Gemini 3.1 Pro Preview vs Kimi K2.5

Pricing math

Provider list price: Gemini 3.1 Pro Preview is $2.00/M input, $12.00/M output. Kimi K2.5 is $0.375/M input, $2.025/M output. On OpenKey, add the flat 3% fee: Gemini becomes $2.00 x 1.03 = $2.06/M input and $12.00 x 1.03 = $12.36/M output. Kimi becomes $0.375 x 1.03 = $0.38625/M input and $2.025 x 1.03 = $2.08575/M output.

Run the numbers on a realistic workload — 10M input tokens, 2M output tokens — and Gemini costs $44.00 versus Kimi's $7.80. That's a 5.33x input price ratio. If you're calling either model at scale (agent loops, batch document processing), that gap adds up fast. Gemini also caches at $0.20/M read and $0.375/M write; Kimi's provider doesn't expose cache pricing in this catalog.

Coding and agent benchmarks

On Design Arena's agent categories, Gemini leads in the categories where design output quality is judged directly: agentichtmlslides (rank 5, 1226 elo) and htmlslides (rank 6, 1209 elo) versus Kimi's fullstack (rank 14, 1182 elo) and webapps (rank 15, 1194 elo). Gemini also ranks higher on the model-level SVG category (rank 2, 1347 elo vs Kimi's rank 25, 1210 elo) and uicomponent (rank 8, 1322 elo vs Kimi's rank 19, 1290 elo).

Kimi does edge out Gemini on godotgamedev (rank 2, 1254 elo vs Gemini's rank 6, 1220 elo) and androidnative (rank 17, 1132 elo vs Gemini's rank 25, 1059 elo) — both game/mobile agent categories. On dataviz the two are effectively tied at 1270 elo, with Gemini at rank 20 and Kimi at rank 21 — not a meaningful gap either way. Artificial Analysis scores Gemini's coding index at 68.8 and agentic index at 21.4; no comparable Artificial Analysis numbers are published for Kimi in this catalog.

Context and long-document work

Gemini's 1,048,576-token context is 4x Kimi's 262,144 tokens. For tasks that need to hold an entire codebase, a long contract, or a multi-hour transcript in context at once, Gemini has real headroom that Kimi doesn't. Gemini also supports a larger max output (65,536 tokens) versus Kimi, which has no stated max completion limit in this catalog. If your workload chunks documents anyway, Kimi's 262,144-token window is still large enough for most single-file or multi-file review tasks — you just hit the ceiling sooner on huge inputs.

Modality differences

Gemini accepts audio, file, image, text, and video as input — it's the broader multimodal model here. Kimi accepts text and image only. If your pipeline needs to process audio transcripts, video frames, or arbitrary file uploads directly, Gemini is the only option of the two. Both models output text only. Gemini's reasoning is mandatory with three effort levels (high, medium, low, defaulting to medium); Kimi's reasoning is optional and enabled by default, giving you a toggle Gemini doesn't offer.

Questions

Which is cheaper, Gemini 3.1 Pro Preview or Kimi K2.5?

Kimi K2.5, by a wide margin. Provider list price is $0.375/M input and $2.025/M output versus Gemini's $2.00/M input and $12.00/M output — a 5.33x gap on input tokens. On a 10M-input/2M-output workload, Kimi costs $7.80 total versus Gemini's $44.00.

Does Kimi K2.5 beat Gemini 3.1 Pro Preview on any benchmark?

Yes — Kimi ranks higher on godotgamedev (rank 2, 1254 elo vs Gemini's rank 6, 1220 elo) and androidnative (rank 17, 1132 elo vs Gemini's rank 25, 1059 elo). On dataviz they're roughly tied at 1270 elo (Gemini rank 20, Kimi rank 21).

Which model has a bigger context window?

Gemini 3.1 Pro Preview, at 1,048,576 tokens versus Kimi K2.5's 262,144 tokens — a 4x difference. Gemini also supports a larger max output at 65,536 tokens; Kimi has no stated max completion limit in this catalog.

Can both models process images and audio?

Both accept image input, but only Gemini 3.1 Pro Preview handles audio, video, and file inputs directly. Kimi K2.5 is limited to text and image input, with text-only output for both models.