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Llama 5 vs DeepSeek V4.1 Flash

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Open-Weight Models · verified 13 Sept 2026

Llama 5Metacurrent
DeepSeek V4.1 FlashDeepSeekcurrent
3 slots left
SpecificationLlama 5DeepSeek V4.1 Flash
SummaryOpen-weight flagship with recursive self-improvement.Twice the parameters of the Flash it replaces, and cheaper to run.
Context—1M
Input ($/Mtok)—$0.3
Output ($/Mtok)—$1.2
LicenceLlama licenceMIT
Max output—256K
Parameters600B+552B total, 8B / 16B active
Released—10 Sep 2026
Model ID—deepseek-flash
CategoryOpen-Weight ModelsOpen-Weight Models
OfficialMeta ↗DeepSeek ↗

Highlighted rows are where these differ.

Llama 5

  • Refines its own reasoning and generates synthetic training data

Best for open frontier.

Full spec sheet →

DeepSeek V4.1 Flash

  • 552B total, 8B active while reading the prompt and 16B while generating, with a 1M token context
  • DeepSeek says it beats V4-Pro; V4-Pro requests route to it from 14 September 2026
  • MIT licence, native image input, and a KV cache about a quarter the size of V4-Flash's

Best for cheap agentic coding with images.

Full spec sheet →