Dataset updated 2026-10-31DeepSeek V4.1 Flash
DeepSeek V4.1 Flash publishes its weights, but at 748B parameters (16B active per token) no consumer machine holds the checkpoint. This page covers the access paths that work and the open models that actually run locally.
- Parameters
- 748B(16B active)
- Format
- API
- Runs locally
- No
- Best for
- Agentic coding, Reasoning, Long context, Vision
Why you can't run DeepSeek V4.1 Flash locally
At 748B parameters (16B active per token), a Q4-class build of DeepSeek V4.1 Flash would need roughly 449 GB, only a maxed-out 512GB Mac Studio could even hold the weights, with no real headroom. That figure is arithmetic, not opinion: 0.6 GB per billion parameters is the standard Q4 rule we apply across the whole catalog. The weights themselves are public (official source linked below); capacity, not licensing, is the wall.
What works instead: the hosted API. For most workloads, the open models below deliver the same job on hardware that fits under a desk.
Sep 10, 2026 refresh of V4 Flash, MIT, updated on Oct 17, 2026 as DeepSeek-V4.1-Flash-1017: a minor update with the same config and weight layout, stronger on reasoning, coding and agent tasks. Multimodal (image + text) MoE: 552B backbone plus a 196B sparsely-accessed Engram memory, 748B in the GGUF header (the 763B safetensors total on Hugging Face also counts the DSpark draft layers and the vision encoder), 8B active on prefill / 16B on decode, 1M context. Unsloth GGUFs of 1017 start at 233 GB (UD-IQ1_S), 250 GB (UD-IQ1_M) and 300 GB (UD-IQ2_XXS): 1-bit and 2-bit builds that need a 512GB Mac, a class ModelFit never ranks. Ollama lists only a cloud tag.
What to run locally instead of DeepSeek V4.1 Flash
| Model | Params | Runs on | Use |
|---|---|---|---|
| Qwen3 235B A22B | 235B | from 192 GB machines | quality |
| Qwen3.5 122B-A10B Instruct | 122B | from 96 GB machines | frontier-level reasoning |
| DeepSeek-R1 671B | 671B | from 512 GB machines | reasoning |
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Frequently asked questions
Can I run DeepSeek V4.1 Flash locally?
Not on hardware you can buy. The weights are public, but DeepSeek V4.1 Flash is a 748B-parameter model (16B active), and a Q4-class build would need roughly 449 GB, only a maxed-out 512GB Mac Studio could even hold the weights, with no real headroom. Until the ecosystem ships a smaller official build, the API or a smaller open model is the practical path.
How do I access DeepSeek V4.1 Flash?
Through the vendor's hosted API. The official source is linked on this page.
What is the best local alternative to DeepSeek V4.1 Flash?
Qwen3 235B A22B is the strongest local model we track (235B, from 192 GB machines), with Qwen3.5 122B-A10B Instruct close behind. Both run on a single high-memory Mac or GPU, see their pages for exact hardware.
Cite this page
ModelFit: DeepSeek V4.1 Flash, specs, memory math and hardware verdicts. https://modelfit.io/models/deepseek-v4.1-flash (dataset updated 2026-10-31, CC BY 4.0).