DeepSeek V3.2 vs Gemini 2.5 Flash Lite

At a Glance

Compare
Gemini 2.5 Flash LiteGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.26Deepinfra · Sep 23, 2026$0.10Google AI · Aug 29, 2026
Output priceFrom · USD / 1M tokens$0.38Deepinfra · Sep 23, 2026$0.40Google AI · Aug 29, 2026
Context windowMaximum documented tokens164K1,049K
Model facts checkedAug 28, 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 →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldDeepSeek-V3.2Gemini 2.5 Flash-Lite
DeveloperDeepSeekGoogle DeepMind
FamilyDeepseek V3 2Gemini 2 5
ModelDeepSeek-V3.2Gemini 2.5 Flash-Lite
VersionDeepSeek-V3.2Gemini 2.5 Flash-Lite
Lifecycleactiveactive
Released2025-12-01Unknown
Knowledge cutoffUnknown2025-01-01
Input modalitiesTextText, Image, Video, Audio, Document
Output modalitiesTextText
Context window164K1,049K
Total parameters685.4BUnknown
Active parametersUnknownUnknown
LicensemitUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitieschat, generation, reasoningchat, generation, reasoning, tools

DeepSeek V3.2 Capabilities

chatgenerationreasoning
Serving providers3
Canonical IDdeepseek-ai/DeepSeek-V3.2

Gemini 2.5 Flash Lite Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDgoogle-deepmind/gemini-2.5-flash-lite

Primary Evidence

Sources and Freshness

Questions

DeepSeek V3.2 vs Gemini 2.5 Flash Lite FAQs

Is DeepSeek V3.2 or Gemini 2.5 Flash Lite better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V3.2 and Gemini 2.5 Flash Lite, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, DeepSeek V3.2 or Gemini 2.5 Flash Lite?+

DeepSeek V3.2 is $0.26 and Gemini 2.5 Flash Lite is $0.10 per million tokens, so Gemini 2.5 Flash Lite is cheaper on this metric. DeepSeek V3.2 is $0.38 and Gemini 2.5 Flash Lite is $0.40 per million tokens, so DeepSeek V3.2 is cheaper on this metric.

Which has a larger context window, DeepSeek V3.2 or Gemini 2.5 Flash Lite?+

Gemini 2.5 Flash Lite has the larger sourced context window. DeepSeek V3.2 supports 164K and Gemini 2.5 Flash Lite supports 1,049K.

Which performs better in benchmarks, DeepSeek V3.2 or Gemini 2.5 Flash Lite?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can DeepSeek V3.2 or Gemini 2.5 Flash Lite be self-hosted?+

DeepSeek V3.2 is the only model in this pair currently marked as self-hostable. DeepSeek V3.2 is open weight; Gemini 2.5 Flash Lite is not marked open weight.

Can DeepSeek V3.2 and Gemini 2.5 Flash Lite understand images?+

DeepSeek V3.2 is not documented with image input; Gemini 2.5 Flash Lite is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V3.2 or Gemini 2.5 Flash Lite?+

Neither has a larger sourced maximum output. DeepSeek V3.2 is — and Gemini 2.5 Flash Lite is 66K.

Do DeepSeek V3.2 and Gemini 2.5 Flash Lite support reasoning and tool use?+

DeepSeek V3.2: reasoning. Gemini 2.5 Flash Lite: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V3.2 or Gemini 2.5 Flash Lite?+

DeepSeek V3.2 has 3 sourced provider routes; Gemini 2.5 Flash Lite has 2, so DeepSeek V3.2 has broader tracked availability.

Which offers better value, DeepSeek V3.2 or Gemini 2.5 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.

Send Feedback