DeepSeek V4.1 Flash 1017 552B vs DeepSeek V4.1 Flash 552B

Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.

Quick verdict

Both models need similar VRAM (571.6 GB) at their recommended builds. The choice comes down to benchmarks and architecture.

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Analysis

DeepSeek V4.1 Flash 1017 is a minor update to the September 10 V4.1 Flash, released five weeks later on October 17, 2026. Nothing about the hardware bill changed: the configuration file is identical and the weights are the same 510.3 GB, so this comparison is not about VRAM at all. It is about what five weeks of extra post-training bought, and about the one thing the new build lacks so far, which is any independent check.

Everything structural is the same. Both are 552B-parameter mixture-of-experts models with 16B active per token on decode and 8B on prefill, 40 layers split into a 20-layer encoder and a 20-layer decoder, a 1M-token context window, native image input and an MIT license, and both hold a full-window KV cache to the same 2.3 GB on this site's math, so at any quantization or context length their VRAM totals are identical (about 571.6 GB at an 8k context for the native release). What differs is the post-training, and DeepSeek published a side-by-side table with the release. The new build is ahead on every row the two share, led by Terminal-Bench 4.0 (31.2 to 42.3), ProgramBench (20.3 to 29.1) and Humanity's Last Exam without tools (36.8 to 42.6), while DeepSWE v1.1 moves only from 74.2 to 77.0. DeepSeek also says the update finishes tasks faster with shorter outputs, and it tuned the build for its own agent harness and for Tencent's CodeBuddy and WorkBuddy. Two gaps limit how far to trust the comparison. Every one of these figures is DeepSeek's own run, and no independent lab had re-scored the 1017 build when this page was written. And any GPQA Diamond figure shown for the two builds is the same 90.9 only because this site carries the September score over to 1017 so they rank level; DeepSeek's 1017 card has no GPQA row. Its card also reports Terminal-Bench 4.0, a newer suite than the Terminal-Bench 2.1 (90.6) behind the September build's entry, so there is no like-for-like Terminal-Bench figure to compare. Availability differs slightly too. Community conversions of the September weights, such as a GGUF of about 169 GB and an MLX build of about 239 GB, are weeks old, while conversions of the 1017 weights (an NVFP4 repository of 429.4 GB and an MLX build of 432.0 GB) appeared within hours of release and are unverified, and the two sets are not interchangeable.

Bottom line: If you call DeepSeek's API through the deepseek-flash name you are already on the 1017 build, and DeepSeek's own table says that is a gain for agent and terminal work, with the caveat that it is DeepSeek's table. If you host the weights on a datacenter node, pull the 1017 checkpoint for agent work: it costs exactly the same memory as the September one. If you were hoping for a quantized build that fits a smaller machine, neither has a verified one, and the September community conversions are the more mature but cannot be loaded as the new weights. Stay on the September build only if you need its published GPQA Diamond or Terminal-Bench 2.1 numbers for a like-for-like record.

Where the 1017 update landed: ten rows from DeepSeek's own table

None of these suites has a field in this site's benchmark schema, so they are charted here from DeepSeek's own release table, where the September build appears as a reference column. The 1017 build leads on all ten, by the widest margin on terminal and repository-level agent tasks.

Terminal-Bench 4.0
1017
42.3
September
31.2
ProgramBench
1017
29.1
September
20.3
Humanity's Last Exam, no tools
1017
42.6
September
36.8
Automation-Bench v1.0.6
1017
60.5
September
54.8
Chartography, with tools
1017
83.0
September
78.9
Agents' Last Exam
1017
35.4
September
31.8
BabyVision, with tools
1017
92.5
September
89.6
NL2Repo-Bench
1017
68.2
September
65.4
DeepSWE v1.1
1017
77.0
September
74.2
ZeroBench-main, with tools, pass@5
1017
51.0
September
49.0

DeepSeek's Hugging Face card for the 1017 build and its API changelog, both 17 October 2026; DeepSeek's own runs on its own harnesses (Claude Code for Terminal-Bench 4.0, Mini-SWE-V2 for DeepSWE v1.1). Vendor-reported; no independent reproduction was available at time of writing. Apex Bench is omitted because DeepSeek's two pages name it differently and disagree on the September figure.

