DeepSeek V4.1 Flash hands-on tests and comparisons

Same one-line three.js prompt to build Sonic in 3D: DeepSeek took 44m20s, 33.5M tokens and $0.28, while Opus 5.5 took 27m26s, 4.89M tokens and $5.67; the author calls DeepSeek the clear winner.

DeepSeek V4.1 Flash 1017 tops OpenCode's 24-hour API call chart at 8.5T tokens versus 503B for Meta's muse-spark, while new Kimi K3.1 Pro misses the top 18.

In the author's test Kimi K3.1 Pro on MAX failed to beat DeepSeek V4.1 Flash on xhigh, costing $24.12 versus $0.49, with MiniMax at $0.23.

Using the Project Maya engine and Maya-XS 1.6-bit quant on 4x 3090, a user raised decode from 33 to 57 tok/s and prefill from 1626 to 2642 tok/s, cutting a 128K prompt from 114s to 49s while enabling 256K context and image input.

An internal bench compares Morph-abliterated and stock DeepSeek V4.1 Flash: 2% vs 100% refusals with no significant IFEval/MMLU-Pro/GSM8K gaps, and 8% vs 0% recall on whole-repo vuln hunting.

Running a 1.62-bit quant of DeepSeek V4.1 Flash locally on a GX10 ranks first of 34 rows on WikiBench at 5.35/10, with coding 7.75 and research 9.3.

MiaAI posts a TensorFold demo of V4.1 Flash-1017 running official weights with 16 concurrent sessions each holding native 1M context, promising the recipe soon.

Claims vLLM now matches DeepSeek's in-house inference engine on V4.1 Flash decoding, hitting 954K tokens/s per GPU on SemiAnalysis AgentX.

After hitting Claude Sonnet 5.5 limits, a user switched to Gemini 4 Argon and free V4.1 Flash in OpenCode, solving photo contour extraction at a 53:1 cost ratio.

The author argues quantization isn't the main factor; KV cache policy, routing and serving optimizations matter more, with speeds ranging down to 3 tok/s and aggressive context compaction on free tiers.

The open-source Strata project offloads MoE experts to RAM and SSD so a 12GB GPU can run quantized DeepSeek-V4.1-Flash-1017; the 2.00 bpw build is about 257GB and wants 46GB+ RAM and an NVMe SSD.

A user spent about 4B tokens having DeepSeek V4.1 Flash agents build a vulnerable lab of 8 Windows AD and 4 Linux machines, avoiding contaminated CTF benchmarks, and found the swarm struggles to pivot between machines.