DeepSeek V3.2 vs Gemini Deep Research Max
At a Glance
| Compare |  DeepSeek V3.2DeepSeek |  Gemini Deep Research MaxGoogle DeepMind |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.26Deepinfra ↗ · Sep 21, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $0.38Deepinfra ↗ · Sep 21, 2026 | Not reported |
| Context windowMaximum documented tokens | 164K | 1,049K |
| Model facts checked | Aug 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
Side-by-Side Facts
| Field | DeepSeek-V3.2 | Gemini Deep Research Max |
|---|---|---|
| Developer | DeepSeek | Google DeepMind |
| Family | Deepseek V3 2 | Gemini Agents |
| Model | DeepSeek-V3.2 | Gemini Deep Research Max |
| Version | DeepSeek-V3.2 | Gemini Deep Research Max |
| Lifecycle | active | preview |
| Released | 2025-12-01 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Video, Audio, Document |
| Output modalities | Text | Text, Image |
| Context window | 164K | 1,049K |
| Total parameters | 685.4B | Unknown |
| Active parameters | Unknown | Unknown |
| License | mit | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | chat, generation, reasoning | generation, reasoning, research, tools |
DeepSeek V3.2 Capabilities
Gemini Deep Research Max Capabilities
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Primary Evidence
Sources and Freshness
Questions
DeepSeek V3.2 vs Gemini Deep Research Max FAQs
Is DeepSeek V3.2 or Gemini Deep Research Max better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V3.2 and Gemini Deep Research Max, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek V3.2 or Gemini Deep Research Max?+
Only DeepSeek V3.2 has a directly sourced input price: $0.26 per million tokens. Only DeepSeek V3.2 has a directly sourced output price: $0.38 per million tokens.
Which has a larger context window, DeepSeek V3.2 or Gemini Deep Research Max?+
Gemini Deep Research Max has the larger sourced context window. DeepSeek V3.2 supports 164K and Gemini Deep Research Max supports 1,049K.
Which performs better in benchmarks, DeepSeek V3.2 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 DeepSeek V3.2 or Gemini Deep Research Max be self-hosted?+
DeepSeek V3.2 is the only model in this pair currently marked as self-hostable. DeepSeek V3.2 is open weight; Gemini Deep Research Max is not marked open weight.
Can DeepSeek V3.2 and Gemini Deep Research Max understand images?+
DeepSeek V3.2 is not 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, DeepSeek V3.2 or Gemini Deep Research Max?+
Neither has a larger sourced maximum output. DeepSeek V3.2 is — and Gemini Deep Research Max is 66K.
Do DeepSeek V3.2 and Gemini Deep Research Max support reasoning and tool use?+
DeepSeek V3.2: reasoning. Gemini Deep Research Max: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V3.2 or Gemini Deep Research Max?+
DeepSeek V3.2 has 3 sourced provider routes; Gemini Deep Research Max has 2, so DeepSeek V3.2 has broader tracked availability.
Which offers better value, DeepSeek V3.2 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.