VRAM at each quantization (8k context)

FP32
DeepSeek V4.1 Flash 1017 552B
2473.0 GB
DeepSeek V4.1 Flash 552B
2473.0 GB
BF16
DeepSeek V4.1 Flash 1017 552B
1236.5 GB
DeepSeek V4.1 Flash 552B
1236.5 GB
FP16
DeepSeek V4.1 Flash 1017 552B
1236.5 GB
DeepSeek V4.1 Flash 552B
1236.5 GB
Q8_0
DeepSeek V4.1 Flash 1017 552B
657.2 GB
DeepSeek V4.1 Flash 552B
657.2 GB
Q6_K
DeepSeek V4.1 Flash 1017 552B
571.6 GB
DeepSeek V4.1 Flash 552B
571.6 GB
Q5_K_M
DeepSeek V4.1 Flash 1017 552B
571.6 GB
DeepSeek V4.1 Flash 552B
571.6 GB
Q4_K_M
DeepSeek V4.1 Flash 1017 552B
571.6 GB
DeepSeek V4.1 Flash 552B
571.6 GB
Q3_K_M
DeepSeek V4.1 Flash 1017 552B
571.6 GB
DeepSeek V4.1 Flash 552B
571.6 GB
Q2_K
DeepSeek V4.1 Flash 1017 552B
571.6 GB
DeepSeek V4.1 Flash 552B
571.6 GB
NVFP4
DeepSeek V4.1 Flash 1017 552B
571.6 GB
DeepSeek V4.1 Flash 552B
571.6 GB
QuantDeepSeek V4.1 Flash 1017 552BDeepSeek V4.1 Flash 552BDiff
FP322473.0 GB2473.0 GB+0%
BF161236.5 GB1236.5 GB+0%
FP161236.5 GB1236.5 GB+0%
Q8_0657.2 GB657.2 GB+0%
Q6_K571.6 GB571.6 GB+0%
Q5_K_M571.6 GB571.6 GB+0%
Q4_K_M571.6 GB571.6 GB+0%
Q3_K_M571.6 GB571.6 GB+0%
Q2_K571.6 GB571.6 GB+0%
NVFP4571.6 GB571.6 GB+0%

Diff is DeepSeek V4.1 Flash 1017 552B relative to DeepSeek V4.1 Flash 552B. Green = lower VRAM (fits more GPUs).

Model specifications

SpecDeepSeek V4.1 Flash 1017 552BDeepSeek V4.1 Flash 552B
OrgDeepSeekDeepSeek
Parameters552B552B
ArchitectureMoE (16B active)MoE (16B active)
Context1024k tokens1024k tokens
Modalitiestext, visiontext, vision
LicenseMITMIT
CommercialYesYes
Released2026-10-172026-09-10
GPUs (native)0 / 1210 / 121

Benchmark scores

BenchmarkDeepSeek V4.1 Flash 1017 552BDeepSeek V4.1 Flash 552B
GPQA Diamond90.990.9

Green = higher score (better). N/A = not yet available. ~ = inherited from a base model, not independently reported for that release itself.

GPUs that run only DeepSeek V4.1 Flash 1017 552B(0)

Every GPU that runs DeepSeek V4.1 Flash 1017 552B also runs DeepSeek V4.1 Flash 552B.

GPUs that run only DeepSeek V4.1 Flash 552B(0)

Every GPU that runs DeepSeek V4.1 Flash 552B also runs DeepSeek V4.1 Flash 1017 552B.

Which should you use?

Choose DeepSeek V4.1 Flash 1017 552B if:
  • • It's the newer release (2026-10-17 vs 2026-09-10); check the benchmark table above for what actually improved
Choose DeepSeek V4.1 Flash 552B if:
  • No clear spec advantage over DeepSeek V4.1 Flash 1017 552B, see the benchmark and VRAM tables above.

Frequently asked questions

Which is better, DeepSeek V4.1 Flash 1017 552B or DeepSeek V4.1 Flash 552B?
Both are capable models. The best choice depends on your hardware and use case.
How much VRAM does DeepSeek V4.1 Flash 1017 552B need vs DeepSeek V4.1 Flash 552B?
At 8k context, DeepSeek V4.1 Flash 1017 552B needs approximately 571.6 GB of VRAM at its Q4_K_M build, while DeepSeek V4.1 Flash 552B needs 571.6 GB at its Q4_K_M build. At the largest build each ships, DeepSeek V4.1 Flash 1017 552B requires 1236.5 GB (FP16) vs 1236.5 GB (FP16) for DeepSeek V4.1 Flash 552B.
Can you run DeepSeek V4.1 Flash 1017 552B on the same GPUs as DeepSeek V4.1 Flash 552B?
These models have very different VRAM requirements, so they do not share the same compatible GPU set.
What is the difference between DeepSeek V4.1 Flash 1017 552B and DeepSeek V4.1 Flash 552B?
DeepSeek V4.1 Flash 1017 552B has 552B parameters (16B active, MoE) with a 1024k context window. DeepSeek V4.1 Flash 552B has 552B parameters (16B active, MoE) with a 1024k context window.
Which model fits in 24 GB of VRAM, DeepSeek V4.1 Flash 1017 552B or DeepSeek V4.1 Flash 552B?
Neither fits in 24 GB: DeepSeek V4.1 Flash 1017 552B needs 571.6 GB at Q4_K_M and DeepSeek V4.1 Flash 552B needs 571.6 GB at Q4_K_M. Both require a multi-GPU server with 572 GB+ of combined VRAM.
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