Gemini 2.5 Pro vs Gemini 3.1 Pro Preview
Gemini 2.5 Pro (2025) and Gemini 3.1 Pro Preview (2026) are frontier reasoning models from Google DeepMind. Gemini 2.5 Pro ships a 1m-token context window, while Gemini 3.1 Pro Preview ships a 1m-token context window. On MMLU PRO, Gemini 3.1 Pro Preview leads by 4.8 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Gemini 3.1 Pro Preview is safer overall; choose Gemini 2.5 Pro when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | Gemini 2.5 Pro | Gemini 3.1 Pro Preview |
|---|---|---|
| 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 | $12/1M tokens |
| Provider routes | 4 tracked | 5 tracked |
| Shared benchmarks | 8 rows | MMLU PRO leader |
Decision tradeoffs
- Gemini 2.5 Pro has the lower cheapest tracked output price at $10/1M tokens.
- Gemini 2.5 Pro uniquely exposes Reasoning in local model data.
- Local decision data tags Gemini 2.5 Pro for Coding, RAG, and Agents.
- Gemini 3.1 Pro Preview holds a shared-benchmark lead on MMLU PRO, ahead by 4.8 points.
- Gemini 3.1 Pro Preview has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Gemini 3.1 Pro Preview 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 3.1 Pro Preview
$4,600
Cheapest tracked route/tier: Google AI Studio
Estimated monthly gap: $1,100. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Google AI Studio, GCP Vertex AI, and OpenRouter; start route-level A/B tests there.
- Gemini 3.1 Pro Preview is $2/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Reasoning before moving production traffic.
- Provider overlap exists on Google AI Studio, GCP Vertex AI, and OpenRouter; start route-level A/B tests there.
- Gemini 2.5 Pro is $2/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Gemini 2.5 Pro adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-17 | 2026-02-19 |
| Context window | 1m | 1m |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Openness | Proprietary | Proprietary |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2025-01 | 2025-01 |
Pricing and availability
| Pricing attribute | Gemini 2.5 Pro | Gemini 3.1 Pro Preview |
|---|---|---|
| Input price |
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| Output price |
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Capabilities
| Capability | Gemini 2.5 Pro | Gemini 3.1 Pro Preview |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Gemini 3.1 Pro Preview |
|---|---|---|
| MMLU PRO | 86.2 | 91.0 |
| SWE-bench Verified | 63.8 | 80.6 |
| Google-Proof Q&A | 86.4 | 94.3 |
| AIME 2025 | 86.7 | 95.0 |
| LiveCodeBench | 75.6 | 91.7 |
| Humanity's Last Exam | 18.8 | 51.4 |
| HumanEval | 93.1 | 94.0 |
| Chatbot Arena | 1398.0 | 1493.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Gemini 2.5 Pro at 86.2 and Gemini 3.1 Pro Preview at 91.0, with Gemini 3.1 Pro Preview ahead by 4.8 points; SWE-bench Verified has Gemini 2.5 Pro at 63.8 and Gemini 3.1 Pro Preview at 80.6, with Gemini 3.1 Pro Preview ahead by 16.8 points; Google-Proof Q&A has Gemini 2.5 Pro at 86.4 and Gemini 3.1 Pro Preview at 94.3, with Gemini 3.1 Pro Preview ahead by 7.9 points. The largest visible gap is 16.8 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. 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 $1.25/1M input and $10/1M output; 0-200,001t is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output; >200K tokens is $2.50/1M input and $15/1M output; 200,001t+ is $2.50/1M input and $15/1M output, while Gemini 3.1 Pro Preview lists tiered pricing: 0-200,001t is $2/1M input and $12/1M output; 200,001t+ is $4/1M input and $18/1M output. A 70/30 input-output blend puts Gemini 2.5 Pro lower by about $1.13 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 5, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support and lower cheapest-tier input-token cost are central to the workload. Choose Gemini 3.1 Pro Preview when coding workflow support 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 2.5 Pro or Gemini 3.1 Pro Preview?
Gemini 2.5 Pro supports 1m tokens, while Gemini 3.1 Pro Preview 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 3.1 Pro Preview?
Gemini 2.5 Pro lists tiered pricing: <=200K tokens is $1.25/1M input and $10/1M output; <=200K tokens is $1.25/1M input and $10/1M output; 0-200,001t is $1.25/1M input and $10/1M output; >200K tokens is $2.50/1M input and $15/1M output; >200K tokens is $2.50/1M input and $15/1M output; 200,001t+ is $2.50/1M input and $15/1M output. Gemini 3.1 Pro Preview lists tiered pricing: 0-200,001t is $2/1M input and $12/1M output; 200,001t+ is $4/1M input and $18/1M output. 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 3.1 Pro Preview open source?
Gemini 2.5 Pro is listed under Proprietary. Gemini 3.1 Pro Preview 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 3.1 Pro Preview?
Both Gemini 2.5 Pro and Gemini 3.1 Pro Preview 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 3.1 Pro Preview?
Both Gemini 2.5 Pro and Gemini 3.1 Pro Preview 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 3.1 Pro Preview?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, OpenRouter, and Vercel AI Gateway. Gemini 3.1 Pro Preview is available on Google AI Studio, GCP Vertex AI, OpenRouter, Replicate API, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-05. Data sourced from public model cards and provider documentation.