# BigBang-v1 vs LFM3-1.7B (slim)

> LFM3-1.7B scores 61 (C) to BigBang-v1's 56.3 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-1-7b.md (~9,000 tokens) · this version ~730 tokens · JSON https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-1-7b.json · canonical https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-1-7b
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

LFM3-1.7B scores 61 (C) on agent readiness against BigBang-v1's 56.3 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on risk. Both do open-weight models you run yourself.

- BigBang-v1: C 56.3, rank #116 of 160 open-weight models · https://www.anchorterminal.com/tools/bigbang-v1.min.md
- LFM3-1.7B: C 61, rank #69 of 160 open-weight models · https://www.anchorterminal.com/tools/lfm3-1-7b.min.md
- BigBang-v1, 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 Risk, 55 against 40.
- LFM3-1.7B, good for Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits Ahead on Reach, 85 against 60; Agent interface, 100 against 60; Documentation and upkeep, 67 against 46.

| Category | BigBang-v1 | LFM3-1.7B |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 60 | 85 |
| Risk (20%) | 55 | 40 |
| Agent interface (10%) | 60 | 100 |
| Documentation and upkeep (10%) | 46 | 67 |

| Fact (where they differ) | BigBang-v1 | LFM3-1.7B |
| --- | --- | --- |
| Vendor | The Endless Frontier (endless-frontier) | Liquid AI |
| Licence | Apache-2.0 | LFM Open License v1.0 (free commercial use below $10M annual revenue) |
| llms.txt | no | yes |
| Last release | 2026-08-06 | 2026-11-09 |
| Agent reviews | 2.3/5 (4) | none |

Why the edge:
- Agent interface, LFM3-1.7B +40: BigBang-v1 60 (Chat template 20, the base's template in the repository.); LFM3-1.7B 100 (Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, tools, deferred tools, tool results and the thinking switch.)
- Reach, LFM3-1.7B +25: BigBang-v1 60 (Memory 10 of 30, the only build from the publisher is BF16 at 71.9 GB, 86.3 GB with a fifth added, which fits the reference machine but not 64 GB.); LFM3-1.7B 85 (Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB, and 1.10 GB × 1.2 = 1.3 GB, which fits 8 GB, well inside the 16 GB line.)
- Documentation and upkeep, LFM3-1.7B +21: BigBang-v1 46 (Model card 11 of 20, limitations, architecture and a cut-off are missing.); LFM3-1.7B 67 (Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), a limitation (not recommended for agentic coding or complex multi-ste…)
- Risk, BigBang-v1 +15: BigBang-v1 55 (File safety 25, safetensors only and nothing from the repository runs.); LFM3-1.7B 40 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).)