Kimi-K2.7-Code
Kimi K2.7 Code is a coding-focused agentic model built upon Kimi K2.6. With substantial improvements on real-world long-horizon coding tasks, it strengthens end-to-end task completion across complex software engineering workflows while improving token efficiency, reducing thinking-token usage by approximately 30% compared with Kimi K2.6.
Params
1,026.9 B
Context
—
Downloads 30d
89 K
Likes
1,424
Download history
tracking started — chart appears after 7 days of snapshots (5 recorded)89 K downloads in the last 30 days
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | i32 | 595.2 GB | 809.2 GB | ❌ Won’t fit |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Use via API
via OpenRouter · USD per 1M tokens · synced 2026-10-24$0.67
input / 1M
$3.35
output / 1M
$0.15
cached input / 1M
$4.02
1M in + 1M out
- Context window
- 262,144 tokens
- Max output
- 235,929 tokens
- Providers
- 11
- Cheapest provider
- StreamLake · $0.71 / $3.00
- Best throughput
- —
- AA Intelligence / Coding / Agentic
- 25.8 / 60.8 / 21
✓ Tool calling
✓ Reasoning
✓ Structured outputs
✓ Image input
✗ File input
✗ Audio input
✓ Prompt caching
Specifications
- Architecture
- KimiK25ForConditionalGeneration
- Parameters
- 1,026.9 B
- Tensor type
- I32
- Licence
- other
- First seen on the Hub
- 2026-06-11
- Training datasets
- undisclosed
- Added to our catalog
- 2026-10-20
Compare with any image-text-to-text model