Gemini 2.5 Pro vs Kimi K2.7 Code
At a Glance
| Compare |  Gemini 2.5 ProGoogle DeepMind |  Kimi K2.7 CodeMoonshot AI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #9 of 44$0.042 per LiveBench case |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $1.25Google AI ↗ · Aug 29, 2026 | $0.68Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $10.00Google AI ↗ · Aug 29, 2026 | $3.21Openrouter ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,049K | 262K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 3, 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
Side-by-Side Facts
| Field | Gemini 2.5 Pro | Kimi K2.7 Code |
|---|---|---|
| Developer | Google DeepMind | Moonshot AI |
| Family | Gemini 2 5 | Kimi K2 7 |
| Model | Gemini 2.5 Pro | Kimi K2.7 Code |
| Version | Gemini 2.5 Pro | Kimi K2.7 Code |
| Lifecycle | active | active |
| Released | Unknown | 2026-06-11 |
| Knowledge cutoff | 2025-01-01 | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text, Image, Video |
| Output modalities | Text | Text |
| Context window | 1,049K | 262K |
| Total parameters | Unknown | 1T |
| Active parameters | Unknown | 32B |
| License | Unknown | modified-mit |
| 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), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, tools | agents, chat, coding, reasoning, tools, vision |
Gemini 2.5 Pro Capabilities
Kimi K2.7 Code Capabilities
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Primary Evidence
Sources and Freshness
Questions
Gemini 2.5 Pro vs Kimi K2.7 Code FAQs
Is Gemini 2.5 Pro or Kimi K2.7 Code better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 2.5 Pro and Kimi K2.7 Code, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 2.5 Pro or Kimi K2.7 Code?+
Gemini 2.5 Pro is $1.25 and Kimi K2.7 Code is $0.68 per million tokens, so Kimi K2.7 Code is cheaper on this metric. Gemini 2.5 Pro is $10.00 and Kimi K2.7 Code is $3.21 per million tokens, so Kimi K2.7 Code is cheaper on this metric.
Which has a larger context window, Gemini 2.5 Pro or Kimi K2.7 Code?+
Gemini 2.5 Pro has the larger sourced context window. Gemini 2.5 Pro supports 1,049K and Kimi K2.7 Code supports 262K.
Which performs better in benchmarks, Gemini 2.5 Pro or Kimi K2.7 Code?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini 2.5 Pro or Kimi K2.7 Code be self-hosted?+
Kimi K2.7 Code is the only model in this pair currently marked as self-hostable. Gemini 2.5 Pro is not marked open weight; Kimi K2.7 Code is open weight.
Can Gemini 2.5 Pro and Kimi K2.7 Code understand images?+
Gemini 2.5 Pro is documented with image input; Kimi K2.7 Code is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini 2.5 Pro or Kimi K2.7 Code?+
Neither has a larger sourced maximum output. Gemini 2.5 Pro is 66K and Kimi K2.7 Code is —.
Do Gemini 2.5 Pro and Kimi K2.7 Code support reasoning and tool use?+
Gemini 2.5 Pro: reasoning, tool calling, and image input. Kimi K2.7 Code: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini 2.5 Pro or Kimi K2.7 Code?+
Gemini 2.5 Pro has 2 sourced provider routes; Kimi K2.7 Code has 4, so Kimi K2.7 Code has broader tracked availability.
Which offers better value, Gemini 2.5 Pro or Kimi K2.7 Code?+
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.