hy4 vs DeepSeek: A 4B Local Lightweight Line Against a 763B Cloud Flagship
Hunyuan hy4 is a 4.22 billion parameter dense model with a native 256K context, while DeepSeek-V4.1-Flash is a 763 billion parameter MoE with a native 1M context. This comparison covers architecture, community activity, quantization options, licensing, and deployment fit.
hy4 vs DeepSeek: A 4B Local Lightweight Line Against a 763B Cloud Flagship
Hunyuan hy4 and DeepSeek V4.1-Flash are almost asymmetric on every axis: a 4.22 billion parameter dense model against a 763 billion parameter MoE flagship. Yet they land in the same architecture review, because the decision is rarely "which is stronger" but "is this task worth paying for capability, and can the data leave our network". This article breaks the two routes apart.
The 30-second version
For capability, reasoning, and concurrency, take DeepSeek V4.1-Flash (callable from the EXAIV cloud catalog, native 1M context). For data that must stay inside your network, offline work, and a single machine, take hy4 (2.61GB at Q4_K_M, with official quantizations). DeepSeek wins on ecosystem and quantization breadth; Hunyuan wins on being genuinely lightweight.
Parameters and architecture
| Dimension | Hunyuan hy4 | DeepSeek-V4.1-Flash |
|---|---|---|
| Total parameters | 4.22 billion (dense) | 763 billion (MoE) |
| Architecture | HunYuanDenseV1ForCausalLM | DeepseekV41ForCausalLM |
| Layers / hidden size | 36 / 3072 | 40 / 5120 |
| Attention heads / KV heads | 32 / 8 | 64 / 1 |
| Native maximum position length | 262144 | 1048576 |
| Official weight formats | BF16 / FP8 / GPTQ-Int4 / AWQ-Int4 | BF16 / FP8 (FP4 experts) |
| 4-bit availability | No official 4-bit, strong community GGUF coverage | No official 4-bit, community conversions lead |
The two long-context strategies are different
hy4's 256K is a native label. DeepSeek V4.1-Flash reaches 1M through YaRN position extrapolation, visible as a rope_scaling factor in the official config. Native long context and extrapolated long context are not equivalent in retrieval quality, so if your task is long-document question answering, measure recall on both sides instead of trusting the headline numbers.
Community activity and ecosystem
| Metric | Hunyuan hy4 | DeepSeek-V4.1-Flash |
|---|---|---|
| Monthly downloads | about 1,000 | about 1,750,000 |
| Community likes | about 30 | about 4,900 |
| Family completeness | 0.5B / 1.8B / 4B / 7B / A13B | V3.2, the V4 line, R1, the DSpark series, and more |
| Official 4-bit weights | FP8 plus GPTQ-Int4 and AWQ-Int4 | FP8 |
| Third-party tooling | Limited | Very broad |
DeepSeek's family depth is its hidden advantage
You are not choosing a model, you are choosing a family. DeepSeek has open weights from V3.2 through V4 Pro and V4 Flash plus the speculative-decoding companions, so you can move up and down one line while validating. Hunyuan has a hole in the most commonly used 5B to 50B band: hy4 sits below it and the 80B A13B sits well above it. For roadmap planning that matters more than any single capability.
Licensing
| Model | Licence |
|---|---|
| Hunyuan hy4 | Vendor-specific terms |
| DeepSeek-V4.1-Flash | Per the official model card |
The Hunyuan line uses vendor-specific terms, so confirm usage scale, redistribution, and derivative-model constraints before commercial use. Licence labels also vary across DeepSeek repositories, so always read the specific repository's model card.
Deployment reality
| Dimension | Hunyuan hy4 | DeepSeek-V4.1-Flash |
|---|---|---|
| How you run it | Self-hosted: GGUF plus llama.cpp or Ollama | Called from the EXAIV cloud catalog |
| Hardware floor | 6GB of VRAM, even CPU-only | None, elastic on the platform side |
| Data boundary | Data stays inside your network | Requests go to the cloud |
| Operations cost | Entirely yours | Handled by the platform |
| Latency profile | Very low when local | Depends on network and platform load |
Scenario fit
| Your situation | Take | Why |
|---|---|---|
| Internal network data, offline environment | hy4 | Fully local, no external dependency |
| Complex reasoning, code review, long documents | DeepSeek V4.1-Flash | Capability and reasoning depth |
| Million-token document analysis | DeepSeek V4.1-Flash | Native 1M context |
| High-frequency light classification and rewriting | hy4 | Low latency, low cost |
| Edge deployment | hy4 | The only realistic option |
| Wanting a continuous path from small model to flagship | The DeepSeek family | Complete spectrum |
| Preferring not to maintain an inference environment | DeepSeek V4.1-Flash | Already on the platform |
Conclusion
DeepSeek V4.1-Flash leads clearly on capability, ecosystem, family depth, and native long context. Hunyuan hy4 has exactly one irreplaceable property: it runs on a machine you own, in a space that barely matters. So the decision lands on three business questions rather than model quality — can the data leave your network, does the team have inference operations capacity, and will the licence survive legal review.
Answer those and the choice is usually obvious: hy4 for internal or edge work, DeepSeek V4.1-Flash for everything else. Mature systems run both, with hy4 taking high-frequency low-difficulty traffic and DeepSeek handling the requests that need depth.
Related reading
- hy4 model page — specification, quantization matrix and memory math
- hy4-preview channel notes — what the 1M context channel is for
- Tencent Hunyuan family overview — every Hunyuan product line in one place
- hy4 model selection guide — sizes and where A13B fits
- DeepSeek V4 family overview — the whole DeepSeek family
- hy4 GGUF local deployment — deployment steps and memory math
- hy4 vs Qwen3.8-Flash — against another cloud flagship
- Model directory — models callable on EXAIV today
Sources
Download counts and structural details follow HuggingFace public statistics and the official configs, sampled in November 2026.