LongCat-2.5 vs Olmo 3 7B Think

LongCat-2.5 35

Memory 0, the smallest build is Meituan's W4A4 repository, 1,336 GB, and 1,336 GB × 1.2 = 1,603 GB, far above 256 GB. The BF16 files are 3,562 GB. Runtimes 0, none of the six runs it in a released version: vLLM 0.33.0, SGLang 0.5.23, Transformers 5.22.2 and llama.cpp b12242 have no LongcatCausalLM or pro_v code, and the model code config.json names isn't in the repository. Builds 10, one quantised build from Meituan, the W4A4 repository (4-bit experts, 1,336 GB). Terms 15, MIT in the metadata, the LICENSE file and the card, with nothing added. Download 10, the Hub API reports gated false for both repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it. 0 + 0 + 10 + 15 + 10 + 0 = 35.

Olmo 3 7B Think 75

Memory earns the full 30, since Ollama's 4-bit build is 4.5 GB and fits 8 GB (per the 21 October check of Ollama's library). Runtimes earn 25, with released llama.cpp (b11963), Ollama (v0.40.14, pinning b11963), vLLM, LM Studio and Transformers all running it. Builds earn nothing, because Ai2 publishes no quantised build of its own. Terms earn 10, since the card binds Apache 2.0 to Ai2's Responsible Use Guidelines, a use policy. Download earns 10, with no gate. Hosted earns nothing, as the Hub's provider mapping is empty and Ai2 has no API for it. 30 + 25 + 0 + 10 + 10 + 0 = 75.

LongCat-2.5 75

Chat template 20, chat_template.jinja in the repository (11,823 characters), with a copy in tokenizer_config.json. Tool-calling format 25, the card documents how tools are declared (the OpenAI function format) and how calls come back (tool_calls with an id, a name and JSON arguments, answered by a tool message), in a worked example against an OpenAI-compatible server. Trained tool calling 10, the card describes reinforcement learning on long agentic tasks and shows one tool call in a turn. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, enable_thinking on or off per request through chat_template_kwargs, with the reasoning returned as reasoning_content, both shown on the card. Context 10, the card states no context length, but config.json gives 524,288 positions and the card's own evaluations ran at 512K and 1M sequence lengths after what it calls long-context training, so 128K or more is taken as trained. 20 + 25 + 10 + 0 + 10 + 10 = 75.

Olmo 3 7B Think 35

The chat template earns 20 for chat_template.jinja in the repository. The tool-calling format earns 10, since only the template and vLLM's own parser describe it. Trained tool calling earns nothing, because Ai2's report says tool calling was trained into the Instruct model, not Think. Structured output earns nothing. Reasoning control earns nothing, since it always thinks. Context earns 5 for 65,536 tokens trained. 20 + 10 + 0 + 0 + 0 + 5 = 35.

LongCat-2.5 60

File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the meituan-longcat organisation, the name of Meituan's GitHub organisation that the card links for deployment, and the card's licence names Meituan (10). Safety evaluation 0, no safety results on the card. Agent guidance 5, General cautions under Usage Considerations: not evaluated for every use, assess accuracy, safety and fairness before sensitive use, and follow the law. Licence risk 15, MIT with no use policy, no threshold and no right to change the terms. Security programme 0, no way to report a flaw on the card beyond a general contact, and Meituan's own security pages weren't looked up, so this scores as absent and is an open question. 25 + 15 + 0 + 5 + 15 + 0 = 60.

Olmo 3 7B Think 75

File safety earns 25, safetensors only and nothing from the repository runs. Provenance earns 15, files in the allenai organisation Ai2 links to, with a checksum for every file. Safety evaluation earns 20, as Ai2 publishes its safety results and the OLMES harness to rerun them. Agent guidance earns 5 for the card's general cautions. Licence risk earns 5, losing 5 for disallowed uses beyond the law and 5 because Ai2 can update the guidelines and end access at its discretion. The security programme earns 5 for a reporting route, a security.txt now past its expiry and a channel for security concerns in the guidelines, with no public advisories. 25 + 15 + 20 + 5 + 5 + 5 = 75.

LongCat-2.5 46

Model card 11, Intended use, limitations (the usage considerations), the architecture and the parameter counts are on the card. Training data 5, A general description of the training stages and where the reinforcement learning tasks came from, with no sources, sizes or cut-off. Last change 20, the last commit, on 10 November 2026, updated the card, on the day of this check. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (9 and 10 November 2026) has a reply from a meituan-longcat member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, LongCat-2.0 stays in its own repositories and 2.5 came out in new ones, with no dated note on the older ones that we read. File health 5, the template is in both places and agrees, but config.json's auto_map names configuration_longcat_oe and modeling_longcat_oe, which aren't in the repository, and the tokenizer config's 131,072-token length is a quarter of the config's 524,288 positions. 11 + 5 + 20 + 0 + 5 + 5 = 46.

Olmo 3 7B Think 52

The model card earns 17, missing only the context length. Training data earns the full 20, as every dataset is released with sources and sizes. The last change earns 10, a card fix on 25 June 2026, within 180 days. Responsiveness earns nothing, with no Ai2 reply among the 4 replies in the discussions. Version policy earns 5, with earlier and later models in their own repositories and no dated notes. File health earns nothing, because the template's default prompt contradicts the card's on the cut-off and a stray swap file and an unanswered report sit in the repository. 17 + 20 + 10 + 0 + 5 + 0 = 52.