DeepSeek V4.1 Flash needs 550.14 GiB at 8,192 tokens

DeepSeek-V4.1-Flash FP8 safetensors (deepseek-ai/DeepSeek-V4.1-Flash) is 510,286,023,000 bytes (475.24 GiB, 510.29 GB). At 8,192 tokens, 1 sequence, FP16 KV, vllm, typical overhead, the calculator estimates 476.49 GiB–550.14 GiB. Rough estimate. Coverage is partial. The other catalog quant, INT4 theoretical, has no weight file. On NVIDIA DGX Spark (GB10, 128 GB unified), the net budget is 112.00 GiB. FP8 safetensors at 4,096 tokens estimates 476.18 GiB–549.77 GiB. The verdict is Does not fit. On GeForce RTX 5090 32GB (desktop), the net budget is 30.00 GiB. FP8 safetensors at 4,096 tokens estimates 476.18 GiB–549.77 GiB. The verdict is Does not fit. This catalog has no calibration trace and no planned benchmark for this model. The ranges are calculator estimates.

This result is an estimate, not a measured trace.Not verifiedFile-backed weights3 known setups

VRAM by quant at 8,192 tokens

1 sequence, FP16 KV, typical overhead. Each total is the calculator for that catalog quant. This catalog has no calibration trace and no planned benchmark for this model. The ranges are calculator estimates.

QuantizationSelected filesEngine8,192 tokens
FP8 safetensors510,286,023,000 (475.24 GiB)vllm476.49 GiB–550.14 GiB
INT4 theoretical
Theoretical rows are not downloadable artifacts.
No weight filellama.cpp356.15 GiB–459.09 GiB

Known working setups

3 known setups

Community and maintainer-tested deployments on real hardware with verified context, quantization, and runtime configurations.

DeepSeek-V4.1-Flash
2× NVIDIA DGX Spark (GB10, 128 GB unified)
Measured by upstream maintainer
Quant:EXL3 2.9 bpw (mul1)(2.9 bpw)
Runtime:vLLM· TP2
Offload:Engram n-gram tables (shards 47+48) → NVME
Tested:
  • ✓ generation
  • ✓ 262,144 context
  • ✓ tool calling
  • ✓ vision
  • ✓ speculative decoding
Measured:31.6 tok/s· 1 stream

2-node DGX Spark setup serving DeepSeek-V4.1-Flash with vLLM tensor-parallel size 2 over ConnectX-7 RoCE, EXL3 2.9 bpw mul1 weights, and native NVMe-resident Engram tables.

DeepSeek-V4.1-Flash
3× NVIDIA DGX Spark (GB10, 128 GB unified)
Measured by upstream maintainer
Quant:Native MXFP4 MoE + FP8 Dense
Runtime:SGLang· TP3
Offload:Engram n-gram tables (189 GiB) → NVME
Tested:
  • ✓ generation
  • ✓ ~208K Tested (256K cfg)
  • ✓ tool calling
  • ✓ vision
  • ✓ speculative decoding
Measured:37.9 tok/s· 1 stream

3-node DGX Spark cluster running native MXFP4 experts and FP8 dense weights with SGLang TP=3 over ConnectX-7 RoCE triangle, with NVMe-resident Engram tables.

DeepSeek-V4.1-Flash
4× NVIDIA DGX Spark (GB10, 128 GB unified)
Measured by upstream maintainer
Quant:Native MXFP4 MoE + FP8 Dense (TP=4)
Runtime:SGLang· TP4
Offload:Engram n-gram tables (189 GiB) → NVME
Tested:
  • ✓ generation
  • ✓ 1,048,576 context
  • ✓ tool calling
  • ✓ vision
  • ✓ speculative decoding
Measured:45.4 tok/s· 1 stream

4-node DGX Spark cluster running native MXFP4 MoE and FP8 dense weights with SGLang TP=4, verified 1M context needle test, and 8M pinned KV token pool.

