Head to head · Open-weight models you run yourself · October 2026 research run
LFM2.5-2.6B vs Ripple-65B Preview
Ripple-65B Preview scores 53.3 (D) on agent readiness against LFM2.5-2.6B's 50.3 (D), and leads in 1 of 4 scored categories. LFM2.5-2.6B leads on reach and documentation and upkeep. Both do open-weight models you run yourself.
Best open-weight models you download and run yourself for AI agents · All 3674 open weights comparisons
Which one, for what
Best for Agents that want a small local helper for tool calls, extraction and RAG on a laptop, phone or CPU, at organisations under the licence's revenue threshold
Ahead on
- Reach, 90 against 45
- Documentation and upkeep, 57 against 49
Watch for
Liquid lists it as deprecated, replaced by LFM3-1.7B; deprecated models stay downloadable but get no further updates
Best for Teams with Blackwell GPUs or a DGX Spark who want an Apache 2.0 coding model to try for terminal and agentic coding work, and can run the publisher's code to serve it.
Ahead on
- Risk, 55 against 50
Watch for
No released runtime runs the architecture, so running it means Ricursive's Python in SGLang 0.5.19 or Transformers' remote code
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Reach LFM2.5-2.6B +45
LFM2.5-2.6B 90
Memory earns the full 30, since Liquid's own 4-bit GGUF is 1.59 GB and fits 8 GB with room to spare. Runtimes earn 25, with the lfm2 architecture in released llama.cpp, vLLM, SGLang and Transformers, and in Ollama through the llama.cpp version it pins. Builds earn 15 for Liquid's own GGUF, MLX and ONNX builds at many precisions. Terms earn 10, a custom licence that is free for commercial use under $10M of annual revenue. Download earns 10, with no gate. Hosted earns nothing, as Hugging Face maps no inference provider and Liquid's docs list no hosted API for it.
Ripple-65B Preview 45
Memory 10 of 30, the smallest 4-bit build is Ricursive's NVFP4 at 57.2 GB, 68.7 GB with a fifth added, which is over 64 GB and fits our reference machine. Runtimes 0, no released runtime runs the ricursive architecture with its own code; Ricursive's SGLang plugin and Transformers' remote code don't count. Builds 10, one quantised precision (NVFP4) from Ricursive. Terms 15, Apache 2.0 with nothing added. Download 10, not gated. Hosted 0, Ricursive serves no API, Hugging Face maps no provider, Together AI's page says coming soon, and GMI Cloud's and OpenRouter's pages weren't read.
Documentation and upkeep LFM2.5-2.6B +8
LFM2.5-2.6B 57
The model card earns 17, with everything but a knowledge cut-off. Training data earns 5 for a general description without a cut-off. The last change earns 20, a card commit on 3 November 2026 naming LFM3-1.7B as the new version. Responsiveness earns 5, with Liquid replies in 2 of 16 discussions. Version policy earns 5, as Liquid now lists the model as deprecated with a replacement but no date. File health earns 5, since the files agree but a report about the card waits without a reply.
Ripple-65B Preview 49
Model card 14 of 20, no limitations and no knowledge cut-off. Training data 5, a general description with token counts and no cut-off. Last change 20, released today. Responsiveness 0, no discussions yet, read as none answered. Version policy 5, a first release, with the NVFP4 checkpoint replaced in place on release day under a commit note. File health 5, tokenizer_config.json carries a second, tool-less chat template and a 131,072-token limit against the card's 1M.
Risk Ripple-65B Preview +5
LFM2.5-2.6B 50
File safety earns 25, safetensors and GGUF only, and nothing from the repository runs to load it or build prompts. Provenance earns 15, files in the LiquidAI organisation Liquid links to, with a checksum for every file. Safety evaluation and agent guidance earn nothing, since Liquid publishes neither. Licence risk earns 10, losing 5 for the revenue threshold, with no use policy and no change since release. The security programme earns nothing, since no security.txt, disclosure policy or security contact was found.
