Gemini 3 Pro vs Kimi K2.5
Gemini 3 Pro (2025) and Kimi K2.5 (2026) compare a standalone API model against a coding-specialized model. Gemini 3 Pro ships a 1m-token context window, while Kimi K2.5 ships a 256k-token context window. On MMLU PRO, Gemini 3 Pro leads by 4.7 pts. On pricing, Kimi K2.5 costs $0.44/1M input tokens versus $1.25/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: Gemini 3 Pro is standalone API model, while Kimi K2.5 is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | Gemini 3 Pro | Kimi K2.5 |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | multimodal apps, tool-calling agents, and long-context analysis | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 256k |
| Cheapest output | $5/1M tokens | $2/1M tokens |
| Provider routes | 2 tracked | 10 tracked |
| Shared benchmarks | MMLU PRO leader | 5 shared |
Decision tradeoffs
- Gemini 3 Pro holds a shared-benchmark lead on MMLU PRO, ahead by 4.7 points.
- Gemini 3 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3 Pro uniquely exposes Tool use and Code execution in local model data.
- Local decision data tags Gemini 3 Pro for Coding, RAG, and Agents.
- Kimi K2.5 holds a shared-benchmark lead on SWE-bench Verified, ahead by 0.6 points.
- Kimi K2.5 has the lower cheapest tracked output price at $2/1M tokens.
- Kimi K2.5 has broader tracked provider coverage for fallback and procurement flexibility.
- Kimi K2.5 uniquely exposes Structured outputs in local model data.
- Local decision data tags Kimi K2.5 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemini 3 Pro
$2,250
Cheapest tracked route/tier: GCP Vertex AI
Kimi K2.5
$852
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $1,398. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Replicate API; start route-level A/B tests there.
- Kimi K2.5 is $3/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Tool use and Code execution before moving production traffic.
- Kimi K2.5 adds Structured outputs in local capability data.
- Provider overlap exists on Replicate API; start route-level A/B tests there.
- Gemini 3 Pro is $3/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- Gemini 3 Pro adds Tool use and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-11 | 2026-03-15 |
| Context window | 1m | 256k |
| Parameters | — | 1T (MoE, 384 experts) |
| Architecture | Decoder Only | Mixture of Experts |
| License | Proprietary | Proprietary |
| Openness | Proprietary | Proprietary |
| Weights | Not released | Not released |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: conditional |
| Knowledge cutoff | 2025-01 | - |
Pricing and availability
| Pricing attribute | Gemini 3 Pro | Kimi K2.5 |
|---|---|---|
| Input price | $1.25/1M tokens | $0.44/1M tokens |
| Output price | $5/1M tokens | $2/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 3 Pro | Kimi K2.5 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | No |
| Structured outputs | No | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemini 3 Pro | Kimi K2.5 |
|---|---|---|
| MMLU PRO | 91.8 | 87.1 |
| SWE-bench Verified | 76.2 | 76.8 |
| Google-Proof Q&A | 91.9 | 87.9 |
| BFCL | 72.5 | 47.1 |
| MMMU Pro | 81.0 | 78.5 |
Deep dive
On shared benchmark coverage, MMLU PRO has Gemini 3 Pro at 91.8 and Kimi K2.5 at 87.1, with Gemini 3 Pro ahead by 4.7 points; SWE-bench Verified has Gemini 3 Pro at 76.2 and Kimi K2.5 at 76.8, with Kimi K2.5 ahead by 0.6 points; Google-Proof Q&A has Gemini 3 Pro at 91.9 and Kimi K2.5 at 87.9, with Gemini 3 Pro ahead by 4 points. The largest visible gap is 4.7 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on tool use: Gemini 3 Pro, structured outputs: Kimi K2.5, and code execution: Gemini 3 Pro. Both models share vision, multimodal input, and function calling, 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 Pro lists $1.25/1M input and $5/1M output tokens on the cheapest tracked provider, while Kimi K2.5 lists $0.44/1M input and $2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2.5 lower by about $1.47 per million blended tokens. Availability is 2 providers versus 10, so concentration risk also matters.
Choose Gemini 3 Pro when coding workflow support and larger context windows are central to the workload. Choose Kimi K2.5 when coding workflow support, lower input-token cost, and broader provider choice 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 Pro or Kimi K2.5?
Gemini 3 Pro supports 1m tokens, while Kimi K2.5 supports 256k 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 Pro or Kimi K2.5?
Kimi K2.5 is cheaper on tracked token pricing. Gemini 3 Pro costs $1.25/1M input and $5/1M output tokens. Kimi K2.5 costs $0.44/1M input and $2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 3 Pro or Kimi K2.5 open source?
Gemini 3 Pro is listed under Proprietary. Kimi K2.5 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 Pro or Kimi K2.5?
Both Gemini 3 Pro and Kimi K2.5 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Gemini 3 Pro or Kimi K2.5?
Both Gemini 3 Pro and Kimi K2.5 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Gemini 3 Pro and Kimi K2.5?
Gemini 3 Pro is available on Replicate API and GCP Vertex AI. Kimi K2.5 is available on Cloudflare Workers AI, Fireworks AI, OpenRouter, Together AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.