshot AI
Capability
Capabilities Index (ECI)156.8 (best)150.0
ECI rank#18 of 148 (best)#49 of 148
GPQA DiamondGraduate-level science questions—87.9%
FrontierMath Tiers 1–3Research-level mathematics—54.0%
OTIS Mock AIME 2024–2025Competition mathematics—95.6%
SWE-bench VerifiedFixing real GitHub issues74.8%—
SimpleQA VerifiedShort factual questions—36.5%
Price per million tokens
Input$1.75$0.95 (best)
Output$14.00$4.00 (best)
Cached input$0.175 (best)$0.19
Blended (3:1)$4.81$1.71 (best)
Long-context rateSame rateSame rate
Price sourceOfficial OpenAI APIOfficial Moonshot AI API
Limits
Context window400,000 tokens (best)262,144 tokens
Max output128,000 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsYesNo
AudioNoNo
VideoNoYes
ReasoningYeslow · medium · high · xhighYes
Tool callingYesYes
Structured outputYesYes
Availability
WeightsProprietaryOpen
API model IDgpt-5.3-codexkimi-k2.7-code
API providers1951 (best)
ReleasedFeb 5, 2026Jun 12, 2026
Knowledge cutoffAug 31, 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.

  • GPT-5.3 Codex$45.50
  • Kimi K2.7 Code$17.50
04 — Questions

Which should you choose?

Which is better: GPT-5.3 Codex or Kimi K2.7 Code?

It is close. Our weighted score puts them within a point (Kimi K2.7 Code 64/100, GPT-5.3 Codex 64/100), so choose by what matters most for your work: GPT-5.3 Codex for raw capability and Kimi K2.7 Code on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-5.3 Codex or Kimi K2.7 Code?

Kimi K2.7 Code is cheaper at $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). GPT-5.3 Codex costs $1.75 input / $14.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.71 per million tokens for Kimi K2.7 Code versus $4.81 for GPT-5.3 Codex (2.8× as much).

Which scores higher on benchmarks?

GPT-5.3 Codex scores higher on the Capabilities Index (ECI): GPT-5.3 Codex 156.8 (#18 of 148) and Kimi K2.7 Code 150.0 (#49 of 148). Their confidence ranges do not overlap (153.5–160.8 vs 148.1–151.8), so the gap is a real one.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2.7 Code yet, so there is no like-for-like coding score. On overall capability, GPT-5.3 Codex 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?

GPT-5.3 Codex has the largest context window at 400,000 tokens, against 262,144 for Kimi K2.7 Code. Maximum output per response: GPT-5.3 Codex up to 128,000, Kimi K2.7 Code up to 262,144 tokens.

Which can read images, PDFs, audio or video?

GPT-5.3 Codex accepts text, images and PDFs; Kimi K2.7 Code accepts text, images and video. They handle the same number of input types.

Are any of these open source?

Kimi K2.7 Code publishes its weights and can be self-hosted; GPT-5.3 Codex is proprietary.

Which is newer?

Kimi K2.7 Code is the newest, released Jun 12, 2026. GPT-5.3 Codex came out Feb 5, 2026. Knowledge cutoff: GPT-5.3 Codex Aug 31, 2025, Kimi K2.7 Code 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.