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Comparison · 2 models · Updated Oct 4, 2026

GPT-5.4 nano vs Kimi K2.7 Code

GPT-5.4 nano comes out ahead, 68 to 64 on our weighted score, and it is the cheaper option too.

  1. Our pick

    OpenAI

    GPT-5.4 nano

    Released Mar 17, 2026

    68/100
    • ECI145.8
    • Price$0.20 / $1.25
    • Context400K
    Full specs Remove GPT-5.4 nano

  2. Moonshot AI

    Kimi K2.7 Code

    Released Jun 12, 2026

    64/100
    • ECI150.0
    • Price$0.95 / $4.00
    • Context262K
    Full specs Remove Kimi K2.7 Code

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GPT-5.4 nano is our pick

GPT-5.4 nano is the better all-round choice, scoring 68/100 against Kimi K2.7 Code (64). It leads on price and context window. Kimi K2.7 Code wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityKimi K2.7 CodeCapabilities Index (ECI): Kimi K2.7 Code 150.0 · GPT-5.4 nano 145.8
  • Lowest priceGPT-5.4 nanoGPT-5.4 nano $0.463 · Kimi K2.7 Code $1.71 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.4 nanoGPT-5.4 nano 400,000 · Kimi K2.7 Code 262,144 tokens
  • Widest inputsKimi K2.7 CodeGPT-5.4 nano: Text, Images · Kimi K2.7 Code: Text, Images, Video
  • Self-hostingKimi K2.7 CodePublishes downloadable weights
How the score is built
MeasureWeightGPT-5.4 nanoKimi K2.7 Code
CapabilityCapabilities Index (ECI)50%7378
Price25%6639
Inputs & features15%7080
Context window10%4437
Overall100%68/10064/100
02 — Side by side

Every spec in one table

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

GPT-5.4 nano vs Kimi K2.7 Code specifications side by side
SpecificationGPT-5.4 nanoOpenAIKimi K2.7 CodeMoonshot AI
Capability
Capabilities Index (ECI)145.8150.0 (best)
ECI rank#75 of 148#49 of 148 (best)
GPQA DiamondGraduate-level science questions78.5%87.9% (best)
FrontierMath Tiers 1–3Research-level mathematics44.9%54.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics87.8%95.6% (best)
SimpleQA VerifiedShort factual questions11.7%36.5% (best)
Price per million tokens
Input$0.20 (best)$0.95
Output$1.25 (best)$4.00
Cached input$0.02 (best)$0.19
Blended (3:1)$0.463 (best)$1.71
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
PDFsNoNo
AudioNoNo
VideoNoYes
ReasoningYeslow · medium · high · xhighYes
Tool callingYesYes
Structured outputYesYes
Availability
WeightsProprietaryOpen
API model IDgpt-5.4-nanokimi-k2.7-code
API providers2651 (best)
ReleasedMar 17, 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-5.4 nano$4.50
  • Kimi K2.7 Code$17.50
04 — Questions

Which should you choose?

Which is better: GPT-5.4 nano or Kimi K2.7 Code?

GPT-5.4 nano is the better all-round choice, scoring 68/100 against Kimi K2.7 Code (64). It leads on price and context window. Kimi K2.7 Code wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-5.4 nano or Kimi K2.7 Code?

GPT-5.4 nano is cheaper at $0.20 input / $1.25 output per million tokens (official OpenAI API price). Kimi K2.7 Code costs $0.95 input / $4.00 output per million tokens (official Moonshot AI API price). At a typical mix of three input tokens to one output token, that is $0.463 per million tokens for GPT-5.4 nano versus $1.71 for Kimi K2.7 Code (3.7× as much).

Which scores higher on benchmarks?

Kimi K2.7 Code scores higher on the Capabilities Index (ECI): Kimi K2.7 Code 150.0 (#49 of 148) and GPT-5.4 nano 145.8 (#75 of 148). Their confidence ranges do not overlap (148.1–151.8 vs 143.2–147.7), so the gap is a real one. On individual benchmarks: GPQA Diamond — Kimi K2.7 Code 87.9%, GPT-5.4 nano 78.5%; FrontierMath Tiers 1–3 — Kimi K2.7 Code 54.0%, GPT-5.4 nano 44.9%; OTIS Mock AIME 2024–2025 — Kimi K2.7 Code 95.6%, GPT-5.4 nano 87.8%; SimpleQA Verified — Kimi K2.7 Code 36.5%, GPT-5.4 nano 11.7%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-5.4 nano and Kimi K2.7 Code yet, so there is no like-for-like coding score. On overall capability, Kimi K2.7 Code 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-5.4 nano has the largest context window at 400,000 tokens, against 262,144 for Kimi K2.7 Code. Maximum output per response: GPT-5.4 nano up to 128,000, Kimi K2.7 Code up to 262,144 tokens.

Which can read images, PDFs, audio or video?

GPT-5.4 nano accepts text and images; Kimi K2.7 Code accepts text, images and video. Kimi K2.7 Code handles the widest range of inputs.

Are any of these open source?

Kimi K2.7 Code publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.

Which is newer?

Kimi K2.7 Code is the newest, released Jun 12, 2026. GPT-5.4 nano came out Mar 17, 2026. Knowledge cutoff: GPT-5.4 nano 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.

05 — Keep comparing

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