Tech • AI • Robotics • Game
DeepSeek V4.1 Flash 1017 Is Insane! Best Open Model Ever?! (Fully Tested)
TL;DR
DeepSeek has released V4.1 Flash 1017, an upgraded coding-focused model that claims stronger benchmark scores, faster completion, shorter outputs and low pricing, while adding broadly available search and fetch tools.
KEY POINTS
Incremental release with wider access
V4.1 Flash 1017 is not a brand-new flagship but a refined version of DeepSeek V4.1 Flash, first launched on September 10 and updated several times since. The latest release is available through DeepSeek chat routes, mobile access and the API, with rollout beginning immediately.
Push toward agentic software development
DeepSeek is concentrating on agentic coding and full project execution rather than one-off code snippets. The model is being tuned with reinforcement learning and self-feedback to handle workflows such as game creation, app building and 3D tasks from start to finish.
Search and fetch APIs opened up
The company has made its search and fetch APIs broadly available, using DeepSeek’s own infrastructure that it says can handle hundreds of millions of requests daily worldwide. Both endpoints are priced at $0.75 per 1,000 calls, and server-side tool calls through supported coding setups are free until October 31 at 16:00 UTC.
Benchmark gains over the previous version
DeepSeek reports sizable jumps on several technical evaluations. On Terminal Bench 4.0, the model rose from 31.2% to 42.3%, ahead of GPT 5.6 Soul at 39.9% in the cited comparison. On DeepSWE 1.1 it scored 77%, and on HLE it improved from 36.8% to 42.6%, indicating stronger reasoning and coding performance.
High speed at low token prices
The model is listed at $0.30 per million input tokens and $1.20 per million output tokens, with a 1 million-token context window. Early tests cited throughput near 244 tokens per second, with some runs approaching 300 tokens per second, placing it among the fastest models in its class while remaining far cheaper than many frontier systems.
Competitive standing, but not dominant
In one multi-domain ranking, the model placed around 10th or 11th overall, reflecting a strong showing without breaking into the very top tier. The gap appears narrow in some categories, particularly in coding and structured project generation, where cost efficiency is a major advantage.
Noticeable progress in 3D and front-end output
Side-by-side project tests showed clear gains over the two-month-old V4.1 Flash baseline in 3D scene generation and front-end work. Reported strengths include better typography, smoother animation, improved scroll effects and more reliable rendering of difficult outputs such as a 360 product viewer.
Price-to-performance stands out in project tests
In one comparison against Opus 5.5, DeepSeek produced a lower-quality but workable result for about $0.23 versus roughly $6, making it about 26 times cheaper, though it took one hour compared with 20 minutes for the more expensive model. In a large voxel-art benchmark, it generated a 2 million-voxel medieval environment in about 25 minutes for around $5.
Cheap enough to challenge stronger rivals
Additional comparisons showed similar trade-offs: a Tesla Roadster 3D task reportedly cost $0.89 on DeepSeek versus $1.70 on GPT-6 Luna, while another max-reasoning test against GPT 6.1 Soul Ultra reportedly came in about 90% cheaper, at roughly $0.44. Output quality often lagged the best premium models, but the cost difference was large enough to keep DeepSeek highly competitive.
Long runtimes remain a weakness
The main limitation is time on complex jobs. Some tasks took 50 minutes for an SVG scene, 1.5 hours for a sandbox-game build, and as long as 7 hours for a more elaborate Blender-based 3D project, even when the final cost was attractive. The model appears especially suited to asynchronous or overnight generation rather than urgent production use.
Training questions remain unresolved
Some outputs reportedly resembled OpenAI-style responses, and the model at times identified itself incorrectly during deeper reasoning traces, prompting speculation about distillation. That remains unproven, but the similarity has become part of the discussion around the system’s rapid gains in coding and visual generation.
CONCLUSION
DeepSeek V4.1 Flash 1017 appears to strengthen the company’s position in low-cost, high-capability AI coding tools by pairing improved benchmarks with useful search infrastructure and stronger 3D generation. Its biggest challenge is consistency and runtime, but its pricing makes it difficult for more expensive rivals to ignore.
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