Model Freshness Tracker
Analyzes how recently AI models and their data have been updated. Track freshness scores, identify stale data, and see which providers keep their models most up to date.
100.0
out of 100
300
models updated
300
models updated
Claude Fable 5.1
0m ago
Model Freshness Distribution
Freshness Tier Distribution
Models grouped by how recently their data was last updated.
Freshest Models
Top 20Models with the most recently updated data, ranked by freshness score.
| # | Model | Provider | Last Updated | Freshness |
|---|---|---|---|---|
| 1 | Claude Sonnet 5 (batch) | Anthropic | 0m ago | 100 |
| 2 | Fugu Ultra | sakana | 0m ago | 100 |
| 3 | North Mini Code (free) | Cohere | 0m ago | 100 |
| 4 | Kimi K2.7 Code | Moonshot AI | 0m ago | 100 |
| 5 | Claude Fable Latest | ~anthropic | 0m ago | 100 |
| 6 | Nemotron 3.5 Content Safety | NVIDIA | 0m ago | 100 |
| 7 | GLM Latest | ~z-ai | 0m ago | 100 |
| 8 | Hy-MT2-7B | Tencent | 0m ago | 100 |
| 9 | Qwen3.8 27B | Alibaba | 0m ago | 100 |
| 10 | Dots3-Note Preview (free) | dots-studio | 0m ago | 100 |
| 11 | Gemini 3.7 Flash | 0m ago | 100 | |
| 12 | Gemini 3.7 Flash (batch) | 0m ago | 100 | |
| 13 | Seed 2.1 Turbo | ByteDance | 0m ago | 100 |
| 14 | Qwen3.8 2.4T A95B | Alibaba | 0m ago | 100 |
| 15 | Seed-2.0-Code | ByteDance | 0m ago | 100 |
| 16 | DeepSeek V4 Pro 0813 | DeepSeek | 0m ago | 100 |
| 17 | LFM2.5-2.6B | Liquid AI | 0m ago | 100 |
| 18 | LFM2.5-2.6B (free) | Liquid AI | 0m ago | 100 |
| 19 | Nemotron 3.5 Lightning | NVIDIA | 0m ago | 100 |
| 20 | Nemotron 3.5 Lightning (free) | NVIDIA | 0m ago | 100 |
Stalest Models
Bottom 20Models with the oldest data. These may have outdated scores or missing signal updates.
| # | Model | Provider | Last Updated | Freshness |
|---|---|---|---|---|
| 1 | Claude Fable 5.1 | Anthropic | 0m ago | 100 |
| 2 | Claude Fable 5.1 (batch) | Anthropic | 0m ago | 100 |
| 3 | Claude Fable 5 | Anthropic | 0m ago | 100 |
| 4 | Claude Fable 5 (batch) | Anthropic | 0m ago | 100 |
| 5 | Claude Opus 5.5 | Anthropic | 0m ago | 100 |
| 6 | Claude Opus 5 | Anthropic | 0m ago | 100 |
| 7 | Claude Opus 4.8 | Anthropic | 0m ago | 100 |
| 8 | Claude Opus 4.7 | Anthropic | 0m ago | 100 |
| 9 | GPT-5.5 Pro | OpenAI | 0m ago | 100 |
| 10 | GPT-5.5 Pro (batch) | OpenAI | 0m ago | 100 |
| 11 | GPT-5.5 | OpenAI | 0m ago | 100 |
| 12 | Gemini 3.1 Pro Preview Custom Tools | 0m ago | 100 | |
| 13 | Gemini 3.1 Pro Preview | 0m ago | 100 | |
| 14 | Gemini 3.1 Pro Preview (batch) | 0m ago | 100 | |
| 15 | GPT-5.4 Pro | OpenAI | 0m ago | 100 |
| 16 | GPT-5.4 Pro (batch) | OpenAI | 0m ago | 100 |
| 17 | GPT-5.4 | OpenAI | 0m ago | 100 |
| 18 | GPT-5.3-Codex | OpenAI | 0m ago | 100 |
| 19 | GPT-5.2-Codex | OpenAI | 0m ago | 100 |
| 20 | GPT-5.2 Chat | OpenAI | 0m ago | 100 |
Update Frequency by Provider
How fresh is each provider's data? Sorted by average freshness score across all their models.
