Decision in 20 seconds
As of July 2, 2026, DeepSeek is the API cost and 1M-context baseline; Kimi is the K2.7 Code and Kimi Code workflow candidate.
Use this page when
- You need a price/context comparison before picking Kimi or DeepSeek.
This page is not for
- Choosing a vendor without running the same task on both sides.
- Ignoring review time, retry count, and integration cost.
Key points
- DeepSeek-V4-Flash: 1M context, 384K max output, $0.0028 cache-hit input, $0.14 cache-miss input, $0.28 output per 1M tokens.
- Kimi K2.x models have 262,144-token context and higher API prices, but add K2.7 Code, HighSpeed, Kimi Code CLI/IDE, and multimodal workflow entries.
- The 50k input + 10k output sample is about $0.0098 on DeepSeek-V4-Flash cache miss and $0.0875 on `kimi-k2.7-code` cache miss.
What changed recently
- `deepseek-chat` and `deepseek-reasoner` are deprecated on July 24, 2026 15:59 UTC.
- Older Kimi K2 preview/thinking names and `kimi-latest` are not good defaults for new projects.
Explanation
For cost-sensitive API batches, start with DeepSeek-V4-Flash.
For coding workflow, test Kimi Code plus `kimi-k2.7-code`.
For long input/output, DeepSeek has the visible 1M and 384K max-output advantage.
Kimi vs DeepSeek hard facts table
Use this table before running builder pilots.
| Model | Context | Max output | Input cache hit | Input cache miss | Output | Extra signal |
|---|---|---|---|---|---|---|
| `deepseek-v4-flash` | 1M | 384K | $0.0028 | $0.14 | $0.28 | concurrency 2500 |
| `deepseek-v4-pro` | 1M | 384K | $0.003625 | $0.435 | $0.87 | concurrency 500 |
| `kimi-k2.7-code` | 262,144 tokens | not separately listed | $0.19 | $0.95 | $4.00 | coding model |
| `kimi-k2.7-code-highspeed` | 262,144 tokens | not separately listed | $0.38 | $1.90 | $8.00 | about 180 tokens/s |
| `kimi-k2.6` | 262,144 tokens | not separately listed | $0.16 | $0.95 | $4.00 | general multimodal / agent |
| `kimi-k2.5` | 262,144 tokens | not separately listed | $0.10 | $0.60 | $3.00 | lower-cost Kimi |
| `moonshot-v1-128k` | 131,072 tokens | not listed | n/a | $2.00 input | $5.00 output | V1 reference |
How to verify the answer
Official pages used for model names, pricing, context, output, deprecation, and Kimi Code facts.
Tools / Examples
- Same API batch — Run one JSON extraction batch through DeepSeek-V4-Flash, DeepSeek-V4-Pro, `kimi-k2.5`, and `kimi-k2.7-code`.
- Same repo edit — Compare Kimi Code with your DeepSeek-powered coding setup by diff size, tests, command output, and failure notes.
Evidence timeline
Sources
- Kimi model list
- Kimi K2.7 Code pricing
- Kimi K2.6 pricing
- Kimi K2.5 pricing
- Moonshot V1 pricing
- Kimi Code GitHub
- DeepSeek models pricing
- DeepSeek API docs
FAQ
Which is cheaper for the 50k input + 10k output sample?
DeepSeek-V4-Flash is cheaper in this sample: about $0.0098 on cache miss.
When does Kimi still make sense?
When Kimi Code, `kimi-k2.7-code`, HighSpeed, multimodal input, or workflow time savings matter more than raw API price.
Related
- Kimi / Moonshot AI model updates
- Chinese AI models list
- Chinese open-source AI models
- China AI updates
- China AI news sources in English
- Best places to track AI research papers
- Best sites to track AI licensing and commercial-use changes
- Best sites to track AI agents and agent framework updates
- AI product updates worth tracking in 2026: real products, concrete changes, and what builders should watch
- Best AI Agent Frameworks for Builders in 2026
- Kimi vs DeepSeek for builders: pricing, context, API cost, and code workflows
Go deeper
- Chinese AI models list
- Chinese open-source AI models
- China AI updates
- China AI news sources in English
Last updated: 2026-07-22 · Policy: Editorial standards · Methodology