Models / Compare /DeepSeek V3.2 vs Kimi K2.7 Code
Head to head
DeepSeek V3.2 vs Kimi K2.7 Code
Compared on live catalog data — pricing synced daily, benchmark scores with provenance.
The short version
- DeepSeek V3.2 is cheaper to run hosted: $0.40/M output vs $3.50/M for Kimi K2.7 Code (8.8× difference at the cheapest tracked provider).
- Kimi K2.7 Code takes 262K tokens of context vs 164K for DeepSeek V3.2.
- DeepSeek V3.2 has downloadable weights (OPEN) so you can self-host it; we hold no downloadable copy of Kimi K2.7 Code, so it runs through a provider's API.
- Kimi K2.7 Code scores 1472.5712 on Arena Code (WebDev) vs 1323.384 for DeepSeek V3.2.
| Spec | ||
|---|---|---|
| Vendor | DeepSeek | Moonshot AI |
| Parameters | 685B / 37B | 1.1T / 32B |
| 164K | 262K | |
| Weights | OPEN | OPEN* |
| License | MIT License | Custom licence |
| Modality | text->text | text+image->text |
| Released | Dec 1, 2025 | Jun 11, 2026 |
| 432.1 GBest | 667.5 GBest | |
| Cheapest hosted | $0.27 / $0.40 per 1M (Novita AI) | $0.73 / $3.50 per 1M (OpenRouter) |
| Tracked providers | 19 | 20 |
DeepSeek V3.2 — our take
DeepSeek V3.2 is a large downloadable text model with a permissive MIT licence and a 163,840-token request limit. Only 37 billion of its 685.4 billion total parameters are active per token, keeping inference costs down while measured coding performance is the clear peak in its benchmark profile.
full breakdown →Kimi K2.7 Code — our take
Moonshot's very large coding model can be downloaded. At over a trillion parameters it is an unusually large model to be downloadable at all, aimed at agentic coding workloads where scale matters.
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