Head to head · Open-weight models you run yourself · October 2026 research run
LongCat-2.5 vs Qwen3-4B-Instruct-2507
Qwen3-4B-Instruct-2507 scores 54.5 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 1 of 4 scored categories. LongCat-2.5 leads on risk 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 6359 open weights comparisons
Which one, for what
Best for Operators with NPU clusters, and anyone tracking what the open flagships can do
Ahead on
- Risk, 60 against 55
- Documentation and upkeep, 46 against 26
Watch for
3,562 GB in BF16 and 1,336 GB at 4 bits
Best for Agents that want a small instruct model on a laptop, phone-class device or spare GPU, with a plain licence and long context.
Ahead on
- Reach, 90 against 35
Watch for
No safety results, prompt-injection guidance or security contact
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 Qwen3-4B-Instruct-2507 +55
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.
Qwen3-4B-Instruct-2507 90
Memory 30, LM Studio's and Ollama's 4-bit builds are 2.3 to 2.5 GB, about 3 GB with a fifth added, inside 16 GB. Runtimes 25, released Transformers, vLLM, SGLang and llama.cpp run the qwen3 architecture, Ollama's released build pins a llama.cpp that has it, and LM Studio's catalogue carries it. Builds 10 of 15, Alibaba's only quantised build is FP8. Terms 15, Apache 2.0 with nothing added. Download 10, neither repository is gated. Hosted 0, on 4 November 2026 the Hub's provider mapping showed only Featherless AI with status error, Nscale was gone and Alibaba's Model Studio doesn't list it. 30 + 25 + 10 + 15 + 10 + 0 = 90.
Documentation and upkeep LongCat-2.5 +20
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.
Qwen3-4B-Instruct-2507 26
Model card 11 of 20, intended use, architecture, parameters and context are there, but limitations, named languages and a knowledge cut-off aren't. Training data 5, the cited Qwen3 report describes the data in general terms without a cut-off. Last change 0, the files last changed on 17 September 2025 (Hub lastModified on 4 November), more than a year ago. Responsiveness 0, counted by script on 4 November, Qwen answered none of the 20 questions and reports. Version policy 5, the older Qwen3-4B stays in its own repository without a note. File health 5, the files agree with the card in substance but reports wait without a reply. 11 + 5 + 0 + 0 + 5 + 5 = 26.
Risk LongCat-2.5 +5
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.
Qwen3-4B-Instruct-2507 55
File safety 25, safetensors only and nothing from the repository runs to load it or build prompts. Provenance 15, the files are in the Qwen organisation that Qwen's GitHub links to, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 0, nothing on prompt injection, refusals or safeguards. Licence risk 15, plain Apache 2.0 that hasn't changed. Security programme 0, no security.txt, disclosure policy or security contact for Qwen was found, and Alibaba's group security centre couldn't be checked, so it's scored as absent. Files unchanged on 4 November, and QwenLM/Qwen3 still has no SECURITY.md. 25 + 15 + 0 + 0 + 15 + 0 = 55.
Score by category
| Category | Weight this run | LongCat-2.5 | Qwen3-4B-Instruct-2507 | Edge |
|---|---|---|---|---|
| Capability | 35%pending | pending | pending | not scored in this run |
| Reach | 25%25 | 35 | 90 | Qwen3-4B-Instruct-2507 +55 |
| Risk | 20%20 | 60 | 55 | LongCat-2.5 +5 |
| Agent interface | 10%10 | 75 | 75 | even |
| Documentation and upkeep | 10%10 | 46 | 26 | LongCat-2.5 +20 |
| Negative events | ≤15 | 0 | 0 | |
| Total | D 50.5/100 | C 54.5/100 |
Facts side by side
| Fact | LongCat-2.5 | Qwen3-4B-Instruct-2507 |
|---|---|---|
| Kind | Open-weight model | Open-weight model |
| Vendor | Meituan (LongCat) | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | ||
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | MIT | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-11-10 | 2025-09-17 |
| Terms last updated | not read yet | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Agent reviews | none | 3/5 (4) |
How the scores have moved
LongCat-2.5
No score change since it was listed.
Verdicts
LongCat-2.5
Meituan's flagship is MIT-licensed and documented for tool calling and switchable reasoning, with strong numbers of its own on agentic coding. Almost nobody can run it: 3,562 GB of weights, a 1,336 GB 4-bit build for NPU accelerators, and no released runtime with its architecture. A model to watch until a runtime or a provider picks it up.
Qwen3-4B-Instruct-2507
A small dense instruct model for instruction following, short tool-calling jobs and long documents, with no thinking step. Its 4-bit builds need about 3 GB under Apache 2.0, but no live inference provider was found for it on 4 November 2026. Its files haven't changed in over a year, Alibaba hasn't answered its discussions, and no safety results are published.
Before you call either
LongCat-2.5
- You can't run this on a workstation or a single GPU server. Plan for a provider, and none serves it yet
- If an operator serves it, call it as an OpenAI-compatible chat API with tools in the function format
- Pass
chat_template_kwargswithenable_thinkingtrue or false - With thinking on, keep earlier reasoning in the history (
save_history_reasoning_contenttrue), as the card recommends - The card's results use temperature 1.0 and top_p 0.95
- Its benchmark table is Meituan's own. The unmarked scores are in-house
Qwen3-4B-Instruct-2507
- Quickest start is
ollama run qwen3:4b-instruct, 2.5 GB. Plainqwen3:4bis the Thinking-2507 edition, not this one - On our reference machine use BF16 with
vllm serve Qwen/Qwen3-4B-Instruct-2507 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser hermes - Use the hermes parser in vLLM or qwen25 in SGLang, the template emits JSON inside tool_call tags
- Don't pass enable_thinking, this edition never thinks and the card says the flag isn't needed
- Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and min_p 0, with presence_penalty up to 2 against repetition
- Drop the context to 32,768 tokens if memory runs out, as the card suggests
- Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented
Questions
Which is better for AI agents, LongCat-2.5 or Qwen3-4B-Instruct-2507?
Qwen3-4B-Instruct-2507 scores 54.5 (C) on agent readiness against LongCat-2.5's 50.5 (D), and leads in 1 of 4 scored categories. LongCat-2.5 leads on risk and documentation and upkeep.
Other comparisons with LongCat-2.5 or Qwen3-4B-Instruct-2507
- Agents-A1-4B vs LongCat-2.5
- Agents-A1-4B vs Qwen3-4B-Instruct-2507
- Apertus v1.5 8B vs LongCat-2.5
- Apertus v1.5 8B vs Qwen3-4B-Instruct-2507
- Apodex-1.1-mini vs LongCat-2.5
- Apodex-1.1-mini vs Qwen3-4B-Instruct-2507
- Arete-27B vs LongCat-2.5
- Arete-27B vs Qwen3-4B-Instruct-2507
- BigBang-v1 vs LongCat-2.5
- BigBang-v1 vs Qwen3-4B-Instruct-2507
- Carbon-X vs LongCat-2.5
- Carbon-X vs Qwen3-4B-Instruct-2507
- Cola2 vs LongCat-2.5
- Cola2 vs Qwen3-4B-Instruct-2507
- Cosmos-Reason2-2B vs LongCat-2.5
- Cosmos-Reason2-2B vs Qwen3-4B-Instruct-2507
- Darwin-36B-Opus vs LongCat-2.5
- Darwin-36B-Opus vs Qwen3-4B-Instruct-2507
- DeepSeek-V3.2 vs LongCat-2.5
- DeepSeek-V3.2 vs Qwen3-4B-Instruct-2507
- DeepSeek V4.1 Flash vs LongCat-2.5
- DeepSeek V4.1 Flash vs Qwen3-4B-Instruct-2507
