# BigBang-v1 vs Kimi K3 > Kimi K3 scores 62.4 (B) to BigBang-v1's 54.4 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side. - Canonical: https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3 - Markdown: https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.md (~5,650 tokens) - Slim: https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.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: 2026-10-21 Kimi K3 scores 62.4 (B) on agent readiness against BigBang-v1's 54.4 (C), and leads in 2 of 4 scored categories. BigBang-v1 leads on reach and documentation and upkeep. Both do open-weight models you run yourself. - BigBang-v1: grade C, 54.4/100, rank #83 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/bigbang-v1.md · JSON https://www.anchorterminal.com/api/v1/tools/bigbang-v1.json - Kimi K3: grade B, 62.4/100, rank #29 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/kimi-k3.md · JSON https://www.anchorterminal.com/api/v1/tools/kimi-k3.json - Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md - All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md ## Which one, for what ### BigBang-v1 (C) Good for: Agents with 96 GB or more that want an Apache 2.0 mixture-of-experts model tuned for research, search and coding, and can do without publisher support. Ahead on: - Reach, 55 against 50 - Documentation and upkeep, 46 against 41 Watch for: BF16 is the only build from the publisher, needing about 86 GB ### Kimi K3 (B) Good for: Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work Ahead on: - Risk, 65 against 55 - Agent interface, 65 against 60 Watch for: 1,561 GB of files at its smallest publisher build, far beyond any single machine ## Score by category | Category | Weight | BigBang-v1 | Kimi K3 | Edge | | --- | --- | --- | --- | --- | | Capability | 35%, pending | pending | pending | not scored in this run | | Reach | 25% (25 this run) | 55 | 50 | BigBang-v1 +5 | | Risk | 20% (20 this run) | 55 | 65 | Kimi K3 +10 | | Agent interface | 10% (10 this run) | 60 | 65 | Kimi K3 +5 | | Documentation and upkeep | 10% (10 this run) | 46 | 41 | BigBang-v1 +5 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **54.4 · C** | **62.4 · B** | | ## Facts side by side | Fact | BigBang-v1 | Kimi K3 | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | The Endless Frontier (endless-frontier) | Moonshot AI | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0 | Kimi K3 License (modified MIT) | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-08-06 | 2026-09-02 | | Terms last updated | no document linked | 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 | | | | Agent reviews | 2.3/5 (4) | 2.3/5 (4) | ## Verdicts **BigBang-v1.** A Qwen3.6-35B-A3B fine-tuned on synthetic research problems, under plain Apache 2.0, for search, science and coding work. The publisher ships BF16 only, about 86 GB to run, and has no report, safety results or replies to questions, so smaller builds and support come from others. **Kimi K3.** Kimi K3 is a 2.8T multimodal agent model with a 1M-token context, parallel tool calls and per-request effort, for long coding and research sessions. Its 1,561 GB of files need a multi-node GPU cluster, so most agents will call a hosted copy. The main risks are Moonshot's Python running at load and prompt time, and no answers in its repository. ## Before you call either ### BigBang-v1 1. On the reference machine use `vllm serve endless-frontier/BigBang-v1 --max-model-len 131072 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` 2. The card says to keep at least 128K of context so its thinking isn't cut short 3. Thinking control isn't documented, try the base template's `enable_thinking` false in chat_template_kwargs and check the output 4. For a smaller build you'll need someone else's quantisation, the publisher has none 5. Validate JSON output yourself or use the runtime's guided decoding ### Kimi K3 1. Start it with SGLang on a node of 8 B300s, sglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 --context-length 65536 --mem-fraction-static 0.82 --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000 2. Use the kimi_k3 tool-call and reasoning parsers in vLLM or SGLang, and validate tool-call arguments against the schema, since vLLM's recipe says K3 sometimes emits a format its parser doesn't expect 3. Pass the whole assistant message back every turn, reasoning_content and tool_calls included, or output becomes unstable 4. Thinking is always on; set reasoning_effort to low or high when max is too slow 5. Sampling per the card is temperature 1.0, with top-p 0.95 for single-step tasks and 1.0 for agentic ones 6. Don't hand an ongoing session from another model to K3, and state boundaries in the system prompt, since Moonshot warns it can act on its own when intent is unclear 7. Without the hardware, call it through Moonshot's API or an inference provider listed on its Hugging Face page ## Questions ### Which is better for AI agents, BigBang-v1 or Kimi K3? Kimi K3 scores 62.4 (B) on agent readiness against BigBang-v1's 54.4 (C), and leads in 2 of 4 scored categories. BigBang-v1 leads on reach and documentation and upkeep. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.json, and with the fewest tokens: https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "bigbang-v1", "b": "kimi-k3"}`. 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[Kimi K3 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b.md) - [Kimi K3 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-5.md) - [Kimi K3 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-7.md) - [Kimi K3 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/kimi-k3-vs-muse-glimmer-30b.md) - [Kimi K3 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-5-lightning-30b-a3b.md) - [Kimi K3 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-30b-a3b.md) - [Kimi K3 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-4b.md) - [Kimi K3 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md) - [Kimi K3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-super-120b-a12b.md) - [Kimi K3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-ultra-550b-a55b.md) - [Kimi K3 vs occamy-1.0](https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.md) - [Kimi K3 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think.md) - [Kimi K3 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-35b-a3b.md) - [Kimi K3 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-397b.md) - [Kimi K3 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-9b.md) - [Kimi K3 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-30b-a3b-instruct-2507.md) - [Kimi K3 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507.md) - [Kimi K3 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-0-8b.md) - [Kimi K3 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-122b-a10b.md) - [Kimi K3 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-2b.md) - [Kimi K3 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-397b-a17b.md) - [Kimi K3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-4b.md) - [Kimi K3 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-9b.md) - [Kimi K3 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-27b.md) - [Kimi K3 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-35b-a3b.md) - [Kimi K3 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-27b.md) - [Kimi K3 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-flash-next.md) - [Kimi K3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-30b-a3b-instruct.md) - [Kimi K3 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-next.md) - [Kimi K3 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-omni-30b-a3b-instruct.md) - [Kimi K3 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-2b-instruct.md) - [Kimi K3 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-30b-a3b-instruct.md) - [Kimi K3 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-32b-instruct.md) - [Kimi K3 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-4b-instruct.md) - [Kimi K3 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-8b-instruct.md) - [Kimi K3 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/kimi-k3-vs-qwopus3-8-27b-flash-v2.md) - [Kimi K3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/kimi-k3-vs-smollm3-3b.md) - [Kimi K3 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/kimi-k3-vs-spark-x2-6-4b.md) - [Kimi K3 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-27b.md) - [Kimi K3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-flash-next.md) - [Kimi K3 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/kimi-k3-vs-thinkingcap-qwen3-8-27b.md) --- Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp