Seed 2.0 Lite vs Gemini Deep Research

At a Glance

Compare
Seed 2.0 LiteByteDance Seed
Gemini Deep ResearchGoogle DeepMind
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.25Openrouter · Sep 22, 2026Not reported
Output priceFrom · USD / 1M tokens$2.00Openrouter · Sep 22, 2026Not reported
Context windowMaximum documented tokensNot reported1,049K
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 →
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

FieldSeed 2.0 LiteGemini Deep Research
DeveloperByteDance SeedGoogle DeepMind
FamilySeed 2 0Gemini Agents
ModelSeed 2.0 LiteGemini Deep Research
VersionSeed 2.0 LiteGemini Deep Research
Lifecycleactivepreview
Released2026-02-14Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, AudioText, Image, Video, Audio, Document
Output modalitiesTextText, Image
Context windowUnknown1,049K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessOpenrouter (Standard)Google AI (Standard), Google Gemini (Standard)
Capabilitiesagents, chat, generation, reasoning, structured_outputs, toolsgeneration, reasoning, research, tools

Seed 2.0 Lite Capabilities

agentschatgenerationreasoningstructured outputstools
Serving providers1
Canonical IDbytedance-seed/seed-2.0-lite

Gemini Deep Research Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Seed 2.0 Lite vs Gemini Deep Research FAQs

Is Seed 2.0 Lite or Gemini Deep Research better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Seed 2.0 Lite and Gemini Deep Research, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Seed 2.0 Lite or Gemini Deep Research?+

Only Seed 2.0 Lite has a directly sourced input price: $0.25 per million tokens. Only Seed 2.0 Lite has a directly sourced output price: $2.00 per million tokens.

Which has a larger context window, Seed 2.0 Lite or Gemini Deep Research?+

Neither model has a larger sourced context window in this comparison. Seed 2.0 Lite is — and Gemini Deep Research is 1,049K.

Which performs better in benchmarks, Seed 2.0 Lite 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 Seed 2.0 Lite or Gemini Deep Research be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Seed 2.0 Lite is not marked open weight; Gemini Deep Research is not marked open weight.

Can Seed 2.0 Lite and Gemini Deep Research understand images?+

Seed 2.0 Lite is 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, Seed 2.0 Lite or Gemini Deep Research?+

Neither has a larger sourced maximum output. Seed 2.0 Lite is — and Gemini Deep Research is 66K.

Do Seed 2.0 Lite and Gemini Deep Research support reasoning and tool use?+

Seed 2.0 Lite: reasoning, tool calling, and image input. Gemini Deep Research: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Seed 2.0 Lite or Gemini Deep Research?+

Seed 2.0 Lite has 1 sourced provider route; Gemini Deep Research has 2, so Gemini Deep Research has broader tracked availability.

Which offers better value, Seed 2.0 Lite 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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