Ripple-65B Preview 55
File safety 15, safetensors only, less 10 because the documented way to run it loads Ricursive's Python. Provenance 15, the files are in the organisation ricursive.com links to, with a checksum on every file. Safety evaluation 10, Ricursive's own FORTRESS and StrongREJECT results. Agent guidance 0, nothing on prompt injection, refusals or safeguards. Licence risk 15, Apache 2.0. Security programme 0, no way to report a flaw.
Score by category
| Category | Weight this run | LFM2.5-2.6B | Ripple-65B Preview | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 90 | 45 | LFM2.5-2.6B +45 |
| Risk | 20%20 | 50 | 55 | Ripple-65B Preview +5 |
| Agent interface | 10%10 | 75 | 75 | even |
| Documentation and upkeep | 10%10 | 57 | 49 | LFM2.5-2.6B +8 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 50.3/100 | D 53.3/100 |
Facts side by side
| Fact | LFM2.5-2.6B | Ripple-65B Preview |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Liquid AI | Ricursive Intelligence |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| Last release | 2026-11-03 | 2026-11-04 |
| Terms last updated | no document linked | not read yet |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | 2.5/5 (4) | none |
How the scores have moved
Ripple-65B Preview
No score change since it was listed.
Verdicts
LFM2.5-2.6B
A small, fast model for tool calls, extraction and long-context steps on a laptop or phone, which Liquid now lists as deprecated in favour of LFM3-1.7B. Liquid's own 4-bit build is 1.6 GB and five common runtimes run it. It always thinks, and organisations over $10M of revenue need another licence. There are no safety results or security contact.
Ripple-65B Preview
A dense 65B coding model from a new lab, pretrained from scratch and released today under Apache 2.0, that Ricursive says leads U.S. open-weight models on Terminal-Bench 2.1. Nobody has checked that yet, and the custom architecture runs only through Ricursive's own SGLang plugin on Blackwell GPUs, with a 57 GB NVFP4 build as the smallest.
Before you call either
LFM2.5-2.6B
- Quickest start is
ollama run LiquidAI/lfm2.5-2.6b, 1.7 GB, orllama-cli -hf LiquidAI/LFM2.5-2.6B-GGUF - With vLLM or SGLang pass
--tool-call-parser lfm2; for vLLM add--reasoning-parser qwen3so the thinking comes back separately - Sample at temperature 0.1, top_k 50 and repetition_penalty 1.1, as the card and generation_config.json set
- Put tools in the system prompt as
List of tools: [...]JSON, or pass tools to apply_chat_template; calls come back as a Python list of function calls, and the system prompt can ask for JSON calls instead - Leave max_tokens unset or generous, since a low cap cuts the reasoning off mid-thought
- Earlier thinking is dropped from the prompt unless
preserve_thinkingis true - Liquid's 328M LFM2.5-2.6B-DSpark drafter speeds decoding about 2.6 times in SGLang and on Apple silicon, per Liquid
- Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented
Ripple-65B Preview
- Run Ricursive's launcher from inference/server with
uv run --script serve.pyon two B200 GPUs; it listens on 127.0.0.1:30000 with a 16K context by default - The launcher turns on
--reasoning-parser rippleand--tool-call-parser ripple; without them tool calls come back as raw text inside tool_call tags - For
tool_choice: "required"setstrict: trueandadditionalProperties: falseon each function, which the README says stopped extra argument fields - Leave room in
max_tokensfor reasoning as well as the answer, since thinking is always on - Use chat_template.jinja, not the template inside tokenizer_config.json, which has no tool support
Questions
Which is better for AI agents, LFM2.5-2.6B or Ripple-65B Preview?
Ripple-65B Preview scores 53.3 (D) on agent readiness against LFM2.5-2.6B's 50.3 (D), and leads in 1 of 4 scored categories. LFM2.5-2.6B leads on reach and documentation and upkeep.
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Machine-readable
- This page as Markdown
/compare/lfm2-5-2-6b-vs-ripple-65b-preview.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/lfm2-5-2-6b.json·/api/v1/tools/ripple-65b-preview.json - From a terminal
anchor compare lfm2-5-2-6b ripple-65b-preview(the CLI) - Over MCP
compare_tools {"a": "lfm2-5-2-6b", "b": "ripple-65b-preview"}at/mcp, no key