Kimi K2.7 Code
Intelligence benchmarks
Artificial Analysis indexes - compared with the best open and proprietary models
Intelligence
41.9
AA Index
Coding
45.6
AA Index
Agentic
61.9
AA Index
Intelligence Index - Kimi K2.7 Code vs. the field
Best open-weight models (you can run locally) and leading proprietary models for context.
Coding Index comparison
Agentic Index comparison
Benchmark data from Artificial Analysis · updated 2026-06-18.
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| GPQA | 89.6 |
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
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Deep dive
Notes, sources, and the full write-up
Kimi K2.7 Code is a 1058.6B-parameter other model from Kimi. It scores 41.9 on the Artificial Analysis Intelligence Index (coding 45.6). At Q4_K_M it needs roughly 614 GB of VRAM, placing it in the 48 GB+ / multi-GPU hardware tier.
Benchmarks
Artificial Analysis Intelligence Index - Kimi K2.7 Code vs. leading closed models:
| Model | Intelligence | Coding | GPQA |
|---|---|---|---|
| Kimi K2.7 Code | 41.9 | 45.6 | 89.6 |
| Claude Fable 5 (with fallback) | 59.9 | 76.5 | 92.6 |
| Claude Opus 4.8 (max) | 55.7 | 56.7 | 92 |
| GPT-5.5 (xhigh) | 54.8 | 74.9 | 93.5 |
| Claude Opus 4.7 (max) | 53.5 | 52.5 | 91.4 |
| Gemini 3.5 Flash | 50.2 | 45 | 92.2 |
Source: Artificial Analysis (2026-06-18).
Popularity
Kimi K2.7 Code has 229,156 downloads in the last month on HuggingFace and 859 likes.
Frequently asked
Quick answers to common questions
How much VRAM does Kimi K2.7 Code need?
Kimi K2.7 Code with 1058.6B parameters needs approximately 614 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Kimi K2.7 Code better than other moonshotai models?
Kimi K2.7 Code has 1058.6B parameters with 262,144 context - a strong choice for general use.
What license is Kimi K2.7 Code under?
Kimi K2.7 Code is released under the other license, making it suitable for most commercial and personal projects.
What hardware runs Kimi K2.7 Code well?
With 1058.6B parameters, Kimi K2.7 Code requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Kimi K2.7 Code?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~752 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Kimi K2.7 Code's context window handle?
Kimi K2.7 Code supports a 262,144-token context window - enough for very long documents, codebases, or multi-turn conversations. Real-world usable context may vary by implementation.
What models compete with Kimi K2.7 Code?
Kimi K2.7 Code competes with other 529B–1588B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Nearby options
Similar models and compatible hardware by spec
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