Gemini Deep Research vs Solar Pro 4
At a Glance
| Compare |  Gemini Deep ResearchGoogle DeepMind |  Solar Pro 4Upstage |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.090Upstage ↗ · Sep 18, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.36Upstage ↗ · Sep 18, 2026 |
| Context windowMaximum documented tokens | 1,049K | 524K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 18, 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 | Gemini Deep Research | Solar Pro 4 |
|---|---|---|
| Developer | Google DeepMind | Upstage |
| Family | Gemini Agents | Solar Pro |
| Model | Gemini Deep Research | Solar Pro 4 |
| Version | Gemini Deep Research | Solar Pro 4 |
| Lifecycle | preview | active |
| Released | Unknown | 2026-08-14 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text |
| Output modalities | Text, Image | Text |
| Context window | 1,049K | 524K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Upstage (Standard) |
| Capabilities | generation, reasoning, research, tools | agents, chat, generation, reasoning, structured_outputs, tools |
| Supported languages | Unknown | English, Korean, Japanese |
| Training data cutoff | Unknown | February 2026 |
Gemini Deep Research Capabilities
Solar Pro 4 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Gemini Deep Research vs Solar Pro 4 FAQs
Is Gemini Deep Research or Solar Pro 4 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini Deep Research and Solar Pro 4, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini Deep Research or Solar Pro 4?+
Only Solar Pro 4 has a directly sourced input price: $0.090 per million tokens. Only Solar Pro 4 has a directly sourced output price: $0.36 per million tokens.
Which has a larger context window, Gemini Deep Research or Solar Pro 4?+
Gemini Deep Research has the larger sourced context window. Gemini Deep Research supports 1,049K and Solar Pro 4 supports 524K.
Which performs better in benchmarks, Gemini Deep Research or Solar Pro 4?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini Deep Research or Solar Pro 4 be self-hosted?+
Solar Pro 4 is the only model in this pair currently marked as self-hostable. Gemini Deep Research is not marked open weight; Solar Pro 4 is not marked open weight.
Can Gemini Deep Research and Solar Pro 4 understand images?+
Gemini Deep Research is documented with image input; Solar Pro 4 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini Deep Research or Solar Pro 4?+
Solar Pro 4 has the larger sourced maximum output: Gemini Deep Research supports 66K and Solar Pro 4 supports 131K output tokens.
Do Gemini Deep Research and Solar Pro 4 support reasoning and tool use?+
Gemini Deep Research: reasoning, tool calling, and image input. Solar Pro 4: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini Deep Research or Solar Pro 4?+
Gemini Deep Research has 2 sourced provider routes; Solar Pro 4 has 1, so Gemini Deep Research has broader tracked availability.
Which offers better value, Gemini Deep Research or Solar Pro 4?+
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.