ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GPT-5.6 Sol vs Grok 4.3 vs Kimi K2.7 Code

Too close to call on our weighted score (Grok 4.3 67, GPT-5.6 Sol 66, Kimi K2.7 Code 64). The right pick depends on what you value most.

  1. OpenAI

    GPT-5.6 Sol

    Released Jul 9, 2026

    66/100
    • ECI161.8
    • Price$4.00 / $20.00
    • Context1.05M
  2. xAI

    Grok 4.3

    Released Apr 17, 2026

    67/100
    • ECI149.2
    • Price$1.25 / $2.50
    • Context1M
  3. Moonshot AI

    Kimi K2.7 Code

    Released Jun 12, 2026

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

Too close to call

It is close. Our weighted score puts them within a point (Grok 4.3 67/100, GPT-5.6 Sol 66/100, Kimi K2.7 Code 64/100), so choose by what matters most for your work: GPT-5.6 Sol for raw capability and Grok 4.3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-5.6 SolCapabilities Index (ECI): GPT-5.6 Sol 161.8 · Kimi K2.7 Code 150.0 · Grok 4.3 149.2
  • Lowest priceGrok 4.3Grok 4.3 $1.56 · Kimi K2.7 Code $1.71 · GPT-5.6 Sol $8.00 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.6 SolGPT-5.6 Sol 1,050,000 · Grok 4.3 1,000,000 · Kimi K2.7 Code 262,144 tokens
  • Widest inputsSame inputsGPT-5.6 Sol: Text, Images, PDFs · Grok 4.3: Text, Images, PDFs · Kimi K2.7 Code: Text, Images, Video
  • Self-hostingKimi K2.7 CodePublishes downloadable weights
How the score is built
MeasureWeightGPT-5.6 SolGrok 4.3Kimi K2.7 Code
CapabilityCapabilities Index (ECI)50%937778
Price25%74139
Inputs & features15%808080
Context window10%616037
Overall100%66/10067/10064/100
02 — Side by side

Every spec in one table

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

GPT-5.6 Sol vs Grok 4.3 vs Kimi K2.7 Code specifications side by side
SpecificationGPT-5.6 SolOpenAIGrok 4.3xAIKimi K2.7 CodeMoonshot AI
Capability
Capabilities Index (ECI)161.8 (best)149.2150.0
ECI rank#8 of 148 (best)#55 of 148#49 of 148
GPQA DiamondGraduate-level science questions93.5% (best)88.8%87.9%
FrontierMath Tiers 1–3Research-level mathematics89.1% (best)42.8%54.0%
OTIS Mock AIME 2024–2025Competition mathematics100% (best)93.3%95.6%
SimpleQA VerifiedShort factual questions69.7% (best)33.2%36.5%
Price per million tokens
Input$4.00$1.25$0.95 (best)
Output$20.00$2.50 (best)$4.00
Cached input$0.40$0.20$0.19 (best)
Blended (3:1)$8.00$1.56 (best)$1.71
Long-context rateOver 272K: $8.00 / $30.00Over 200K: $2.50 / $5.00Same rate
Price sourceOfficial OpenAI APIOfficial xAI APIOfficial Moonshot AI API
Limits
Context window1,050,000 tokens (best)1,000,000 tokens262,144 tokens
Max output128,000 tokens30,000 tokens262,144 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsYesYesNo
AudioNoNoNo
VideoNoNoYes
ReasoningYeslow · medium · high · xhigh · maxYeslow · medium · highYes
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsProprietaryProprietaryOpen
API model IDgpt-5.6-solgrok-4.3kimi-k2.7-code
API providers402751 (best)
ReleasedJul 9, 2026Apr 17, 2026Jun 12, 2026
Knowledge cutoffFeb 16, 2026—Jan 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-5.6 Sol$80.00
  • Grok 4.3$17.50
  • Kimi K2.7 Code$17.50
04 — Questions

Which should you choose?

Which is better: GPT-5.6 Sol, Grok 4.3 or Kimi K2.7 Code?

It is close. Our weighted score puts them within a point (Grok 4.3 67/100, GPT-5.6 Sol 66/100, Kimi K2.7 Code 64/100), so choose by what matters most for your work: GPT-5.6 Sol for raw capability and Grok 4.3 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-5.6 Sol, Grok 4.3 or Kimi K2.7 Code?

Grok 4.3 is cheaper at $1.25 input / $2.50 output per million tokens (official xAI API price). Kimi K2.7 Code costs $0.95 input / $4.00 output per million tokens (official Moonshot AI API price); GPT-5.6 Sol costs $4.00 input / $20.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.56 per million tokens for Grok 4.3 versus $1.71 for Kimi K2.7 Code (1.1× as much) and $8.00 for GPT-5.6 Sol (5.1× as much).

Which scores higher on benchmarks?

GPT-5.6 Sol scores higher on the Capabilities Index (ECI): GPT-5.6 Sol 161.8 (#8 of 148), Kimi K2.7 Code 150.0 (#49 of 148) and Grok 4.3 149.2 (#55 of 148). Their confidence ranges do not overlap (159.3–165.3 vs 148.1–151.8), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-5.6 Sol 93.5%, Grok 4.3 88.8%, Kimi K2.7 Code 87.9%; FrontierMath Tiers 1–3 — GPT-5.6 Sol 89.1%, Kimi K2.7 Code 54.0%, Grok 4.3 42.8%; OTIS Mock AIME 2024–2025 — GPT-5.6 Sol 100%, Kimi K2.7 Code 95.6%, Grok 4.3 93.3%; SimpleQA Verified — GPT-5.6 Sol 69.7%, Kimi K2.7 Code 36.5%, Grok 4.3 33.2%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-5.6 Sol, Grok 4.3 and Kimi K2.7 Code yet, so there is no like-for-like coding score. On overall capability, GPT-5.6 Sol leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

GPT-5.6 Sol has the largest context window at 1,050,000 tokens, against 1,000,000 for Grok 4.3 and 262,144 for Kimi K2.7 Code. Maximum output per response: GPT-5.6 Sol up to 128,000, Grok 4.3 up to 30,000, Kimi K2.7 Code up to 262,144 tokens.

Which can read images, PDFs, audio or video?

GPT-5.6 Sol accepts text, images and PDFs; Grok 4.3 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-5.6 Sol and Grok 4.3 is proprietary.

Which is newer?

GPT-5.6 Sol is the newest, released Jul 9, 2026. Kimi K2.7 Code came out Jun 12, 2026; Grok 4.3 came out Apr 17, 2026. Knowledge cutoff: GPT-5.6 Sol Feb 16, 2026, 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.