DeepSeek V4.1 Flash 1017 Posts 675.9 TPS
A reported local run pushed DeepSeek V4.1 Flash 1017 to 675.9 tokens per second, highlighting how aggressively inference optimization is advancing. The MIT-licensed, 552B-parameter MoE model activates just 8B–16B parameters per token and supports a 1M-token context window.
The speed is impressive, but throughput claims are highly dependent on hardware, quantization, batching, and runtime configuration. Still, this model makes local deployment look increasingly viable for serious agent workloads.
- –The 1017 checkpoint keeps the same architecture while improving coding, reasoning, agentic, and visual performance.
- –Sparse activation lowers per-token compute despite the model’s enormous total parameter count.
- –Local inference at this speed could make interactive coding agents feel substantially more responsive.
- –Developers should reproduce the benchmark before comparing it with hosted providers or other local runtimes.
- –The model’s 510GB repository and hardware demands mean “local” still primarily describes well-equipped workstations or servers.
DISCOVERED
54m ago
2026-10-22
PUBLISHED
1h ago
2026-10-22
RELEVANCE
AUTHOR
0x0SojalSec