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// 1h agoBENCHMARK RESULT
DeepSeek V4.1 Flash stumbles on PC build eval
Mia's AI Lab evaluated a local quant of DeepSeek V4.1 Flash against the viral 3D PC assembly animation challenge, revealing significant visual and logic flaws compared to frontier cloud models. The test highlights the persistent spatial reasoning and coordination gap between fast open-weight models and multi-agent frontier systems on heavy code-generation tasks.
// ANALYSIS
While running massive models locally is increasingly viable, complex spatial reasoning remains a brutal filter that separates cheap inference from frontier capability.
- –The benchmark reproduces Mr Tactical's multi-agent Claude test, which required over seven hours and $138 in compute to generate a functioning animated PC assembly in code.
- –Running a 1017-quantized build locally, DeepSeek V4.1 Flash struggled with component hierarchy and state transitions in the resulting animation.
- –The breakdown illustrates that raw context window and token speed cannot substitute for multi-step architectural planning during complex front-end synthesis.
- –Evaluators are turning to GLM 5.3 Flash and Sonnet as the next comparison points to map where lightweight models fail on visual code tasks.
// TAGS
deepseek-v4-1-flashdeepseekbenchmarkevaluationai-codingcode-generationopen-weights
DISCOVERED
1h ago
2026-11-14
PUBLISHED
1h ago
2026-11-14
RELEVANCE
7/ 10
AUTHOR
0x0SojalSec