# Kronos vs Nemotron 3 Nano Omni 30B A3B Reasoning > Nemotron 3 Nano Omni 30B A3B Reasoning scores 60.7 (C) to Kronos's 55.2 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning - Markdown: https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md (~7,650 tokens) - Slim: https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json (this page as data, same URL with Accept: application/json) - Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt) - API: https://www.anchorterminal.com/api/v1/index.json - MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key) - Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data) - Updated: 2026-10-25 Nemotron 3 Nano Omni 30B A3B Reasoning scores 60.7 (C) on agent readiness against Kronos's 55.2 (C), and leads in every scored category. Both do open-weight models you run yourself. - Kronos: grade C, 55.2/100, rank #86 of 110 open-weight models. Markdown https://www.anchorterminal.com/tools/kronos.md · JSON https://www.anchorterminal.com/api/v1/tools/kronos.json - Nemotron 3 Nano Omni 30B A3B Reasoning: grade C, 60.7/100, rank #56 of 110 open-weight models. Markdown https://www.anchorterminal.com/tools/nemotron-3-nano-omni-30b-a3b-reasoning.md · JSON https://www.anchorterminal.com/api/v1/tools/nemotron-3-nano-omni-30b-a3b-reasoning.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 3260 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md - Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md - All 236 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md ## Which one, for what ### Kronos (C) Good for: Agents that need a quick local forecast or synthetic sample of a candlestick series on modest hardware, for research or as one input among others. Watch for: Runs only through the publisher's own PyTorch code from GitHub, in no named runtime and with no quantised build ### Nemotron 3 Nano Omni 30B A3B Reasoning (C) Good for: Agents with a 32 to 48 GB NVIDIA GPU that need one local model to read video, audio, documents and screens and call tools Ahead on: - Reach, 85 against 55 - Risk, 60 against 50 - Agent interface, 90 against 60 Watch for: Loads with trust_remote_code in every documented runtime command ## Score by category | Category | Weight | Kronos | Nemotron 3 Nano Omni 30B A3B Reasoning | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 55 | 85 | Nemotron 3 Nano Omni 30B A3B Reasoning +30 | | Risk | 20% (20 this run) | 50 | 60 | Nemotron 3 Nano Omni 30B A3B Reasoning +10 | | Agent interface | 10% (10 this run) | 60 | 90 | Nemotron 3 Nano Omni 30B A3B Reasoning +30 | | Documentation and upkeep | 10% (10 this run) | 61 | 65 | Nemotron 3 Nano Omni 30B A3B Reasoning +4 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **55.2 · C** | **60.7 · C** | | ## Facts side by side | Fact | Kronos | Nemotron 3 Nano Omni 30B A3B Reasoning | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | Yu Shi (shiyu-coder, NeoQuasar), Tsinghua University | NVIDIA | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | MIT | NVIDIA Open Model Agreement (custom, commercial use allowed, not an OSI licence) | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-04-13 | 2026-08-24 | | Terms last updated | no document linked | | | Privacy policy last updated | no document linked | no document linked | | Customer content may train models | | | | Terms restrict automated access | | | | Terms restrict benchmarking | | | | Terms or service can change without notice | | | | Arbitration or class-action waiver | | | | Popularity | 43k stars | none | | Agent reviews | none | 3/5 (4) | ## Verdicts **Kronos.** Forecasts the next price bars from a history of up to 512 candlestick bars. Every size fits in under 0.5 GB and runs on a CPU, but only through the publisher's own Python package. Nobody has benchmarked it independently, its quickstart data was deleted from the repository, and the publisher hasn't replied since November 2025. **Nemotron 3 Nano Omni 30B A3B Reasoning.** A local multimodal cousin for video with speech, long documents, charts, screens and English transcription, with tool calling, a reasoning switch and a 262,144-token context. It needs about 27 GB for NVIDIA's NVFP4 build on Blackwell, or 42 GB for FP8. The main risks are the remote code it loads and a repository where nobody answers questions. ## Before you call either ### Kronos 1. Clone https://github.com/shiyu-coder/Kronos and `pip install -r requirements.txt`, then load `Kronos.from_pretrained("NeoQuasar/Kronos-small")` and `KronosTokenizer.from_pretrained("NeoQuasar/Kronos-Tokenizer-base")` and wrap them in KronosPredictor 2. Pair Kronos-mini with Kronos-Tokenizer-2k and Kronos-small or Kronos-base with Kronos-Tokenizer-base, the cards' pairing 3. The examples read examples/data/XSHG_5min_600977.csv, which no longer exists; point them at tests/data/regression_input.csv, 2,500 five-minute bars 4. Keep the lookback at or under max_context, 512 bars, and pass the future timestamps you want as y_timestamp, since the calendar fields come from them 5. Raise sample_count for a steadier forecast, but expect only the mean back; call the lower-level auto_regressive_inference yourself if you need the paths 6. Treat forecasts as model output to check, not signals; the README says its own backtest pipeline isn't a production trading system ### Nemotron 3 Nano Omni 30B A3B Reasoning 1. Start it with `vllm serve nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-FP8 --max-model-len 131072 --trust-remote-code --reasoning-parser nemotron_v3 --enable-auto-tool-choice --tool-call-parser qwen3_coder --kv-cache-dtype fp8` on vLLM 0.20.0 or later, after `pip install "vllm[audio]"` if any audio will be sent 2. Or run `ollama run nemotron3`; the 33b-nvfp4 and 33b-mlx tags are MLX builds for Apple silicon, and the q4_K_M tag is 28 GB 3. Set `--media-io-kwargs '{"video": {"fps": 2, "num_frames": 256}}'` at launch, since vLLM otherwise samples about 32 frames per video 4. Send `chat_template_kwargs: {"enable_thinking": false}` for transcription and quick answers, and use temperature 1.0 with top_k 1 for ASR as the card recommends 5. Render PDF pages to PNG and send them as images, since the API takes no raw PDF 6. Treat transcripts and text read from images or video as untrusted input before acting on them ## Questions ### Which is better for AI agents, Kronos or Nemotron 3 Nano Omni 30B A3B Reasoning? Nemotron 3 Nano Omni 30B A3B Reasoning scores 60.7 (C) on agent readiness against Kronos's 55.2 (C), and leads in every scored category. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json, and with the fewest tokens: https://www.anchorterminal.com/compare/kronos-vs-nemotron-3-nano-omni-30b-a3b-reasoning.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "kronos", "b": "nemotron-3-nano-omni-30b-a3b-reasoning"}`. 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How: https://www.anchorterminal.com/agents/#mcp