DeepSeek-V4-Flash-0731 VRAM & Memory Requirements

Specific checkpoints with sourced architecture and weight files. FP8 safetensors: 156.71 GiB–182.40 GiB at 8,192 tokens, 1 sequence, FP16 KV, vllm.

This result is an estimate, not a measured trace.Not verifiedFile-backed weights1 known setups

Known working setups

1 known setups

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

DeepSeek-V4-Flash-0731
2× NVIDIA DGX Spark (GB10, 128 GB unified)
Measured by upstream maintainer
Quant:Official FP8 Safetensors
Runtime:vLLM· TP2
Tested:
  • ✓ generation
  • ✓ 1,048,576 context
  • ✓ tool calling
  • ✓ vision
  • ✓ speculative decoding
Measured:75.4 tok/s· 1 stream

2-node DGX Spark deployment for DeepSeek-V4-Flash-Vision-Exp running vLLM TP=2 with DSpark speculative decoding and nvfp4_ds_mla KV cache.

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
155.42 GiB (166,878,536,440 bytes)
Raw KV cache
0.67 GiB (721,420,288 bytes)
Engine extras / workspace
0.63 GiB–26.31 GiB
Total estimated demand
156.71 GiB–182.40 GiB

Published artifacts

QuantizationSelected filesBytesEngineEvidence
FP8 safetensors
fp8
48 safetensors shards
Total selected bytes: 166,878,536,440 (155.42 GiB / 166.88 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
166,878,536,440 (155.42 GiB / 166.88 GB)vllm, sglang, unspecifiedfile-metadata
INT4 theoreticalNo published file152,090,209,247 (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 safetensors156.21 GiB–181.80 GiB156.71 GiB–182.40 GiB158.73 GiB–184.79 GiB
INT4 theoretical
Theoretical rows are not downloadable artifacts.
141.94 GiB–183.21 GiB142.44 GiB–183.84 GiB144.46 GiB–186.32 GiB

Raw KV contribution

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Quantization

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Workload

Context length primarily affects KV cache memory.

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Engine and KV cache type for this estimate.

Workload

Overhead scenario and the prefill workspace.

Topology

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

Replica count is an advanced deployment option. Quantity is nodes or GPUs, not replicas.

Budget

System reserve and safety margin. An empty number keeps the previous value.

GiB (2^30 bytes)

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