Gemini 3 Flash vs Kimi K3
At a Glance
| Compare |  Gemini 3 FlashGoogle DeepMind |  Kimi K3Moonshot AI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #17 of 4670.3 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #30 of 44$0.194 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #21 of 3852.5 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.50Google AI ↗ · Aug 29, 2026 | $2.85Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $3.00Google AI ↗ · Aug 29, 2026 | $14.25Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,049K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Gemini 3 Flash | Kimi-K3 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,442.4098% of row best · rating · gemini-3-flash (thinking-minimal); 95% CI [1439.30492660, 1445.49388279]; votes 85799; rank 61 | 1,472.27100% of row best · rating · kimi-k3-max; 95% CI [1467.05577758, 1477.48944277]; votes 20987; rank 23 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 benchmark winNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Gemini 3 Flash | Kimi-K3 |
|---|---|---|
| Developer | Google DeepMind | Moonshot AI |
| Family | Gemini 3 | Kimi K3 |
| Model | Gemini 3 Flash | Kimi-K3 |
| Version | Gemini 3 Flash | Kimi-K3 |
| Lifecycle | preview | active |
| Released | Unknown | 2026-07-16 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 1,049K |
| Total parameters | Unknown | 2.8T |
| Active parameters | Unknown | 104B |
| License | Unknown | other |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning |
Gemini 3 Flash Capabilities
Kimi K3 Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
Gemini 3 FlashGoogle DeepMind | vs | Kimi-K2.6Moonshot AI | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  GPT-6 AstraOpenAI | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs | Gemini 3.1 ProGoogle DeepMind | family variantstext |
 DeepSeek-V4.1-FlashDeepSeek | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs | Grok 4.6xAI | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | Gemini 3 FlashGoogle DeepMind | cross-developer peerstext |
Gemini 3 FlashGoogle DeepMind | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini 3 Flash vs Kimi K3 FAQs
Is Gemini 3 Flash or Kimi K3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3 Flash and Kimi K3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3 Flash or Kimi K3?+
Gemini 3 Flash is $0.50 and Kimi K3 is $2.85 per million tokens, so Gemini 3 Flash is cheaper on this metric. Gemini 3 Flash is $3.00 and Kimi K3 is $14.25 per million tokens, so Gemini 3 Flash is cheaper on this metric.
Which has a larger context window, Gemini 3 Flash or Kimi K3?+
Neither model has a larger sourced context window in this comparison. Gemini 3 Flash is 1,049K and Kimi K3 is 1,049K.
Which performs better in benchmarks, Gemini 3 Flash or Kimi K3?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini 3 Flash or Kimi K3 be self-hosted?+
Kimi K3 is the only model in this pair currently marked as self-hostable. Gemini 3 Flash is not marked open weight; Kimi K3 is open weight.
Can Gemini 3 Flash and Kimi K3 understand images?+
Gemini 3 Flash is documented with image input; Kimi K3 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 3 Flash or Kimi K3?+
Neither has a larger sourced maximum output. Gemini 3 Flash is 66K and Kimi K3 is —.
Do Gemini 3 Flash and Kimi K3 support reasoning and tool use?+
Gemini 3 Flash: reasoning, tool calling, and image input. Kimi K3: reasoning and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 3 Flash or Kimi K3?+
Gemini 3 Flash has 2 sourced provider routes; Kimi K3 has 5, so Kimi K3 has broader tracked availability.
Which offers better value, Gemini 3 Flash or Kimi K3?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.