Gemini 3 Flash Preview vs Kimi K2 Thinking (Comparative Analysis)
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Comparative Analysis: Gemini 3 Flash Preview vs. Kimi K2 Thinking
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Overview
Kimi K2 Thinking was released 1 month before Gemini 3 Flash Preview.
 Gemini 3 Flash Preview |  Kimi K2 Thinking | |
|---|---|---|
Model Provider The organization behind this AI's development | Google | MoonshotAI |
Input Context Window Maximum input tokens this model can process at once | 1M tokens | 262.1K tokens |
Output Token Limit Maximum output tokens this model can generate at once | 65.5K tokens | 100.4K tokens |
Release Date When this model first became publicly available | December 17, 2025 7 months ago December 17th, 2025 | November 6, 2025 8 months ago November 6th, 2025 |
Capabilities & Features
Compare supported features, modalities, and advanced capabilities
Gemini 3 Flash Preview | Kimi K2 Thinking | |
|---|---|---|
Input Types Supported input formats | 📝Text🖼️Image📁File🎵Audio🎬Video | 📝Text |
Reasoning Controls Defaults and configurable reasoning effort | OptionalEffort: High, Medium, Low, MinimalDefault: Medium | Always enabled |
Output Types Supported output formats | 📝Text | 📝Text |
Tokenizer Text encoding system | Gemini | Other |
Key Features Advanced capabilities | ✓Function Calling✓Structured Output✓Reasoning ModeContent Moderation | ✓Function Calling✓Structured Output✓Reasoning ModeContent Moderation |
Open Source Model availability | Proprietary | Available on HuggingFace → |
Pricing
Gemini 3 Flash Preview is roughly 0.8x less expensive compared to Kimi K2 Thinking for input tokens and roughly 1.2x more expensive for output tokens.
| Gemini 3 Flash Preview | Kimi K2 Thinking | |
|---|---|---|
Input Token Cost Cost per million input tokens | $0.50 per million tokens | $0.60 per million tokens |
Output Token Cost Cost per million output tokens | $3.00 per million tokens | $2.50 per million tokens |
Web Search Cost Additional cost for each web search operation | $0.014 per search | Not specified |
Cache Read Cost Cost to reuse cached input tokens | $0.05 per million tokens | $0.15 per million tokens |
Cache Write Cost Cost to write input tokens to the cache | $0.08 per million tokens | Not specified |
Reasoning Token Cost Cost for internal reasoning tokens | $3.00 per million tokens | Not specified |
Image Input Cost Additional cost for each image input | $0.0000005 per image | Not specified |
Audio Input Cost Additional cost for audio input | $0.000001 per unit | Not specified |
Audio Cache Cost Cost to reuse cached audio input tokens | $0.10 per million tokens | Not specified |
Benchmarks
Compare relevant benchmarks between Gemini 3 Flash Preview and Kimi K2 Thinking.
| Gemini 3 Flash Preview | Kimi K2 Thinking | |
|---|---|---|
Intelligence Index Overall model quality across independent evaluations | Benchmark not available. | 17.3 (Artificial Analysis index; higher is better) |
Coding Index Programming performance across independent evaluations | Benchmark not available. | 21 (Artificial Analysis index; higher is better) |
Agentic Index Ability to complete multi-step agentic tasks | Benchmark not available. | 1.8 (Artificial Analysis index; higher is better) |
Best Design Arena Score Highest human-preference Elo score across design arenas | 1,241 Elo (#36 in 3D (62.7% win rate)) | 1,138 Elo (#79 in Website (48.8% win rate)) |
At a Glance
Quick overview of what makes Gemini 3 Flash Preview and Kimi K2 Thinking unique.
Gemini 3 Flash Preview by Google understands both text and images, handles audio, analyzes video, can use external tools and APIs, offers advanced reasoning, generates structured data. It can handle standard conversations with its 1M token context window. Reasonably priced at $0.50/M input and $3.00/M output tokens. Released December 17th, 2025.Kimi K2 Thinking by MoonshotAI can use external tools and APIs, offers advanced reasoning, generates structured data. It can handle standard conversations with its 262.1K token context window. Reasonably priced at $0.60/M input and $2.50/M output tokens. Released November 6th, 2025.Explore More Comparisons
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