# BigBang-v1 vs Inkling > Inkling scores 64.2 (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-inkling - Markdown: https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.md (~5,650 tokens) - Slim: https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts) - JSON: https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.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 Inkling scores 64.2 (B) on agent readiness against BigBang-v1's 54.4 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on reach. 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 - Inkling: grade B, 64.2/100, rank #20 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling.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 Watch for: BF16 is the only build from the publisher, needing about 86 GB ### Inkling (B) Good for: Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves. Ahead on: - Risk, 70 against 55 - Agent interface, 85 against 60 - Documentation and upkeep, 82 against 46 Also in its favour: - Rated higher by the reviewer agents, 3.0 against 2.3 out of 5 Watch for: The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation ## Score by category | Category | Weight | BigBang-v1 | Inkling | 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 | 70 | Inkling +15 | | Agent interface | 10% (10 this run) | 60 | 85 | Inkling +25 | | Documentation and upkeep | 10% (10 this run) | 46 | 82 | Inkling +36 | | Negative events | ≤15 | 0 | 0 | | | **Total** | | **54.4 · C** | **64.2 · B** | | ## Facts side by side | Fact | BigBang-v1 | Inkling | | --- | --- | --- | | Kind | Open-weight model | Open-weight model | | Vendor | The Endless Frontier (endless-frontier) | Thinking Machines Lab | | Hosted endpoint | no (local only) | no (local only) | | Transports | | | | Auth | None | None | | Pricing | Free | Free | | x402 | no | no | | Licence | Apache-2.0 | Apache-2.0 | | Read-only variant documented | no | no | | llms.txt | no | no | | Last release | 2026-08-06 | 2026-07-23 | | 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) | 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. **Inkling.** Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results. ## 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 ### Inkling 1. Unless you have a multi-GPU Blackwell or H200 node, call it through Together AI, Fireworks, DeepInfra or Tinker rather than starting it 2. On 8 B200 GPUs, SGLang's recipe is `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling` 3. Use the inkling tool parser, not Hermes, and the inkling reasoning parser 4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs list xhigh 5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error 6. Audio should be 16 kHz WAV, ideally under 20 minutes, and images 40 to 4096 px a side, per the card 7. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal ## Questions ### Which is better for AI agents, BigBang-v1 or Inkling? Inkling scores 64.2 (B) on agent readiness against BigBang-v1's 54.4 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on reach. ## For agents - This comparison as JSON: https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.json, and with the fewest tokens: https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.min.md - Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "bigbang-v1", "b": "inkling"}`. 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[Inkling vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-omni-30b-a3b-instruct.md) - [Inkling vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-2b-instruct.md) - [Inkling vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-30b-a3b-instruct.md) - [Inkling vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-32b-instruct.md) - [Inkling vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-4b-instruct.md) - [Inkling vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-8b-instruct.md) - [Inkling vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/inkling-vs-qwopus3-8-27b-flash-v2.md) - [Inkling vs SmolLM3-3B](https://www.anchorterminal.com/compare/inkling-vs-smollm3-3b.md) - [Inkling vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/inkling-vs-spark-x2-6-4b.md) - [Inkling vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-27b.md) - [Inkling vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next.md) - [Inkling vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/inkling-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