Gemini 3.7 Flash vs Hy4 preview
Model Markets Rankings
Intelligence, Cost, and Efficiency
| Ranking | Gemini 3.7 Flash | Hy4 preview |
|---|---|---|
| IntelligenceHigher is better · MM Intelligence v1.2 | #3 of 2287.8 score | UnrankedNot in the 22-model eligible cohort |
| CostLower is better · Published-token output estimate | #15 of 36$0.085 per LiveBench case | UnrankedNot in the 36-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.0 | #2 of 2268.1 score | UnrankedNot in the 22-model eligible cohort |
Ranks come from the current complete eligible cohorts. Green highlights appear only when both models are ranked in the same metric. Missing required inputs remain unranked, and the three dimensions are not collapsed into an overall winner.
Benchmark Performance
Available Benchmarks
Technical Differences
Side-by-Side Facts
| Field | Gemini 3.7 Flash | Hy4 preview |
|---|---|---|
| Developer | Google DeepMind | Tencent |
| Family | Gemini 3 | Hy4 |
| Model | Gemini 3.7 Flash | Hy4 preview |
| Version | Gemini 3.7 Flash | Hy4 preview |
| Lifecycle | active | preview |
| Released | Unknown | 2026-08-28 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video, Audio, Document | Text |
| Output modalities | Text | 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 | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
13 comparable fields · 10 material differences · Pair passes the primary-source comparison gate
Gemini 3.7 Flash Capabilities
Hy4 preview Capabilities
Internal Comparison Graph
Related Comparisons
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Gemini 3.7 FlashGoogle DeepMind | vs | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Gemini 3.7 Flash vs Hy4 preview FAQs
Is Gemini 3.7 Flash or Hy4 preview better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Gemini 3.7 Flash and Hy4 preview, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Gemini 3.7 Flash or Hy4 preview?+
Gemini 3.7 Flash is $0.75 and Hy4 preview is $0.834 per million tokens, so Gemini 3.7 Flash is cheaper on this metric. Gemini 3.7 Flash is $3.75 and Hy4 preview is $2.501 per million tokens, so Hy4 preview is cheaper on this metric.
Which has a larger context window, Gemini 3.7 Flash or Hy4 preview?+
Gemini 3.7 Flash has the larger sourced context window. Gemini 3.7 Flash supports 1,049K and Hy4 preview supports 1,000K.
Which performs better in benchmarks, Gemini 3.7 Flash 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 3.7 Flash or Hy4 preview be self-hosted?+
Hy4 preview is the only model in this pair currently marked as self-hostable. Gemini 3.7 Flash is not marked open weight; Hy4 preview is open weight.
Can Gemini 3.7 Flash and Hy4 preview understand images?+
Gemini 3.7 Flash 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 3.7 Flash or Hy4 preview?+
Neither has a larger sourced maximum output. Gemini 3.7 Flash is 66K and Hy4 preview is —.
Do Gemini 3.7 Flash and Hy4 preview support reasoning and tool use?+
Gemini 3.7 Flash: 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 3.7 Flash or Hy4 preview?+
Gemini 3.7 Flash has 2 sourced provider routes; Hy4 preview has 1, so Gemini 3.7 Flash has broader tracked availability.
Which offers better value, Gemini 3.7 Flash 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.