Claude Sonnet 4.5 vs Gemini 2.5 Pro
At a Glance
| Compare | Claude Sonnet 4.5Anthropic |  Gemini 2.5 ProGoogle DeepMind |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #36 of 4627.7 score · 2/3 sources · provisional · missing LiveBench · full-core range 18.5–51.8 | UnrankedNot in the 46-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $3.00Anthropic ↗ · Sep 3, 2026 | $1.25Google AI ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $15.00Anthropic ↗ · Sep 3, 2026 | $10.00Google AI ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 200K | 1,049K |
| Model facts checked | Sep 3, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Claude Sonnet 4.5 | Gemini 2.5 Pro |
|---|---|---|
| LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · leader | 1,449.81100% of row best · rating · claude-sonnet-4-5-20250929; 95% CI [1443.68972646, 1455.92640287]; votes 31455; rank 28 | 1,421.2398% of row best · rating · gemini-2.5-pro; 95% CI [1414.98072895, 1427.48825137]; votes 25110; rank 36 |
| LMArena Search Arenasearch-2026-08-24-d25aabda0010 · arena_rating · leader | 1,158.46100% of row best · rating · claude-sonnet-4-5-search; 95% CI [1153.41447529, 1163.49714967]; votes 127378; rank 24 | 1,141.6599% of row best · rating · gemini-2.5-pro-grounding; 95% CI [1137.05776179, 1146.24105969]; votes 83404; rank 27 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,433.9498% of row best · rating · claude-sonnet-4-5-20250929-high-32k; 95% CI [1431.13982742, 1436.74901697]; votes 80980; rank 81 | 1,457.77100% of row best · rating · gemini-2.5-pro; 95% CI [1455.30542635, 1460.23799206]; votes 122554; rank 36 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 77.2599% of row best · points · Claude Sonnet 4.5 · 7,415 output tokens / case | 78.27100% of row best · points · Gemini 2.5 Pro · 4,521 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 2 benchmark winsNo overall winner | 1 benchmark winNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Sonnet 4.5 | Gemini 2.5 Pro |
|---|---|---|
| Developer | Anthropic | Google DeepMind |
| Family | Claude 4 | Gemini 2 5 |
| Model | Claude Sonnet 4.5 | Gemini 2.5 Pro |
| Version | Claude Sonnet 4.5 | Gemini 2.5 Pro |
| Lifecycle | active | active |
| Released | 2025-09-29 | Unknown |
| Knowledge cutoff | 2025-01-01 | 2025-01-01 |
| Input modalities | Text, Image | Text, Image, Video, Audio, Document |
| Output modalities | Text | Text |
| Context window | 200K | 1,049K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Anthropic (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, tools |
Claude Sonnet 4.5 Capabilities
Gemini 2.5 Pro Capabilities
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|---|---|---|---|
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Claude Sonnet 4.5Anthropic | vs |  GLM-5.3Z.ai | cross-developer peerstext |
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Claude Sonnet 4.5Anthropic | vs | Seed 2.1 ProByteDance Seed | cross-developer peersimage, text |
Claude Sonnet 4.5Anthropic | vs |  Mistral Large 3Mistral AI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
Claude Sonnet 4.5 vs Gemini 2.5 Pro FAQs
Is Claude Sonnet 4.5 or Gemini 2.5 Pro better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Sonnet 4.5 and Gemini 2.5 Pro, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Sonnet 4.5 or Gemini 2.5 Pro?+
Claude Sonnet 4.5 is $3.00 and Gemini 2.5 Pro is $1.25 per million tokens, so Gemini 2.5 Pro is cheaper on this metric. Claude Sonnet 4.5 is $15.00 and Gemini 2.5 Pro is $10.00 per million tokens, so Gemini 2.5 Pro is cheaper on this metric.
Which has a larger context window, Claude Sonnet 4.5 or Gemini 2.5 Pro?+
Gemini 2.5 Pro has the larger sourced context window. Claude Sonnet 4.5 supports 200K and Gemini 2.5 Pro supports 1,049K.
Which performs better in benchmarks, Claude Sonnet 4.5 or Gemini 2.5 Pro?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Claude Sonnet 4.5 or Gemini 2.5 Pro be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Sonnet 4.5 is not marked open weight; Gemini 2.5 Pro is not marked open weight.
Can Claude Sonnet 4.5 and Gemini 2.5 Pro understand images?+
Claude Sonnet 4.5 is documented with image input; Gemini 2.5 Pro is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Sonnet 4.5 or Gemini 2.5 Pro?+
Gemini 2.5 Pro has the larger sourced maximum output: Claude Sonnet 4.5 supports 64K and Gemini 2.5 Pro supports 66K output tokens.
Do Claude Sonnet 4.5 and Gemini 2.5 Pro support reasoning and tool use?+
Claude Sonnet 4.5: reasoning, tool calling, and image input. Gemini 2.5 Pro: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Sonnet 4.5 or Gemini 2.5 Pro?+
Claude Sonnet 4.5 has 1 sourced provider route; Gemini 2.5 Pro has 2, so Gemini 2.5 Pro has broader tracked availability.
Which offers better value, Claude Sonnet 4.5 or Gemini 2.5 Pro?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.