Gemini 3.1 Flash-Lite vs Kimi K2 Thinking Turbo
Gemini 3.1 Flash-Lite (2026) and Kimi K2 Thinking Turbo (2025) are general-purpose language models from Google DeepMind and Moonshot AI. Gemini 3.1 Flash-Lite ships a 1.05m-token context window, while Kimi K2 Thinking Turbo ships a 262k-token context window. On pricing, Gemini 3.1 Flash-Lite costs $0.25/1M input tokens versus $1.15/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemini 3.1 Flash-Lite is ~360% cheaper at $0.25/1M; pay for Kimi K2 Thinking Turbo only for provider fit.
Decision scorecard
Local evidence first| Signal | Gemini 3.1 Flash-Lite | Kimi K2 Thinking Turbo |
|---|---|---|
| Best for | multimodal apps, tool-calling agents, and long-context analysis | general production evaluation |
| Decision fit | Coding, RAG, and Agents | Long context |
| Context window | 1.05m | 262k |
| Cheapest output | $1.50/1M tokens | $8/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemini 3.1 Flash-Lite has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3.1 Flash-Lite has the lower cheapest tracked output price at $1.50/1M tokens.
- Gemini 3.1 Flash-Lite has broader tracked provider coverage for fallback and procurement flexibility.
- Gemini 3.1 Flash-Lite uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Gemini 3.1 Flash-Lite for Coding, RAG, and Agents.
- Local decision data tags Kimi K2 Thinking Turbo for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemini 3.1 Flash-Lite
$575
Cheapest tracked route/tier: Google AI Studio
Kimi K2 Thinking Turbo
$2,920
Cheapest tracked route/tier: Vercel AI Gateway
Estimated monthly gap: $2,345. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- Kimi K2 Thinking Turbo is $6.50/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- Gemini 3.1 Flash-Lite is $6.50/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Gemini 3.1 Flash-Lite adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-05-07 | 2025-11-06 |
| Context window | 1.05m | 262k |
| Parameters | — | 1T (32B active) |
| Architecture | decoder only | - |
| License | Proprietary | Proprietary |
| Knowledge cutoff | 2025-01 | - |
Pricing and availability
| Pricing attribute | Gemini 3.1 Flash-Lite | Kimi K2 Thinking Turbo |
|---|---|---|
| Input price | $0.25/1M tokens | $1.15/1M tokens |
| Output price | $1.50/1M tokens | $8/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 3.1 Flash-Lite | Kimi K2 Thinking Turbo |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Gemini 3.1 Flash-Lite, multimodal input: Gemini 3.1 Flash-Lite, function calling: Gemini 3.1 Flash-Lite, tool use: Gemini 3.1 Flash-Lite, structured outputs: Gemini 3.1 Flash-Lite, and code execution: Gemini 3.1 Flash-Lite. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Gemini 3.1 Flash-Lite lists $0.25/1M input and $1.50/1M output tokens on the cheapest tracked provider, while Kimi K2 Thinking Turbo lists $1.15/1M input and $8/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemini 3.1 Flash-Lite lower by about $2.58 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Gemini 3.1 Flash-Lite when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Kimi K2 Thinking Turbo when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemini 3.1 Flash-Lite or Kimi K2 Thinking Turbo?
Gemini 3.1 Flash-Lite supports 1.05m tokens, while Kimi K2 Thinking Turbo supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemini 3.1 Flash-Lite or Kimi K2 Thinking Turbo?
Gemini 3.1 Flash-Lite is cheaper on tracked token pricing. Gemini 3.1 Flash-Lite costs $0.25/1M input and $1.50/1M output tokens. Kimi K2 Thinking Turbo costs $1.15/1M input and $8/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 3.1 Flash-Lite or Kimi K2 Thinking Turbo open source?
Gemini 3.1 Flash-Lite is listed under Proprietary. Kimi K2 Thinking Turbo is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemini 3.1 Flash-Lite or Kimi K2 Thinking Turbo?
Gemini 3.1 Flash-Lite has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Gemini 3.1 Flash-Lite or Kimi K2 Thinking Turbo?
Gemini 3.1 Flash-Lite has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemini 3.1 Flash-Lite and Kimi K2 Thinking Turbo?
Gemini 3.1 Flash-Lite is available on Google AI Studio, OpenRouter, and Vercel AI Gateway. Kimi K2 Thinking Turbo is available on Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.