Gemini Deep Research Max vs Hy4 preview
At a Glance
| Compare |  Gemini Deep Research MaxGoogle DeepMind |  Hy4 previewTencent |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.834Openrouter ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $2.501Openrouter ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,049K | 1,000K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 2, 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 Max | Hy4 preview |
|---|---|---|
| Developer | Google DeepMind | Tencent |
| Family | Gemini Agents | Hy4 |
| Model | Gemini Deep Research Max | Hy4 preview |
| Version | Gemini Deep Research Max | Hy4 preview |
| Lifecycle | preview | preview |
| Released | Unknown | 2026-08-28 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text |
| Output modalities | Text, Image | Text |
| Context window | 1,049K | 1,000K |
| Total parameters | Unknown | 770B |
| Active parameters | Unknown | 49B |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Google AI (Standard), Google Gemini (Standard) | Openrouter (Standard) |
| Capabilities | generation, reasoning, research, tools | chat, generation, reasoning, tools |
Gemini Deep Research Max Capabilities
Hy4 preview Capabilities
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Gemini Deep Research MaxGoogle DeepMind | vs | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini Deep Research Max vs Hy4 preview FAQs
Is Gemini Deep Research Max or Hy4 preview better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini Deep Research Max and Hy4 preview, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini Deep Research Max or Hy4 preview?+
Only Hy4 preview has a directly sourced input price: $0.834 per million tokens. Only Hy4 preview has a directly sourced output price: $2.501 per million tokens.
Which has a larger context window, Gemini Deep Research Max or Hy4 preview?+
Gemini Deep Research Max has the larger sourced context window. Gemini Deep Research Max supports 1,049K and Hy4 preview supports 1,000K.
Which performs better in benchmarks, Gemini Deep Research Max or Hy4 preview?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Gemini Deep Research Max or Hy4 preview be self-hosted?+
Hy4 preview is the only model in this pair currently marked as self-hostable. Gemini Deep Research Max is not marked open weight; Hy4 preview is open weight.
Can Gemini Deep Research Max and Hy4 preview understand images?+
Gemini Deep Research Max is documented with image input; Hy4 preview is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Gemini Deep Research Max or Hy4 preview?+
Neither has a larger sourced maximum output. Gemini Deep Research Max is 66K and Hy4 preview is —.
Do Gemini Deep Research Max and Hy4 preview support reasoning and tool use?+
Gemini Deep Research Max: reasoning, tool calling, and image input. Hy4 preview: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Gemini Deep Research Max or Hy4 preview?+
Gemini Deep Research Max has 2 sourced provider routes; Hy4 preview has 1, so Gemini Deep Research Max has broader tracked availability.
Which offers better value, Gemini Deep Research Max or Hy4 preview?+
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.