Runs on

Publisher and provenance

Active parameters describe tokens' routed compute, not the full resident model weight footprint. Full-resident weight estimates use total parameters.

Memory layers in this estimate

Artifact bytes, raw KV, engine extras, and total demand are separate. This is not a runtime trace.

Weight artifact
475.24 GiB (510,286,023,000 bytes)
Raw KV cache
0.63 GiB (671,088,640 bytes)
Engine extras / workspace
0.63 GiB–74.28 GiB
Total estimated demand
476.49 GiB–550.14 GiB

Published artifacts

QuantizationSelected filesBytesEngineEvidence
FP8 safetensors
fp8
48 safetensors shards
Total selected bytes: 510,286,023,000 (475.24 GiB / 510.29 GB)
First shard: model-00001-of-00048.safetensors
Last shard: model-00048-of-00048.safetensors
View all 48 shard files
  • model-00001-of-00048.safetensors
  • model-00002-of-00048.safetensors
  • model-00003-of-00048.safetensors
  • model-00004-of-00048.safetensors
  • model-00005-of-00048.safetensors
  • model-00006-of-00048.safetensors
  • model-00007-of-00048.safetensors
  • model-00008-of-00048.safetensors
  • model-00009-of-00048.safetensors
  • model-00010-of-00048.safetensors
  • model-00011-of-00048.safetensors
  • model-00012-of-00048.safetensors
  • model-00013-of-00048.safetensors
  • model-00014-of-00048.safetensors
  • model-00015-of-00048.safetensors
  • model-00016-of-00048.safetensors
  • model-00017-of-00048.safetensors
  • model-00018-of-00048.safetensors
  • model-00019-of-00048.safetensors
  • model-00020-of-00048.safetensors
  • model-00021-of-00048.safetensors
  • model-00022-of-00048.safetensors
  • model-00023-of-00048.safetensors
  • model-00024-of-00048.safetensors
  • model-00025-of-00048.safetensors
  • model-00026-of-00048.safetensors
  • model-00027-of-00048.safetensors
  • model-00028-of-00048.safetensors
  • model-00029-of-00048.safetensors
  • model-00030-of-00048.safetensors
  • model-00031-of-00048.safetensors
  • model-00032-of-00048.safetensors
  • model-00033-of-00048.safetensors
  • model-00034-of-00048.safetensors
  • model-00035-of-00048.safetensors
  • model-00036-of-00048.safetensors
  • model-00037-of-00048.safetensors
  • model-00038-of-00048.safetensors
  • model-00039-of-00048.safetensors
  • model-00040-of-00048.safetensors
  • model-00041-of-00048.safetensors
  • model-00042-of-00048.safetensors
  • model-00043-of-00048.safetensors
  • model-00044-of-00048.safetensors
  • model-00045-of-00048.safetensors
  • model-00046-of-00048.safetensors
  • model-00047-of-00048.safetensors
  • model-00048-of-00048.safetensors
510,286,023,000 (475.24 GiB / 510.29 GB)vllm, sglang, unspecifiedfile-metadata
INT4 theoreticalNo published file381,602,657,897 (theoretical)—theoretical

Memory by quantization and context

Concurrent sequences = 1. KV defaults to FP16. The range includes documented runtime extras for the listed engine. These figures use the same core as the interactive calculator.

Quantization2,048 tokens8,192 tokens32,768 tokens
FP8 safetensors476.02 GiB–549.59 GiB476.49 GiB–550.14 GiB478.37 GiB–552.36 GiB
INT4 theoretical
Theoretical rows are not downloadable artifacts.
355.68 GiB–458.51 GiB356.15 GiB–459.09 GiB358.02 GiB–461.40 GiB

Raw KV contribution

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Assumptions that affect this result

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Quantization

Device type

Workload

Context length primarily affects KV cache memory.

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Runtime

Engine and KV cache type for this estimate.

Workload

Overhead scenario and the prefill workspace.

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How the model is split across devices. Memory is not added together.

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Budget

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