Claude Sonnet 4.5 vs Gemini 3 Pro
Claude Sonnet 4.5 (2025) and Gemini 3 Pro (2025) are frontier reasoning models from Anthropic and Google DeepMind. Claude Sonnet 4.5 ships a 200k-token context window, while Gemini 3 Pro ships a 1m-token context window. On MMLU PRO, Gemini 3 Pro leads by 5.8 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 Pro fits 5x more tokens; pick it for long-context work and Claude Sonnet 4.5 for tighter calls.
Decision scorecard
Local evidence first| Signal | Claude Sonnet 4.5 | 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 | 200k | 1m |
| Cheapest output | $15/1M tokens | $5/1M tokens |
| Provider routes | 8 tracked | 2 tracked |
| Shared benchmarks | 6 shared | MMLU PRO leader |
Decision tradeoffs
- Claude Sonnet 4.5 holds a shared-benchmark lead on SWE-bench Verified, ahead by 1 points.
- Claude Sonnet 4.5 has broader tracked provider coverage for fallback and route flexibility.
- Claude Sonnet 4.5 uniquely exposes Reasoning and Structured outputs in local model data.
- Local decision data tags Claude Sonnet 4.5 for Coding, RAG, and Agents.
- Gemini 3 Pro holds a shared-benchmark lead on MMLU PRO, ahead by 5.8 points.
- Gemini 3 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 3 Pro has the lower cheapest tracked output price at $5/1M tokens.
- Gemini 3 Pro uniquely exposes Code execution in local model data.
- 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.
Claude Sonnet 4.5
$6,150
Cheapest tracked route/tier: Microsoft Foundry
Gemini 3 Pro
$2,250
Cheapest tracked route/tier: GCP Vertex AI
Estimated monthly gap: $3,900. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Replicate API and GCP Vertex AI; start route-level A/B tests there.
- Gemini 3 Pro is $10/1M 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.
- Gemini 3 Pro adds Code execution in local capability data.
- Provider overlap exists on GCP Vertex AI and Replicate API; start route-level A/B tests there.
- Claude Sonnet 4.5 is $10/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Code execution before moving production traffic.
- Claude Sonnet 4.5 adds Reasoning and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-09-29 | 2025-12-11 |
| Context window | 200k | 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 | 2025-12 | 2025-01 |
Pricing and availability
| Pricing attribute | Claude Sonnet 4.5 | Gemini 3 Pro |
|---|---|---|
| Input price |
| $1.25/1M tokens |
| Output price |
| $5/1M tokens |
| Providers |
Capabilities
| Capability | Claude Sonnet 4.5 | Gemini 3 Pro |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| JSON / Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Claude Sonnet 4.5 | Gemini 3 Pro |
|---|---|---|
| MMLU PRO | 86.0 | 91.8 |
| SWE-bench Verified | 77.2 | 76.2 |
| Google-Proof Q&A | 83.4 | 91.9 |
| Massive Multi-discipline Multimodal Understanding | 77.8 | 81.0 |
| MMMU Pro | 68.9 | 81.0 |
| BFCL | 73.2 | 72.5 |
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Last reviewed: 2026-07-26. Data sourced from public model cards and provider documentation.