Claude Sonnet 4.5 vs Gemini 3.5 Flash

At a Glance

Compare
Gemini 3.5 FlashGoogle 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#15 of 4672.1 score · 3/3 sources · complete
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#25 of 44$0.140 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#15 of 3856.8 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokens$3.00Anthropic · Sep 3, 2026$1.50Google AI · Aug 29, 2026
Output priceFrom · USD / 1M tokens$15.00Anthropic · Sep 3, 2026$9.00Google AI · Aug 29, 2026
Context windowMaximum documented tokens200K1,049K
Model facts checkedSep 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

All benchmark results →
BenchmarkClaude Sonnet 4.5Gemini 3.5 Flash
ARC-AGI-1verified-v1-ba05d69f6453 · verified_score · leader63.6769% of row best · percent · Claude Sonnet 4.5 (Thinking 32K)92.50100% of row best · percent · Gemini 3.5 Flash (High)
ARC-AGI-2verified-v2-6c676fa3e9af · verified_score · leader13.6119% of row best · percent · Claude Sonnet 4.5 (Thinking 32K)72.08100% of row best · percent · Gemini 3.5 Flash (High)
LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · statistical tie1,449.8199% of row best · rating · claude-sonnet-4-5-20250929; 95% CI [1443.68972646, 1455.92640287]; votes 31455; rank 281,461.40100% of row best · rating · gemini-3.5-flash-high; 95% CI [1452.14297727, 1470.66464631]; votes 4061; rank 22
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,433.9497% of row best · rating · claude-sonnet-4-5-20250929-high-32k; 95% CI [1431.13982742, 1436.74901697]; votes 80980; rank 811,475.72100% of row best · rating · gemini-3.5-flash-medium; 95% CI [1471.24691172, 1480.19960285]; votes 36627; rank 19
ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified77.25100% of row best · points · Claude Sonnet 4.5 · 7,415 output tokens / case75.5898% of row best · points · Gemini 3.5 Flash (high thinking) · 16,743 output tokens / case
Overall ResultCounted from the protocol-matched rows above · 1 tie0 benchmark wins3 benchmark winsOverall lead

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

FieldClaude Sonnet 4.5Gemini 3.5 Flash
DeveloperAnthropicGoogle DeepMind
FamilyClaude 4Gemini 3
ModelClaude Sonnet 4.5Gemini 3.5 Flash
VersionClaude Sonnet 4.5Gemini 3.5 Flash
Lifecycleactiveactive
Released2025-09-29Unknown
Knowledge cutoff2025-01-01Unknown
Input modalitiesText, ImageText, Image, Video, Audio, Document
Output modalitiesTextText
Context window200K1,049K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessAnthropic (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitieschat, generation, reasoning, structured_outputs, toolschat, generation, reasoning, tools

Claude Sonnet 4.5 Capabilities

chatgenerationreasoningstructured outputstools
Serving providers1
Canonical IDanthropic/claude-sonnet-4-5

Gemini 3.5 Flash Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDgoogle-deepmind/gemini-3.5-flash

Primary Evidence

Sources and Freshness

Questions

Claude Sonnet 4.5 vs Gemini 3.5 Flash FAQs

Is Claude Sonnet 4.5 or Gemini 3.5 Flash 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, 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?+

Claude Sonnet 4.5 is $3.00 and Gemini 3.5 Flash is $1.50 per million tokens, so Gemini 3.5 Flash is cheaper on this metric. Claude Sonnet 4.5 is $15.00 and Gemini 3.5 Flash is $9.00 per million tokens, so Gemini 3.5 Flash is cheaper on this metric.

Which has a larger context window, Claude Sonnet 4.5 or Gemini 3.5 Flash?+

Gemini 3.5 Flash has the larger sourced context window. Claude Sonnet 4.5 supports 200K and Gemini 3.5 Flash supports 1,049K.

Which performs better in benchmarks, Claude Sonnet 4.5 or Gemini 3.5 Flash?+

Gemini 3.5 Flash leads the current overall benchmark count. The result uses 4 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.

Can Claude Sonnet 4.5 or Gemini 3.5 Flash 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 is not marked open weight.

Can Claude Sonnet 4.5 and Gemini 3.5 Flash understand images?+

Claude Sonnet 4.5 is documented with image input; Gemini 3.5 Flash 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?+

Gemini 3.5 Flash has the larger sourced maximum output: Claude Sonnet 4.5 supports 64K and Gemini 3.5 Flash supports 66K output tokens.

Do Claude Sonnet 4.5 and Gemini 3.5 Flash support reasoning and tool use?+

Claude Sonnet 4.5: reasoning, tool calling, and image input. Gemini 3.5 Flash: 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?+

Claude Sonnet 4.5 has 1 sourced provider route; Gemini 3.5 Flash has 2, so Gemini 3.5 Flash has broader tracked availability.

Which offers better value, Claude Sonnet 4.5 or Gemini 3.5 Flash?+

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.

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