Gemini 3.8 Flash vs Kimi K2 Instruct
Gemini 3.8 Flash leads the LLM Stats Score 51.0 to 22.0. Kimi K2 Instruct is 3.0x cheaper per token.
Google · Moonshot AI · Updated for 2026
Which is better?
Gemini 3.8 Flash leads the overall LLM Stats Score 51.0 to 22.0, ranking #15 overall.
On price, Kimi K2 Instruct is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.8 Flash 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 Gemini 3.8 Flash
- overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Kimi K2 Instruct
- cost matters — it's about 3.0x cheaper per token
- 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
13 reported for Gemini 3.8 Flash · 38 for Kimi K2 Instruct
Gemini 3.8 Flash and Kimi K2 Instructdon'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, Gemini 3.8 Flash ($0.75/1M tokens) is 1.5x more expensive than Kimi K2 Instruct ($0.50/1M tokens).
For output processing, Gemini 3.8 Flash ($3.75/1M tokens) is 7.5x more expensive than Kimi K2 Instruct ($0.50/1M tokens).
In conclusion, Gemini 3.8 Flash is more expensive than Kimi K2 Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.8 Flash accepts 1,048,576 input tokens compared to Kimi K2 Instruct's 200,000 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while Gemini 3.8 Flash is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 3.8 Flash supports multimodal inputs, whereas Kimi K2 Instruct does not.
Gemini 3.8 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 3.8 Flash
Kimi K2 Instruct
License
Usage and distribution terms
Gemini 3.8 Flash is licensed under a proprietary license, while Kimi K2 Instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Gemini 3.8 Flash was released on 2026-09-02, while Kimi K2 Instruct was released on 2025-07-11.
Gemini 3.8 Flash is 14 months newer than Kimi K2 Instruct.
Sep 2, 2026
1 days ago
1.1yr newerJul 11, 2025
1.1 years ago
Knowledge Cutoff
When training data ends
Gemini 3.8 Flash has a documented knowledge cutoff of 2026-03-31, while Kimi K2 Instruct's cutoff date is not specified.
We can confirm Gemini 3.8 Flash's training data extends to 2026-03-31, but cannot make a direct comparison without Kimi K2 Instruct's cutoff date.
Mar 2026
—
Provider Availability
Gemini 3.8 Flash is available from Google. Kimi K2 Instruct is available from Fireworks, Novita.
Gemini 3.8 Flash
Kimi K2 Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 3.8 Flash and Kimi K2 Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 3.8 Flash vs Kimi K2 Instruct.