RigPerDollar

What GPU do you need to run DeepSeek-V4.1-Flash (1017)?

No single GPU. DeepSeek-V4.1-Flash (1017) needs about 502.2 GB at UD-Q4_K_XL, more than any GPU, system or build we price.

Parameters763.21B16B active (mixture-of-experts)
UD-Q4_K_XL GGUF500.71 GBsource
VRAM needed~502.2 GBfile + headroom
Single GPUs the weights fit0context unknown
ReleasedSep 10, 2026source
LicenseMIT
Context window1M tokens

763.21B parameters, 16B active (mixture-of-experts) (Hugging Face, accessed 2026-10-18). UD-Q4_K_XL GGUF: 500.71 GB (source). No context estimate: DeepSeek V4.1 CSA2 compressed sparse attention (compress_ratios, kv_source_layer_ids, index_topk) has no verified llama.cpp KV formula yet (details).

Points at the Oct 17 snapshot DeepSeek-V4.1-Flash-1017, a minor update of the Sep 10 DeepSeek-V4.1-Flash with an identical config.json and parameter count. Card: 552B backbone parameters plus 196B Engram conditional memory (763B in the safetensors), 8B/16B activated (we use 16B), 1M context. No plain Q4_K_M found, so the size is unsloth UD-Q4_K_XL of the 1017 snapshot. Release date is the original V4.1-Flash release.

Other places to get it

Checked Nov 14, 2026. We list only copies we opened and checked. Check file hashes for copies from other uploaders.

Weights-only fits, context unknown. We have no KV cache data for DeepSeek-V4.1-Flash (1017), so every fit on this page only checks that the UD-Q4_K_XL file and headroom fit. How much context fits beside the weights is unknown, so none of these is a proven fit for any context length.

No single GPU in our database fits it. Use multiple GPUs (see calculator).

Speed calculator

estimate

Estimate = bandwidth ÷ GB read per token (the model's listed GGUF file: Q4_K_M for most models, otherwise the quant named in the list; scaled by active/total parameters for MoE), scaled by a per-platform efficiency and fixed per-token costs calibrated to 45 measured llama.cpp benchmarks (2025–26). Fit = file size + 1.5 GB headroom ≤ total VRAM (on Macs, the part of unified memory macOS lets the GPU use by default), and room for at least 4K tokens of context with an 8-bit KV cache. For a model with no KV cache data, only the file and headroom are checked, so a fit says nothing about context. Multi-GPU: VRAM adds, speed stays one card's (a layer split runs the cards in turn); max context uses the total. Speed is for short context. Max context = what is left after the file and a 1 GB runtime reserve ÷ KV cache bytes per token, default FP16 and 8-bit (q8_0) cache. How speed works · how context works

Reported by others

These are speed reports posted by individual users or reviewers. We haven't checked or reproduced them. They are not our estimates, they don't feed the estimator or My Rig, and they can't be compared with the tok/s figures elsewhere on this site or with each other, because each used a different model, quant, engine and test.

What this does and doesn't show

For coding agents, how much total output a machine keeps up with several requests at once, and how long each waits for its first token, matter as much as single-request tok/s. These reports show that for specific setups only; they don't show what you'd get with a different engine, quant or workload.

DeepSeek V4.1 Flash: one Mac Studio M5 Ultra 512 GB and four ASUS GX10 boxes (vLLM TP4), same bench

Reported by @seapy on X
How this run was set up
Model & revisionDeepSeek V4.1 Flash, original weights (chart title: "original weights, no quantization"). seapy doesn't name the snapshot; this site's model entry is the 1017 checkpoint
QuantNone per the chart. The spark-ds41f README says it uses DeepSeek's native FP8/FP4/BF16 weights: "Nothing is re-quantized". Mac file: Unknown
Runtime & versionMac: mlx-serve 26.11.2 by @ddalcu (an MLX-based server for Apple Silicon). GX10: the spark-ds41f recipe by @christopherowen, vLLM with tensor parallel 4 (seapy's reply: "It's vLLM (TP4)"); vLLM version Unknown
TopologyMac: 1x Mac Studio M5 Ultra 512 GB (8 TB). GX10: 4x ASUS GX10 (GB10, 128 GB each), vLLM TP4; seapy says the recipe works without a switchThe GX10 figures are for the whole four-box cluster, not per box. Neither the cluster nor the 512 GB Mac is a hardware entry on this site.
Input / output / contextText and code prompts at concurrency 1 and 16, plus 128K-token and 980K-token prompts for prefill; other prompt and output lengths Unknown
Concurrency1 and 16
Speculative decodingNot stated by seapy for either side. The spark-ds41f README lists "DSpark and CopyDrafter speculative decoding" under Speed and "DSpark speculative decoding with five draft tokens" in its production configuration, so the recipe's documented configuration includes DSpark drafting; seapy doesn't state it. Mac side: Unknown.
How speed was timed"total tok/s" per the chart; the prefill rows are prompt tokens per second. Method otherwise Unknown
Date measuredUnknown (posted 2026-11-11)
Source@seapy on X, 2026-11-11 (post and chart) · seapy's reply: vLLM (TP4) · seapy's reply: no switch · spark-ds41f recipe (GitHub) · mlx-serve (GitHub)
Evidence statusSelf-reported, not independently reproduced

Mac and 4x GX10, total tok/s as charted (drafting not stated; the GX10 recipe's documented configuration includes DSpark)

WhatMac4x GX10Note
Concurrency 1, text52.6 tok/s total73.4 tok/s total—
Concurrency 1, code83.7 tok/s total122 tok/s total—
Concurrency 16, text137 tok/s total330 tok/s totaleveryone's tokens added up
Concurrency 16, code148 tok/s total847 tok/s totaleveryone's tokens added up

Mac and 4x GX10: prompt reading (prefill; drafting not stated)

WhatMac4x GX10Note
128K-token prompt3,325 prompt tok/s7,522 prompt tok/s—
980K-token prompt1,787 prompt tok/s5,505 prompt tok/s—

The Mac column is the chart's other machine: one Mac Studio M5 Ultra 512 GB running mlx-serve 26.11.2.

Prices on the chart are seapy's, dated 11 Nov 2026: Mac $25,799 (apple.com, 512 GB / 8 TB); GX10 $5,999.99 each at Micro Center, $24,000 for four.

seapy's post headline gives speed ratios; those are his, and we don't repeat them.

These are two different setups; the table shows what seapy measured, not which machine to buy.

Caveats

  • seapy doesn't say whether drafting was on for either side; the GX10 recipe's documented configuration includes DSpark drafting with five draft tokens.
  • These are whole-cluster figures for the GX10 side; do not divide or multiply them by the number of boxes.
  • seapy says only "DeepSeek V4.1 Flash"; this site's model entry is the 1017 checkpoint.
  • Self-reported, not independently reproduced.