| Provider | Models | Avg Score |
|---|---|---|
| ~anthropic | 1 | 100.0 |
| dots-studio | 1 | 100.0 |
| ByteDance | 2 | 100.0 |
| thinkingmachines | 2 | 100.0 |
| Meituan | 1 | 100.0 |
| ~x-ai | 1 | 100.0 |
| sakana | 4 | 100.0 |
| ~z-ai | 2 | 100.0 |
| Liquid AI | 3 | 100.0 |
| NVIDIA | 6 | 100.0 |
| ~deepseek | 3 | 100.0 |
| inclusionai | 4 | 100.0 |
| meta | 8 | 100.0 |
| aion-labs | 4 | 100.0 |
| Upstage | 2 | 100.0 |
| Tencent | 6 | 100.0 |
| Xiaomi | 3 | 100.0 |
| inference-net | 2 | 100.0 |
| ~openai | 4 | 100.0 |
| IBM | 1 | 100.0 |
| Moonshot AI | 6 | 100.0 |
| Inception | 2 | 100.0 |
| prism-ml | 2 | 100.0 |
| elorian | 1 | 100.0 |
| xingchen-agi | 1 | 100.0 |
| reflection | 1 | 100.0 |
| moondream | 2 | 100.0 |
| unbiased | 2 | 100.0 |
| ~unbiased | 1 | 100.0 |
| scaledown | 2 | 100.0 |
| StepFun | 1 | 100.0 |
| typesafe | 1 | 100.0 |
| perceptron | 1 | 100.0 |
| fireworks | 1 | 100.0 |
| Alibaba | 14 | 100.0 |
| Cohere | 5 | 100.0 |
| DeepSeek | 12 | 100.0 |
| MiniMax | 4 | 100.0 |
| Cursor | 2 | 100.0 |
| Microsoft | 1 | 100.0 |
| ricursiveai | 1 | 100.0 |
| particle-ai | 1 | 100.0 |
| recursive | 1 | 100.0 |
| Meta | 5 | 100.0 |
| Mistral AI | 5 | 100.0 |
| 25 | 100.0 | |
| Zhipu AI | 17 | 100.0 |
| OpenAI | 84 | 100.0 |
| Anthropic | 30 | 100.0 |
| xAI | 9 | 100.0 |
Methodology
Freshness Score
Computed as 100 minus the number of hours since the last update, capped at 100 hours. A score of 100 means the model was just updated; a score of 0 means it has not been updated in over 100 hours (4+ days).
Freshness Tiers
Models are grouped into five tiers based on update recency: Just Updated (<1h), Fresh (1-6h), Recent (6-24h), Aging (1-7d), and Stale (>7d). Models without a known update timestamp are classified as Stale.
Why Freshness Matters
Stale data can lead to inaccurate rankings and outdated signal scores. Models with fresh data reflect the latest pricing, capabilities, and benchmark results. Monitoring freshness helps identify data pipeline issues early.
Explore More
Dive deeper into model tracking, release velocity, and weekly trend analysis across the AI ecosystem.
Data freshness measures how recently each AI model's information has been updated. A freshness score of 100 means the model was just updated, while 0 means its data is over 100 hours (4+ days) old.
Our data pipeline refreshes model information hourly from multiple API sources. Each update pulls the latest pricing, capabilities, and benchmark data for all tracked models.
Stale data can lead to inaccurate rankings and outdated signal scores. Models with fresh data reflect the latest pricing changes, capability updates, and benchmark results, ensuring you make decisions based on current information.
Models are grouped into five tiers: Just Updated (under 1 hour), Fresh (1-6 hours), Recent (6-24 hours), Aging (1-7 days), and Stale (over 7 days). Models without a known update timestamp are classified as Stale.