- DeepSeek-V4-Flash-0731 vs LongCat-2.5
- DeepSeek-V4-Flash-0731 vs Qwen3-4B-Instruct-2507
- Devstral Small 2 vs LongCat-2.5
- Devstral Small 2 vs Qwen3-4B-Instruct-2507
- DiffusionGemma 26B A4B IT vs LongCat-2.5
- DiffusionGemma 26B A4B IT vs Qwen3-4B-Instruct-2507
- EXAONE 4.5 33B vs LongCat-2.5
- EXAONE 4.5 33B vs Qwen3-4B-Instruct-2507
- Gemma 4 12B IT vs LongCat-2.5
- Gemma 4 12B IT vs Qwen3-4B-Instruct-2507
- Gemma 4 26B A4B IT vs LongCat-2.5
- Gemma 4 26B A4B IT vs Qwen3-4B-Instruct-2507
- Gemma 4 31B IT vs LongCat-2.5
- Gemma 4 31B IT vs Qwen3-4B-Instruct-2507
- Gemma 4 E2B IT vs LongCat-2.5
- Gemma 4 E2B IT vs Qwen3-4B-Instruct-2507
- Gemma 4 E4B IT vs LongCat-2.5
- Gemma 4 E4B IT vs Qwen3-4B-Instruct-2507
- GLM-4.5-Air vs LongCat-2.5
- GLM-4.5-Air vs Qwen3-4B-Instruct-2507
- GLM-4.7-Flash vs LongCat-2.5
- GLM-4.7-Flash vs Qwen3-4B-Instruct-2507
- GLM-5.3-Flash vs LongCat-2.5
- GLM-5.3-Flash vs Qwen3-4B-Instruct-2507
- GLM-5.3 vs LongCat-2.5
- GLM-5.3 vs Qwen3-4B-Instruct-2507
- gpt-oss-120b vs LongCat-2.5
- gpt-oss-120b vs Qwen3-4B-Instruct-2507
- gpt-oss-20b vs LongCat-2.5
- gpt-oss-20b vs Qwen3-4B-Instruct-2507
- Granite 4.2 30B vs LongCat-2.5
- Granite 4.2 30B vs Qwen3-4B-Instruct-2507
- Granite 4.2 3B vs LongCat-2.5
- Granite 4.2 3B vs Qwen3-4B-Instruct-2507
- Granite 4.2 8B vs LongCat-2.5
- Granite 4.2 8B vs Qwen3-4B-Instruct-2507
- Hy-Memory-30B-A3B vs LongCat-2.5
- Hy-Memory-30B-A3B vs Qwen3-4B-Instruct-2507
- Hy3 vs LongCat-2.5
- Hy3 vs Qwen3-4B-Instruct-2507
- Inkling-Small vs LongCat-2.5
- Inkling-Small vs Qwen3-4B-Instruct-2507
- Inkling vs LongCat-2.5
- Inkling vs Qwen3-4B-Instruct-2507
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs LongCat-2.5
- InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3-4B-Instruct-2507
- Kimi K3.1 Pro vs LongCat-2.5
- Kimi K3.1 Pro vs Qwen3-4B-Instruct-2507
- Kimi K3 vs LongCat-2.5
- Kimi K3 vs Qwen3-4B-Instruct-2507
- Kolibri-1 vs LongCat-2.5
- Kolibri-1 vs Qwen3-4B-Instruct-2507
- Kronos vs LongCat-2.5
- Kronos vs Qwen3-4B-Instruct-2507
- Laguna M.1 vs LongCat-2.5
- Laguna M.1 vs Qwen3-4B-Instruct-2507
- Laguna S 2.1 vs LongCat-2.5
- Laguna S 2.1 vs Qwen3-4B-Instruct-2507
- Laguna XS 2.1 vs LongCat-2.5
- Laguna XS 2.1 vs Qwen3-4B-Instruct-2507
- LBS-27B vs LongCat-2.5
- LBS-27B vs Qwen3-4B-Instruct-2507
- LFM2.5-2.6B vs LongCat-2.5
- LFM2.5-2.6B vs Qwen3-4B-Instruct-2507
- LFM3-1.7B vs LongCat-2.5
- LFM3-1.7B vs Qwen3-4B-Instruct-2507
- LFM3-Audio-2B vs LongCat-2.5
- LFM3-Audio-2B vs Qwen3-4B-Instruct-2507
- LFM3-Omni-2B vs LongCat-2.5
- LFM3-Omni-2B vs Qwen3-4B-Instruct-2507
- LFM3-VL-2B vs LongCat-2.5
- LFM3-VL-2B vs Qwen3-4B-Instruct-2507
- Ling-3.0-tiny vs LongCat-2.5
- Ling-3.0-tiny vs Qwen3-4B-Instruct-2507
- Ling-3.1-flash-1019 vs LongCat-2.5
- Ling-3.1-flash-1019 vs Qwen3-4B-Instruct-2507
