ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Kimi K2.7 Code vs Qwen3.8 27B vs Grok 4.3

Too close to call on our weighted score (Qwen3.8 27B 67, Grok 4.3 67, Kimi K2.7 Code 64). The right pick depends on what you value most.

  1. 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

  2. Alibaba (Qwen)

    Qwen3.8 27B

    Released Aug 14, 2026

    67/100
    • ECI149.4
    • Price$0.40 / $2.50
    • Context262K
    Full specs Remove Qwen3.8 27B

  3. xAI

    Grok 4.3

    Released Apr 17, 2026

    67/100
    • ECI149.2
    • Price$1.25 / $2.50
    • Context1M
    Full specs Remove Grok 4.3
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Qwen3.8 27B 67/100, Grok 4.3 67/100, Kimi K2.7 Code 64/100), so choose by what matters most for your work: Kimi K2.7 Code for raw capability, Qwen3.8 27B on price and Grok 4.3 for long inputs. 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 · Qwen3.8 27B 149.4 · Grok 4.3 149.2
  • Lowest priceQwen3.8 27BQwen3.8 27B $0.925 · Grok 4.3 $1.56 · Kimi K2.7 Code $1.71 per 1M tokens (3:1 blend)
  • Longest contextGrok 4.3Grok 4.3 1,000,000 · Kimi K2.7 Code 262,144 · Qwen3.8 27B 262,144 tokens
  • Widest inputsSame inputsKimi K2.7 Code: Text, Images, Video · Qwen3.8 27B: Text, Images, Video · Grok 4.3: Text, Images, PDFs
  • Self-hostingKimi K2.7 Code and Qwen3.8 27BPublishes downloadable weights
How the score is built
MeasureWeightKimi K2.7 CodeQwen3.8 27BGrok 4.3
CapabilityCapabilities Index (ECI)50%787777
Price25%395141
Inputs & features15%808080
Context window10%373760
Overall100%64/10067/10067/100
02 — Side by side

Every spec in one table

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

Kimi K2.7 Code vs Qwen3.8 27B vs Grok 4.3 specifications side by side
SpecificationKimi K2.7 CodeMoonshot AIQwen3.8 27BAlibaba (Qwen)Grok 4.3xAI
Capability
Capabilities Index (ECI)150.0 (best)149.4149.2
ECI rank#49 of 148 (best)#53 of 148#55 of 148
GPQA DiamondGraduate-level science questions87.9%—88.8% (best)
FrontierMath Tiers 1–3Research-level mathematics54.0% (best)—42.8%
OTIS Mock AIME 2024–2025Competition mathematics95.6% (best)—93.3%
SimpleQA VerifiedShort factual questions36.5% (best)—33.2%
Price per million tokens
Input$0.95$0.40 (best)$1.25
Output$4.00$2.50 (best)$2.50 (best)
Cached input$0.19 (best)—$0.20
Blended (3:1)$1.71$0.925 (best)$1.56
Long-context rateSame rateSame rateOver 200K: $2.50 / $5.00
Price sourceOfficial Moonshot AI APIMedian of 39 providersOfficial xAI API
Limits
Context window262,144 tokens262,144 tokens1,000,000 tokens (best)
Max output262,144 tokens (best)32,768 tokens30,000 tokens
Inputs and features
TextYesYesYes
ImagesYesYesYes
PDFsNoNoYes
AudioNoNoNo
VideoYesYesNo
ReasoningYesYesYeslow · medium · high
Tool callingYesYesYes
Structured outputYesYesYes
Availability
WeightsOpenOpenProprietary
API model IDkimi-k2.7-code—grok-4.3
API providers51 (best)4127
ReleasedJun 12, 2026Aug 14, 2026Apr 17, 2026
Knowledge cutoffJan 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.

  • Kimi K2.7 Code$17.50
  • Qwen3.8 27B$9.00
  • Grok 4.3$17.50
04 — Questions

Which should you choose?

Which is better: Kimi K2.7 Code, Qwen3.8 27B or Grok 4.3?

It is close. Our weighted score puts them within a point (Qwen3.8 27B 67/100, Grok 4.3 67/100, Kimi K2.7 Code 64/100), so choose by what matters most for your work: Kimi K2.7 Code for raw capability, Qwen3.8 27B on price and Grok 4.3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Kimi K2.7 Code, Qwen3.8 27B or Grok 4.3?

Qwen3.8 27B is cheaper at $0.40 input / $2.50 output per million tokens (median across 39 API providers). Grok 4.3 costs $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). At a typical mix of three input tokens to one output token, that is $0.925 per million tokens for Qwen3.8 27B versus $1.56 for Grok 4.3 (1.7× as much) and $1.71 for Kimi K2.7 Code (1.9× 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), Qwen3.8 27B 149.4 (#53 of 148) and Grok 4.3 149.2 (#55 of 148). The confidence ranges of the top two overlap (148.1–151.8 vs 147.5–151.6), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Kimi K2.7 Code, Qwen3.8 27B and Grok 4.3 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. All three support tool calling for agent workflows.

Which has the bigger context window?

Grok 4.3 has the largest context window at 1,000,000 tokens, against 262,144 for Kimi K2.7 Code and 262,144 for Qwen3.8 27B. Maximum output per response: Kimi K2.7 Code up to 262,144, Qwen3.8 27B up to 32,768, Grok 4.3 up to 30,000 tokens.

Which can read images, PDFs, audio or video?

Kimi K2.7 Code accepts text, images and video; Qwen3.8 27B accepts text, images and video; Grok 4.3 accepts text, images and PDFs. They handle the same number of input types.

Are any of these open source?

Kimi K2.7 Code and Qwen3.8 27B publishes its weights and can be self-hosted; Grok 4.3 is proprietary.

Which is newer?

Qwen3.8 27B is the newest, released Aug 14, 2026. Kimi K2.7 Code came out Jun 12, 2026; Grok 4.3 came out Apr 17, 2026. Knowledge cutoff: 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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