Gemini 2.5 Pro vs Gemini 3 Pro
Gemini 2.5 Pro (2025) and Gemini 3 Pro (2025) are frontier reasoning models from Google DeepMind. Gemini 2.5 Pro ships a 1m-token context window, while Gemini 3 Pro ships a 1m-token context window. On MMLU PRO, Gemini 3 Pro leads by 5.6 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Pick Gemini 3 Pro for general evaluation; Gemini 2.5 Pro is better when coding workflow support matters more.
Decision scorecard
Local evidence first| Signal | Gemini 2.5 Pro | Gemini 3 Pro |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps, tool-calling agents, and long-context analysis |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 1m |
| Cheapest output | $10/1M tokens | $5/1M tokens |
| Provider routes | 4 tracked | 2 tracked |
| Shared benchmarks | 5 shared | MMLU PRO leader |
Decision tradeoffs
- Gemini 2.5 Pro holds a shared-benchmark lead on Massive Multi-discipline Multimodal Understanding, ahead by 0.7 points.
- Gemini 2.5 Pro has broader tracked provider coverage for fallback and procurement flexibility.
- Gemini 2.5 Pro uniquely exposes Reasoning and Structured outputs in local model data.
- Local decision data tags Gemini 2.5 Pro for Coding, RAG, and Agents.
- Gemini 3 Pro holds a shared-benchmark lead on MMLU PRO, ahead by 5.6 points.
- Gemini 3 Pro has the lower cheapest tracked output price at $5/1M tokens.
- Local decision data tags Gemini 3 Pro 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 2.5 Pro
$3,500
Cheapest tracked route/tier: Google AI Studio <=200K tokens
Gemini 3 Pro
$2,250
Cheapest tracked route/tier: GCP Vertex AI
Estimated monthly gap: $1,250. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Gemini 3 Pro is $5/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and Structured outputs before moving production traffic.
- Use this scaffold for Gemini users checking whether Gemini 3 Pro changes the answer for long-context, RAG, or tool-use workloads.
- Start from context-window fit, then compare output-token pricing and cache availability.
- Preserve Gemini 2.5 Pro as a candidate when the page lacks sourced peer benchmarks for the task.
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Gemini 2.5 Pro is $5/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Gemini 2.5 Pro adds Reasoning and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-17 | 2025-12-11 |
| Context window | 1m | 1m |
| Parameters | — | — |
| Architecture | Decoder Only | Decoder Only |
| 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 | 2025-01 |
Pricing and availability
| Pricing attribute | Gemini 2.5 Pro | Gemini 3 Pro |
|---|---|---|
| Input price |
| $1.25/1M tokens |
| Output price |
| $5/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 2.5 Pro | Gemini 3 Pro |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Gemini 3 Pro |
|---|---|---|
| MMLU PRO | 86.2 | 91.8 |
| SWE-bench Verified | 63.8 | 76.2 |
| Google-Proof Q&A | 86.4 | 91.9 |
| Massive Multi-discipline Multimodal Understanding | 81.7 | 81.0 |
| Chatbot Arena | 1398.0 | 1486.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Gemini 2.5 Pro at 86.2 and Gemini 3 Pro at 91.8, with Gemini 3 Pro ahead by 5.6 points; SWE-bench Verified has Gemini 2.5 Pro at 63.8 and Gemini 3 Pro at 76.2, with Gemini 3 Pro ahead by 12.4 points; Google-Proof Q&A has Gemini 2.5 Pro at 86.4 and Gemini 3 Pro at 91.9, with Gemini 3 Pro ahead by 5.5 points. The largest visible gap is 12.4 points on SWE-bench Verified, 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 reasoning mode: Gemini 2.5 Pro and structured outputs: Gemini 2.5 Pro. Both models share vision, multimodal input, function calling, and tool use, 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 2.5 Pro lists tiered pricing: <=200K tokens is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output, while Gemini 3 Pro lists $1.25/1M input and $5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemini 3 Pro lower by about $1.50 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 4 providers versus 2, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support and broader provider choice are central to the workload. Choose Gemini 3 Pro when coding workflow support 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 2.5 Pro or Gemini 3 Pro?
Gemini 2.5 Pro supports 1m tokens, while Gemini 3 Pro supports 1m 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 2.5 Pro or Gemini 3 Pro?
Gemini 2.5 Pro lists tiered pricing: <=200K tokens is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output. Gemini 3 Pro lists $1.25/1M input and $5/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Gemini 3 Pro open source?
Gemini 2.5 Pro is listed under Proprietary. Gemini 3 Pro 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 2.5 Pro or Gemini 3 Pro?
Both Gemini 2.5 Pro and Gemini 3 Pro expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Gemini 2.5 Pro or Gemini 3 Pro?
Both Gemini 2.5 Pro and Gemini 3 Pro 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 2.5 Pro and Gemini 3 Pro?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, OpenRouter, and Vercel AI Gateway. Gemini 3 Pro is available on Replicate API and GCP Vertex AI. 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.