DeepSeek V3 vs Gemini Deep Research

At a Glance

Compare
DeepSeek V3DeepSeek
Gemini Deep ResearchGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.2574Openrouter · Aug 29, 2026Not reported
Output priceFrom · USD / 1M tokens$0.89Deepinfra · Sep 21, 2026Not reported
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-V3Gemini Deep Research
DeveloperDeepSeekGoogle DeepMind
FamilyDeepseek V3Gemini Agents
ModelDeepSeek-V3Gemini Deep Research
VersionDeepSeek-V3Gemini Deep Research
Lifecycleactivepreview
Released2024-12-26Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Video, Audio, Document
Output modalitiesTextText, Image
Context window164K1,049K
Total parameters684.5BUnknown
Active parameters37BUnknown
LicenseUnknownUnknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitieschat, generationgeneration, reasoning, research, tools

DeepSeek V3 Capabilities

chatgeneration
Serving providers3
Canonical IDdeepseek-ai/DeepSeek-V3

Gemini Deep Research Capabilities

generationreasoningresearchtools
Serving providers2
Canonical IDgoogle-deepmind/deep-research-preview-04-2026

Primary Evidence

Sources and Freshness

Questions

DeepSeek V3 vs Gemini Deep Research FAQs

Is DeepSeek V3 or Gemini Deep Research better for coding?+

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

Which is cheaper, DeepSeek V3 or Gemini Deep Research?+

Only DeepSeek V3 has a directly sourced input price: $0.2574 per million tokens. Only DeepSeek V3 has a directly sourced output price: $0.89 per million tokens.

Which has a larger context window, DeepSeek V3 or Gemini Deep Research?+

Gemini Deep Research has the larger sourced context window. DeepSeek V3 supports 164K and Gemini Deep Research supports 1,049K.

Which performs better in benchmarks, DeepSeek V3 or Gemini Deep Research?+

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

Can DeepSeek V3 or Gemini Deep Research be self-hosted?+

DeepSeek V3 is the only model in this pair currently marked as self-hostable. DeepSeek V3 is open weight; Gemini Deep Research is not marked open weight.

Can DeepSeek V3 and Gemini Deep Research understand images?+

DeepSeek V3 is not documented with image input; Gemini Deep Research is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V3 or Gemini Deep Research?+

Neither has a larger sourced maximum output. DeepSeek V3 is — and Gemini Deep Research is 66K.

Do DeepSeek V3 and Gemini Deep Research support reasoning and tool use?+

DeepSeek V3: none of these features are definitively sourced. Gemini Deep Research: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V3 or Gemini Deep Research?+

DeepSeek V3 has 3 sourced provider routes; Gemini Deep Research has 2, so DeepSeek V3 has broader tracked availability.

Which offers better value, DeepSeek V3 or Gemini Deep Research?+

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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