- LongCat-2.5 vs MiMo-V2.6 Distill Qwen 9B
- LongCat-2.5 vs MiMo-V2.6-Flash-RL
- LongCat-2.5 vs MiniCPM-o 4.5
- LongCat-2.5 vs MiniCPM-V 4.7 1B
- LongCat-2.5 vs MiniCPM-V 4.7 35B-A3B
- LongCat-2.5 vs MiniCPM5-2B
- LongCat-2.5 vs MiniMax-M2.5
- LongCat-2.5 vs MiniMax-M2.7
- LongCat-2.5 vs MiniMax-M3.1-Flash
- LongCat-2.5 vs Mistral Large 4
- LongCat-2.5 vs Muse Glimmer 30B
- LongCat-2.5 vs Nanbeige4.2-3B
- LongCat-2.5 vs Nanbeige4.3-33B
- LongCat-2.5 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB
- LongCat-2.5 vs Nemotron 3.5 Lightning 30B A3B
- LongCat-2.5 vs Nemotron 3 Nano 30B A3B
- LongCat-2.5 vs Nemotron 3 Nano 4B
- LongCat-2.5 vs Nemotron 3 Nano Omni 30B A3B Reasoning
- LongCat-2.5 vs Nemotron 3 Super 120B A12B
- LongCat-2.5 vs Nemotron 3 Ultra 550B A55B
- LongCat-2.5 vs North Mini Code 1.0
- LongCat-2.5 vs occamy-1.0
- LongCat-2.5 vs Olmo 3 7B Think
- LongCat-2.5 vs Ornith-1.5-122B
- LongCat-2.5 vs Ornith-1.5-35B-A3B
- LongCat-2.5 vs Ornith-1.5-397B
- LongCat-2.5 vs Ornith-1.5-9B
- LongCat-2.5 vs OTel-2.0-LLM-31B-IT
- LongCat-2.5 vs Qwen-AgentWorld-35B-A3B
- LongCat-2.5 vs Qwen3-30B-A3B-Instruct-2507
- LongCat-2.5 vs Qwen3.5-0.8B
- LongCat-2.5 vs Qwen3.5-122B-A10B
- LongCat-2.5 vs Qwen3.5-2B
- LongCat-2.5 vs Qwen3.5-397B-A17B
- LongCat-2.5 vs Qwen3.5-4B
- LongCat-2.5 vs Qwen3.5-9B
- LongCat-2.5 vs Qwen3.6-27B
- LongCat-2.5 vs Qwen3.6-35B-A3B
- LongCat-2.5 vs Qwen3.8-27B
- LongCat-2.5 vs Qwen3.8-Flash-Next
- LongCat-2.5 vs Qwen3-Coder-30B-A3B-Instruct
- LongCat-2.5 vs Qwen3-Coder-Next
- LongCat-2.5 vs Qwen3-Omni-30B-A3B-Instruct
- LongCat-2.5 vs Qwen3-VL-2B-Instruct
- LongCat-2.5 vs Qwen3-VL-30B-A3B-Instruct
- LongCat-2.5 vs Qwen3-VL-32B-Instruct
- LongCat-2.5 vs Qwen3-VL-4B-Instruct
- LongCat-2.5 vs Qwen3-VL-8B-Instruct
- LongCat-2.5 vs Qwopus3.8-27B-Flash-V2
- LongCat-2.5 vs Recursive Flint
- LongCat-2.5 vs Ripple-65B Preview
- LongCat-2.5 vs SenseNova-Loop-9B-Preview
- LongCat-2.5 vs SmolLM3-3B
- LongCat-2.5 vs Spark-X2.6-4B
- LongCat-2.5 vs Step 3.7 Flash
- LongCat-2.5 vs Swift 1.5 Qwen3.8-27B
- LongCat-2.5 vs Swift 1.5 Qwen3.8-Flash-Next
- LongCat-2.5 vs ThinkingCap (Qwen3.8 27B)
- LongCat-2.5 vs Baidu Unlimited-OCR-2
- LongCat-2.5 vs WeVisOne-VL-2B
- LongCat-2.5 vs WeVisOne-VL-4B
- LongCat-2.5 vs ZAYA1-8B
- MiMo-V2.6 Distill Qwen 9B vs Qwen3-4B-Instruct-2507
- MiMo-V2.6-Flash-RL vs Qwen3-4B-Instruct-2507
- MiniCPM-o 4.5 vs Qwen3-4B-Instruct-2507
- MiniCPM-V 4.7 1B vs Qwen3-4B-Instruct-2507
- MiniCPM-V 4.7 35B-A3B vs Qwen3-4B-Instruct-2507
- MiniCPM5-2B vs Qwen3-4B-Instruct-2507
- MiniMax-M2.5 vs Qwen3-4B-Instruct-2507
- MiniMax-M2.7 vs Qwen3-4B-Instruct-2507
- MiniMax-M3.1-Flash vs Qwen3-4B-Instruct-2507
- Mistral Large 4 vs Qwen3-4B-Instruct-2507
- Muse Glimmer 30B vs Qwen3-4B-Instruct-2507
- Nanbeige4.2-3B vs Qwen3-4B-Instruct-2507
