DeepSeek-V4-Flash-Vision-Exp vs Kimi K2.7 Code
DeepSeek-V4-Flash-Vision-Exp leads the LLM Stats Score 48.5 to 39.6. DeepSeek-V4-Flash-Vision-Exp is 4.3x cheaper per token.
DeepSeek · Moonshot AI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-Vision-Exp leads the overall LLM Stats Score 48.5 to 39.6, ranking #17 overall.
On price, DeepSeek-V4-Flash-Vision-Exp is roughly 4.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-Vision-Exp also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-Vision-Exp
- overall performance matters — it scores 48.5 and ranks #17 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 4.3x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Kimi K2.7 Code
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
7 reported for DeepSeek-V4-Flash-Vision-Exp · 9 for Kimi K2.7 Code
DeepSeek-V4-Flash-Vision-Exp and Kimi K2.7 Codedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-Vision-Exp ($0.22/1M tokens) is 3.4x cheaper than Kimi K2.7 Code ($0.74/1M tokens).
For output processing, DeepSeek-V4-Flash-Vision-Exp ($0.66/1M tokens) is 5.3x cheaper than Kimi K2.7 Code ($3.50/1M tokens).
In conclusion, Kimi K2.7 Code is more expensive than DeepSeek-V4-Flash-Vision-Exp.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Vision-Exp accepts 1,048,576 input tokens compared to Kimi K2.7 Code's 262,144 tokens. DeepSeek-V4-Flash-Vision-Exp can generate longer responses up to 393,216 tokens, while Kimi K2.7 Code is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4-Flash-Vision-Exp and Kimi K2.7 Code support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4-Flash-Vision-Exp
Kimi K2.7 Code
Release Timeline
When each model was launched
DeepSeek-V4-Flash-Vision-Exp was released on 2026-08-21, while Kimi K2.7 Code was released on 2026-06-12.
DeepSeek-V4-Flash-Vision-Exp is 2 months newer than Kimi K2.7 Code.
Aug 21, 2026
1 weeks ago
2mo newerJun 12, 2026
2 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-Vision-Exp is available from DeepSeek. Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
DeepSeek-V4-Flash-Vision-Exp
Kimi K2.7 Code
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Vision-Exp and Kimi K2.7 Code side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-Vision-Exp vs Kimi K2.7 Code.