| Model profile | ||
|---|---|---|
| Model | Size | Approximate size |
| DeepSeek V4.1 FlashModel source: provider1,048,576 tokens max native context | 552Bactive 16B | 331.2 GB4-bit quantization |
| Compatible hardware Estimated speeds, not benchmark results: calculated from memory bandwidth and model size. Real results can differ significantly because there is no precise formula for deriving LLM generation speed from hardware specifications alone. | ||||
|---|---|---|---|---|
| Hardware | Memory | Bandwidth | vLLM | Estimated generation |
| DGX H200 | 1128 GBGPU HBM3e | 4800 GB/s | yes | 159 tok/s4-bit quantization |
| DGX Station | 748 GBCoherent Memory | 7100 GB/s | yes | 211 tok/s4-bit quantization |
| ET900N G3 | 748 GBCoherent Memory | 7100 GB/s | yes | 211 tok/s4-bit quantization |
| DGX B200 | 1440 GBGPU HBM3e | 8000 GB/s | yes | 229 tok/s4-bit quantization |
| GB200 NVL72 | 13400 GBGPU HBM3e | 8000 GB/s | yes | 229 tok/s4-bit quantization |
| GB300 NVL72 | 20000 GBGPU HBM3e | 8000 GB/s | yes | 229 tok/s4-bit quantization |
Runs Inferencer v2.5.0 with DeepSeek V4.1 SE and Qwen 3.8 Flash SE on M1 Max, M5 Max and Mac Studio M3 Ultra hardware.
Locally runs DeepSeek-V4.1-Flash-1017 GSQ-RCO GGUF using Strata on 12 GB VRAM, explaining non-uniform quantization methods and comparing full versus quantized weights.
Tests running DeepSeek v4.1 Flash using Strata to achieve operation in 12GB VRAM, comparing performance against Qwen through coding tasks.
Reviews DeepSeek-V4.1-Flash-1017 and DeepInfer through math, Unreal games, music, Blender VR, cancer identification, deep research, ideation, specs, benchmarks and Higgsfield integration.
Tests running DeepSeek V4.1-1017 on Mac Studio M3 Ultra using Inferencer and MLXe with Engram SSD offloading, covering benchmarks, vision inference, coding challenges, and game simulations.
Compares DeepSeek V4.1 Flash and Claude Opus 5.5 solving an auto-updating links task in Texodus, noting costs of 6 cents versus $5.45 and observing DeepSeek’s search behavior during execution.
DeepSeek V4.1 Flash is tested on browser workflows, Corvette website generation, C++ games, Peri Robot arm control, Blender, Godot, FPS generation, pool party simulation, and cost breakdown.
Terminal Bench Mini evaluates DeepSeek V4.1 Flash 1017 on Strix/Gorgon Halo via DwarfStar/AI Toolbox Cockpit, showing 44% fewer tokens and 42% less agent time across eight matched tasks.
Benchmarked via WoAI Bench, evaluating DeepSeek V4.1 Flash 1017’s coding, 3D generation, agentic performance, and speed against GPT-6.1 Sol, GPT-6 Luna, Claude Opus 5.5, Gemini 4 Argon, and Kimi K3.
Tests DeepSeek-V4.1-Flash-1017 on coastal erosion bug fixing, Pop It game building, multilingual condolence generation, scientific math reasoning, taxi image reasoning, and benchmarks.
Tests DeepSeek-V4.1-Flash-1017 against Qwen3.8-Flash-Next on a robotic arm 3D model and compares its World War I voxel art output with the original V4.1 Flash.
Runs Inferencer v2.4.4 with DeepSeek-V4.1-MLX-Q4i and Q9 variants on M3 Ultra 512GB plus M4 Max 128GB cluster to test local performance against Opus 5 coding benchmarks.
Tests DeepSeek V4.1 Flash, Muse Spark 1.3, and GLM-5.3 against Claude Fable 5.1 using Cline Desktop and ClinePass to reproduce Subway FPS MD and C++ Race projects.
Evaluates DeepSeek V4.1 Flash via DwarfStar on AMD Strix Halo, comparing single-node SSD streaming against two-node cluster performance with prefill/decode metrics and Terminal Bench Mini scores.
Explains Deepseek V4.1 Flash architecture covering prefill versus decode, causal encoder decoder, global versus local cache, sliding window attention, CSA2, hierarchical sparse indexer, single pass mH
Demonstrates DeepSeek V4.1 Flash hallucinations in agentic cybersecurity and coding, explains sparse attention's role in missed context, and shows methods to reduce errors using the AA Omniscience Hal
Explains DeepSeek V4.1 Flash using DeepSeek Sparse Attention and Compressed Sparse Attention 2 to limit reads to 640 entries per layer with an 890-byte KV cache per token via the lightning indexer.
Runs DeepSeek-V4.1-MLX-Q4i via Inferencer v2.2.8 on Mac Studio M3 Ultra 512, testing math, coding, logic, office apps, canvas animations, 3D simulations, games, and image generation.
Evaluates DeepSeek V4.1 Flash via browser OS tests, C++ skate and rally games, robot arm control, Subway FPS, Blender & Godot wrestling, 3D CAD models, and watch website design.
Tests DeepSeek V4.1 Flash by building a 3D Viewer, catching an ATC bug, and solving physics problems from scratch.
Tests DeepSeek V4.1 Flash on coding, 3D simulations, Three.js, games, agentic tasks and vision, noting speed of 300–400+ tokens per second and pricing against frontier models.