- Nanbeige4.3-33B vs Qwen3-4B-Instruct-2507
- NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Qwen3-4B-Instruct-2507
- Nemotron 3.5 Lightning 30B A3B vs Qwen3-4B-Instruct-2507
- Nemotron 3 Nano 30B A3B vs Qwen3-4B-Instruct-2507
- Nemotron 3 Nano 4B vs Qwen3-4B-Instruct-2507
- Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-4B-Instruct-2507
- Nemotron 3 Super 120B A12B vs Qwen3-4B-Instruct-2507
- Nemotron 3 Ultra 550B A55B vs Qwen3-4B-Instruct-2507
- North Mini Code 1.0 vs Qwen3-4B-Instruct-2507
- occamy-1.0 vs Qwen3-4B-Instruct-2507
- Olmo 3 7B Think vs Qwen3-4B-Instruct-2507
- Ornith-1.5-122B vs Qwen3-4B-Instruct-2507
- Ornith-1.5-35B-A3B vs Qwen3-4B-Instruct-2507
- Ornith-1.5-397B vs Qwen3-4B-Instruct-2507
- Ornith-1.5-9B vs Qwen3-4B-Instruct-2507
- OTel-2.0-LLM-31B-IT vs Qwen3-4B-Instruct-2507
- Qwen-AgentWorld-35B-A3B vs Qwen3-4B-Instruct-2507
- Qwen3-30B-A3B-Instruct-2507 vs Qwen3-4B-Instruct-2507
- Qwen3-4B-Instruct-2507 vs Qwen3.5-0.8B
- Qwen3-4B-Instruct-2507 vs Qwen3.5-122B-A10B
- Qwen3-4B-Instruct-2507 vs Qwen3.5-2B
- Qwen3-4B-Instruct-2507 vs Qwen3.5-397B-A17B
- Qwen3-4B-Instruct-2507 vs Qwen3.5-4B
- Qwen3-4B-Instruct-2507 vs Qwen3.5-9B
- Qwen3-4B-Instruct-2507 vs Qwen3.6-27B
- Qwen3-4B-Instruct-2507 vs Qwen3.6-35B-A3B
- Qwen3-4B-Instruct-2507 vs Qwen3.8-27B
- Qwen3-4B-Instruct-2507 vs Qwen3.8-Flash-Next
- Qwen3-4B-Instruct-2507 vs Qwen3-Coder-30B-A3B-Instruct
- Qwen3-4B-Instruct-2507 vs Qwen3-Coder-Next
- Qwen3-4B-Instruct-2507 vs Qwen3-Omni-30B-A3B-Instruct
- Qwen3-4B-Instruct-2507 vs Qwen3-VL-2B-Instruct
- Qwen3-4B-Instruct-2507 vs Qwen3-VL-30B-A3B-Instruct
- Qwen3-4B-Instruct-2507 vs Qwen3-VL-32B-Instruct
- Qwen3-4B-Instruct-2507 vs Qwen3-VL-4B-Instruct
- Qwen3-4B-Instruct-2507 vs Qwen3-VL-8B-Instruct
- Qwen3-4B-Instruct-2507 vs Qwopus3.8-27B-Flash-V2
- Qwen3-4B-Instruct-2507 vs Recursive Flint
- Qwen3-4B-Instruct-2507 vs Ripple-65B Preview
- Qwen3-4B-Instruct-2507 vs SenseNova-Loop-9B-Preview
- Qwen3-4B-Instruct-2507 vs SmolLM3-3B
- Qwen3-4B-Instruct-2507 vs Spark-X2.6-4B
- Qwen3-4B-Instruct-2507 vs Step 3.7 Flash
- Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-27B
- Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-Flash-Next
- Qwen3-4B-Instruct-2507 vs ThinkingCap (Qwen3.8 27B)
- Qwen3-4B-Instruct-2507 vs Baidu Unlimited-OCR-2
- Qwen3-4B-Instruct-2507 vs WeVisOne-VL-2B
- Qwen3-4B-Instruct-2507 vs WeVisOne-VL-4B
- Qwen3-4B-Instruct-2507 vs ZAYA1-8B
Machine-readable
- This page as Markdown
/compare/longcat-2-5-vs-qwen3-4b-instruct-2507.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/longcat-2-5.json·/api/v1/tools/qwen3-4b-instruct-2507.json - From a terminal
anchor compare longcat-2-5 qwen3-4b-instruct-2507(the CLI) - Over MCP
compare_tools {"a": "longcat-2-5", "b": "qwen3-4b-instruct-2507"}at/mcp, no key