FINAL-Bench/Darwin-Prediction-Weather
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Which Weather Model Is Most Accurate? We Score Them Every Day, in the OpenOrganizations
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Which Weather Model Is Most Accurate? We Score Them Every Day, in the Open
FINAL-Bench
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dataset about 13 hours ago
reacted to SeaWolf-AI's post with ā¤ļøšš about 13 hours ago
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š¦ļø Which weather model is most accurate? We score them every day, in the open.
We released two things on Hugging Face:
š Global Weather Model Leaderboard
Every day it records what each global model predicted for 24 world cities, compares it with what actually happened (ERA5), and updates the ranking. ECMWF IFS and AIFS, NOAA GFS and AIGFS, DWD ICON, JMA, ECCC GEM, MET Norway, side by side, on the same cases, since 1 January 2026.
Four elements, four tabs: max temperature, min temperature, wind, precipitation. Forecast leads from 1 to 7 days, with 8 to 10 days joining as they are verified.
š§¬ Darwin-Prediction-Weather
VIDRAFT's weather prediction system: a fusion engine that combines global forecasts, learning only from days already observed. It holds the lowest error in all four elements at every lead on the 2026 record, and the lowest error in all 15 evaluated cells of the WeatherBench 2 (2020) protocol.
What the 2026 record shows so far:
ā¢ AI models now lead physics models at the major centres (AIFS vs IFS, AIGFS vs GFS)
ā¢ Fusion goes further: 7-day max temperature RMSE 2.09 Ā°C vs 2.41 Ā°C for the next model
Also inside: yesterday's results with a daily WIN for the closest model, a 10-day outlook for every city, champions by city and by month, and a Live Earth map with wind, clouds, radar and temperature.
Every forecast and every observed value is open as CSV, so anyone can check the scores.
š Article: https://huggingface.co/blog/FINAL-Bench/which-weather-model-is-most-accurate-we-score-them
š Leaderboard: FINAL-Bench/Weather-Model-Leaderboard
š§¬ Model: FINAL-Bench/Darwin-Prediction-Weather
š Daily record: FINAL-Bench/Weather-Model-Forecast-Archive
Questions, corrections and new models to add are welcome.
We released two things on Hugging Face:
š Global Weather Model Leaderboard
Every day it records what each global model predicted for 24 world cities, compares it with what actually happened (ERA5), and updates the ranking. ECMWF IFS and AIFS, NOAA GFS and AIGFS, DWD ICON, JMA, ECCC GEM, MET Norway, side by side, on the same cases, since 1 January 2026.
Four elements, four tabs: max temperature, min temperature, wind, precipitation. Forecast leads from 1 to 7 days, with 8 to 10 days joining as they are verified.
š§¬ Darwin-Prediction-Weather
VIDRAFT's weather prediction system: a fusion engine that combines global forecasts, learning only from days already observed. It holds the lowest error in all four elements at every lead on the 2026 record, and the lowest error in all 15 evaluated cells of the WeatherBench 2 (2020) protocol.
What the 2026 record shows so far:
ā¢ AI models now lead physics models at the major centres (AIFS vs IFS, AIGFS vs GFS)
ā¢ Fusion goes further: 7-day max temperature RMSE 2.09 Ā°C vs 2.41 Ā°C for the next model
Also inside: yesterday's results with a daily WIN for the closest model, a 10-day outlook for every city, champions by city and by month, and a Live Earth map with wind, clouds, radar and temperature.
Every forecast and every observed value is open as CSV, so anyone can check the scores.
š Article: https://huggingface.co/blog/FINAL-Bench/which-weather-model-is-most-accurate-we-score-them
š Leaderboard: FINAL-Bench/Weather-Model-Leaderboard
š§¬ Model: FINAL-Bench/Darwin-Prediction-Weather
š Daily record: FINAL-Bench/Weather-Model-Forecast-Archive
Questions, corrections and new models to add are welcome.
reacted to SeaWolf-AI's post with š§ š¤š¤šā¤ļø 8 days ago
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SuperCLUEās November 2026 results highlight why category scores matter when choosing a model.
Across the 19 published entries, here are the highest displayed scores in each category, followed by the leader among models labeled open:
ā¢ Agentic coding: GPT-6.1-Sol (69.23); open: DeepSeek-V4.1-Flash-1017 (65.38).
ā¢ Mathematical and scientific reasoning: GPT-6.1-Sol (76.32); open: Darwin-180B-RSI-R3 (73.68).
ā¢ Hallucination control: Gemini-4-Argon (83.19); open: Kimi-K3.1-Pro (67.78).
ā¢ Precise instruction following: Gemini-4-Argon and GPT-6.1-Sol (68.97 each); open: Kimi-K3.1-Pro (44.83).
ā¢ Ultra-long context: Gemini-4-Argon (95.63); open: Kimi-K3.1-Pro (87.25).
On the overall leaderboard, Gemini-4-Argon (73.62) and GPT-6.1-Sol (71.76) have the highest displayed scores, but neither has an official rank number. Kimi-K3.1-Pro (61.46) holds official rank No. 1 and leads the open models overall, followed by DeepSeek-V4.1-Flash-1017 (58.95, official No. 2) and GLM-5.3 (50.66, official No. 3).
These comparisons include entries whose official rank is ā-ā. Among officially ranked open models only, DeepSeek leads mathematical and scientific reasoning at 71.05. āOpenā follows SuperCLUEās classification, not an independent license review. Scores are benchmark points, not error rates; small differences and results from a Chinese-language-focused evaluation need validation on your own workloads. Detailed evaluation settings and the aggregation formula were not verified for this summary.
