Claude Sonnet 4.5 vs Gemini 3.5 Flash Lite
At a Glance
| Compare | Claude Sonnet 4.5Anthropic |  Gemini 3.5 Flash LiteGoogle 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 | #39 of 4617.6 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #8 of 44$0.029 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #32 of 3846.2 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $3.00Anthropic ↗ · Sep 3, 2026 | $0.30Google AI ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $15.00Anthropic ↗ · Sep 3, 2026 | $2.50Google 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 3.5 Flash-Lite |
|---|---|---|
| ARC-AGI-1verified-v1-ba05d69f6453 · verified_score · leader | 63.67100% of row best · percent · Claude Sonnet 4.5 (Thinking 32K) | 53.5084% of row best · percent · Gemini 3.5 Flash-Lite (High) |
| ARC-AGI-2verified-v2-6c676fa3e9af · verified_score · leader | 13.61100% of row best · percent · Claude Sonnet 4.5 (Thinking 32K) | 10.2876% of row best · percent · Gemini 3.5 Flash-Lite (High) |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,433.94100% of row best · rating · claude-sonnet-4-5-20250929-high-32k; 95% CI [1431.13982742, 1436.74901697]; votes 80980; rank 81 | 1,435.54100% of row best · rating · gemini-3.5-flash-lite; 95% CI [1430.59505493, 1440.49024696]; votes 26165; rank 79 |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 77.25100% of row best · points · Claude Sonnet 4.5 · 7,415 output tokens / case | 73.4295% of row best · points · Gemini 3.5 Flash-Lite · 1,966 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 2 benchmark winsNo overall winner | 0 benchmark winsNo 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 3.5 Flash-Lite |
|---|---|---|
| Developer | Anthropic | Google DeepMind |
| Family | Claude 4 | Gemini 3 |
| Model | Claude Sonnet 4.5 | Gemini 3.5 Flash-Lite |
| Version | Claude Sonnet 4.5 | Gemini 3.5 Flash-Lite |
| Lifecycle | active | active |
| Released | 2025-09-29 | Unknown |
| Knowledge cutoff | 2025-01-01 | Unknown |
| 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 3.5 Flash Lite Capabilities
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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 3.5 Flash Lite FAQs
Is Claude Sonnet 4.5 or Gemini 3.5 Flash Lite better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Sonnet 4.5 and Gemini 3.5 Flash Lite, 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 3.5 Flash Lite?+
Claude Sonnet 4.5 is $3.00 and Gemini 3.5 Flash Lite is $0.30 per million tokens, so Gemini 3.5 Flash Lite is cheaper on this metric. Claude Sonnet 4.5 is $15.00 and Gemini 3.5 Flash Lite is $2.50 per million tokens, so Gemini 3.5 Flash Lite is cheaper on this metric.
Which has a larger context window, Claude Sonnet 4.5 or Gemini 3.5 Flash Lite?+
Gemini 3.5 Flash Lite has the larger sourced context window. Claude Sonnet 4.5 supports 200K and Gemini 3.5 Flash Lite supports 1,049K.
Which performs better in benchmarks, Claude Sonnet 4.5 or Gemini 3.5 Flash Lite?+
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 3.5 Flash Lite be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Sonnet 4.5 is not marked open weight; Gemini 3.5 Flash Lite is not marked open weight.
Can Claude Sonnet 4.5 and Gemini 3.5 Flash Lite understand images?+
Claude Sonnet 4.5 is documented with image input; Gemini 3.5 Flash Lite is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Sonnet 4.5 or Gemini 3.5 Flash Lite?+
Gemini 3.5 Flash Lite has the larger sourced maximum output: Claude Sonnet 4.5 supports 64K and Gemini 3.5 Flash Lite supports 66K output tokens.
Do Claude Sonnet 4.5 and Gemini 3.5 Flash Lite support reasoning and tool use?+
Claude Sonnet 4.5: reasoning, tool calling, and image input. Gemini 3.5 Flash Lite: 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 3.5 Flash Lite?+
Claude Sonnet 4.5 has 1 sourced provider route; Gemini 3.5 Flash Lite has 2, so Gemini 3.5 Flash Lite has broader tracked availability.
Which offers better value, Claude Sonnet 4.5 or Gemini 3.5 Flash Lite?+
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.