Seed 2.0 Lite vs Gemini Deep Research Max
At a Glance
| Compare | Seed 2.0 LiteByteDance Seed |  Gemini Deep Research MaxGoogle DeepMind |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.25Openrouter ↗ · Sep 22, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $2.00Openrouter ↗ · Sep 22, 2026 | Not reported |
| Context windowMaximum documented tokens | Not reported | 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
Side-by-Side Facts
| Field | Seed 2.0 Lite | Gemini Deep Research Max |
|---|---|---|
| Developer | ByteDance Seed | Google DeepMind |
| Family | Seed 2 0 | Gemini Agents |
| Model | Seed 2.0 Lite | Gemini Deep Research Max |
| Version | Seed 2.0 Lite | Gemini Deep Research Max |
| Lifecycle | active | preview |
| Released | 2026-02-14 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio | Text, Image, Video, Audio, Document |
| Output modalities | Text | Text, Image |
| Context window | Unknown | 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 | Openrouter (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | agents, chat, generation, reasoning, structured_outputs, tools | generation, reasoning, research, tools |
Seed 2.0 Lite Capabilities
Gemini Deep Research Max Capabilities
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Primary Evidence
Sources and Freshness
Questions
Seed 2.0 Lite vs Gemini Deep Research Max FAQs
Is Seed 2.0 Lite or Gemini Deep Research Max better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Seed 2.0 Lite and Gemini Deep Research Max, 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 Max?+
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 Max?+
Neither model has a larger sourced context window in this comparison. Seed 2.0 Lite is — and Gemini Deep Research Max is 1,049K.
Which performs better in benchmarks, Seed 2.0 Lite or Gemini Deep Research Max?+
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 Max 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 Max is not marked open weight.
Can Seed 2.0 Lite and Gemini Deep Research Max understand images?+
Seed 2.0 Lite is documented with image input; Gemini Deep Research Max 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 Max?+
Neither has a larger sourced maximum output. Seed 2.0 Lite is — and Gemini Deep Research Max is 66K.
Do Seed 2.0 Lite and Gemini Deep Research Max support reasoning and tool use?+
Seed 2.0 Lite: reasoning, tool calling, and image input. Gemini Deep Research Max: 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 Max?+
Seed 2.0 Lite has 1 sourced provider route; Gemini Deep Research Max has 2, so Gemini Deep Research Max has broader tracked availability.
Which offers better value, Seed 2.0 Lite or Gemini Deep Research Max?+
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.