Read the full breakdown: https://huggingface.co/blog/FINAL-Bench/superclue-november-2026-category-leaders-open-mode
Source: SuperCLUE results released November 5, 2026
https://www.superclueai.com/homepage
Official November data: https://www.superclueai.com/data/generalboard/2026%E5%B9%B411%E6%9C%88.xlsx
Across the 19 published entries, here are the highest displayed scores in each category, followed by the leader among models labeled open:
ā¢ Agentic coding: GPT-6.1-Sol (69.23); open: DeepSeek-V4.1-Flash-1017 (65.38).
ā¢ Mathematical and scientific reasoning: GPT-6.1-Sol (76.32); open: Darwin-180B-RSI-R3 (73.68).
ā¢ Hallucination control: Gemini-4-Argon (83.19); open: Kimi-K3.1-Pro (67.78).
ā¢ Precise instruction following: Gemini-4-Argon and GPT-6.1-Sol (68.97 each); open: Kimi-K3.1-Pro (44.83).
ā¢ Ultra-long context: Gemini-4-Argon (95.63); open: Kimi-K3.1-Pro (87.25).
On the overall leaderboard, Gemini-4-Argon (73.62) and GPT-6.1-Sol (71.76) have the highest displayed scores, but neither has an official rank number. Kimi-K3.1-Pro (61.46) holds official rank No. 1 and leads the open models overall, followed by DeepSeek-V4.1-Flash-1017 (58.95, official No. 2) and GLM-5.3 (50.66, official No. 3).
These comparisons include entries whose official rank is ā-ā. Among officially ranked open models only, DeepSeek leads mathematical and scientific reasoning at 71.05. āOpenā follows SuperCLUEās classification, not an independent license review. Scores are benchmark points, not error rates; small differences and results from a Chinese-language-focused evaluation need validation on your own workloads. Detailed evaluation settings and the aggregation formula were not verified for this summary.
Read the full breakdown: https://huggingface.co/blog/FINAL-Bench/superclue-november-2026-category-leaders-open-mode
Source: SuperCLUE results released November 5, 2026
https://www.superclueai.com/homepage
Official November data: https://www.superclueai.com/data/generalboard/2026%E5%B9%B411%E6%9C%88.xlsx
upvoted an article 8 days ago
Article
SuperCLUE November 2026: Category Leaders and the Full 19-Model Score Ranking
FINAL-Bench
ā¢ ā¢ 8 upvoted an article 12 days ago
Article
The Sleeper in the Weights: We Planted a Backdoor in an Agent, and Only the Kernel Caught It
FINAL-Bench
ā¢ ā¢ 7 liked a
Space 12 days ago
upvoted an article 12 days ago
Article
ViKernel: Why the Kill Switch Must Live Inside the Model
FINAL-Bench
ā¢ ā¢ 11 reacted to SeaWolf-AI's post with ā¤ļøšš„š 12 days ago
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š What if the kill switch lived inside the model itself?
For 50 years, the operating system lived inside the computer. Now the operating system lives inside the AI.
Today we're sharing ViKernel : Weight-Native OS, a Secure OS wired directly into the weights of an LLM.
š§ How it works
ViKernel wires CPU, NPU (vector unit), RAM and ROM circuits into the model weights, runs them accelerated on GPU or NPU, and boots a Secure OS on top.
ā” Boots in the weights: change a single byte and it locks itself
āļø Decides in the weights: every action is allowed or blocked by rule, and persuasion does not change the verdict
š Remembers in the weights: every decision is sealed in a tamper-evident chain
š Stops in the weights: anyone can stop it, and restarting requires a signed key
The original weights stay untouched, so the model keeps its skills. It plugs into any LLM or VLM.
Why the kill switch belongs inside the model: external guardrails can be removed, argued with, or rewritten. A switch that travels with the weights cannot be left behind. We see it as one layer of defense in depth, alongside hardware stops where you have them.
š Read the full write-up:
https://huggingface.co/blog/FINAL-Bench/vikernel-why-the-kill-switch-must-live-inside-the
š„ļø Try the desktop demo (Terminal, Kill Switch Lab, Leak Test, Audit Viewer, and a Kernel Guard game):
FINAL-Bench/ViKernel-Desktop
Try it in 30 seconds: press š KILL, type
For 50 years, the operating system lived inside the computer. Now the operating system lives inside the AI.
Today we're sharing ViKernel : Weight-Native OS, a Secure OS wired directly into the weights of an LLM.
š§ How it works
ViKernel wires CPU, NPU (vector unit), RAM and ROM circuits into the model weights, runs them accelerated on GPU or NPU, and boots a Secure OS on top.
ā” Boots in the weights: change a single byte and it locks itself
āļø Decides in the weights: every action is allowed or blocked by rule, and persuasion does not change the verdict
š Remembers in the weights: every decision is sealed in a tamper-evident chain
š Stops in the weights: anyone can stop it, and restarting requires a signed key
The original weights stay untouched, so the model keeps its skills. It plugs into any LLM or VLM.
Why the kill switch belongs inside the model: external guardrails can be removed, argued with, or rewritten. A switch that travels with the weights cannot be left behind. We see it as one layer of defense in depth, alongside hardware stops where you have them.
š Read the full write-up:
https://huggingface.co/blog/FINAL-Bench/vikernel-why-the-kill-switch-must-live-inside-the
š„ļø Try the desktop demo (Terminal, Kill Switch Lab, Leak Test, Audit Viewer, and a Kernel Guard game):
FINAL-Bench/ViKernel-Desktop
Try it in 30 seconds: press š KILL, type
run weather (refused), then resume --key vikernel-demo.