AI Models
DeepSeek-V4.1-Flash on Fireworks： Astra-level DeepSWE at 1/15th the cost
Fireworks 评测 DeepSeek-V4.1-Flash：DeepSWE 达 GPT-6 Astra 水准、成本仅 1/15
DeepSeek-V4.1-Flash on Fireworks: Astra-level DeepSWE at 1/15th the cost
Fireworks AIDeepSeek V4.1-Flash on Fireworks establishes a new cost-performance Pareto frontier by matching top-tier models like GPT-6 Astra on coding accuracy (74.34% vs. 74.12% pass@1 on DeepSWE) at 1/15th the price per task ($0.43 vs. $6.52). Its 552B Mixture-of-Experts architecture features an asymmetric split activation (8B input / 16B output) and advanced KV caching that cuts HBM usage to $1/4$ and SSD storage to $1/8$, achieving a 99% cache hit rate that makes continuous, background software engineering highly affordable. While it trails on standalone academic reasoning tasks like HLE (34.52% vs. Astra's 50.40%), pairing it with Astra in a routed system outscores Astra alone at a fraction of the cost. Developers can deploy DeepSeek V4.1-Flash today via Fireworks Serverless or Dedicated APIs, with US-hosted endpoints and fine-tuning support coming soon—tag @FireworksAI_HQ on X to share what you build.
Open sourceRecommended because
This is worth tracking because it is a concrete model capability signal, not just a passing headline. The source preview points to a change in model capability, availability, benchmark behavior, or developer access. For builders and operators, "DeepSeek-V4.1-Flash on Fireworks： Astra-level DeepSWE at 1/15th the cost" can be used as a checkpoint for model selection, product roadmaps, eval planning, and timing decisions. I keep this thread indexed so future searches around AI model updates, capability shifts, and developer adoption can land on a source-linked page instead of disappearing into a fast-moving feed from Fireworks AI.
What to take from this signal
Context
"DeepSeek-V4.1-Flash on Fireworks： Astra-level DeepSWE at 1/15th the cost" is archived here as a source-linked AI signal from Fireworks AI. The useful part is the connection between DeepSeek-V4, 1-Flash, Fireworks, Astra-level, DeepSWE and model selection, product roadmaps, eval planning, and timing decisions, which makes the item more actionable than a normal feed headline. The source context says: DeepSeek V4.1-Flash on Fireworks establishes a new cost-performance Pareto frontier by matching top-tier models like GPT-6 Astra on coding accuracy (74.34% vs. 74.12% pass@1 on DeepSWE) at 1/15th the price per task ($0.43 vs. $6.52). Its 552B Mixture-of-Experts architecture features an asymmetric split activation (8B input / 16B output) and advanced KV caching that cuts HBM usage to $1/4$ and SSD storage to $1/8$, achieving a 99% cache hit rate that makes continuous, background software engineering highly affordable. While it trails on standalone academic reasoning tasks like HLE (34.52% vs. Astra's 50.40%), pairing it with Astra in a routed system outscores Astra alone at a fraction of the cost. Developers can deploy DeepSeek V4.1-Flash today via Fireworks Serverless or Dedicated APIs, with US-hosted endpoints and fine-tuning support coming soon—tag @FireworksAI_HQ on X to share what you build.
Builder takeaway
For an AI builder, the main takeaway is to watch how this signal changes practical decisions around model quality, latency, cost, eval coverage, and release timing. It can inform what to test next, which product surface to compare, and whether the underlying workflow is ready for real users.
Source context
Fireworks AI remains the authoritative source for the original claim. This page adds a stable archive URL, a short builder interpretation, and related search language so the item can be found later when the original feed has moved on.
Search angles
- DeepSeek-V4.1-Flash on Fireworks： Astra-level DeepSWE at 1/15th the cost AI Models context
- Fireworks AI AI model releases
- DeepSeek-V4, 1-Flash, Fireworks, Astra-level, DeepSWE builder takeaway
- AI model updates, capability shifts, and developer adoption
This page keeps a source preview and a stable archive URL for search discovery. The original source remains authoritative.